metode based learning problem solving

Problem-Based Learning (PBL)

What is Problem-Based Learning (PBL)? PBL is a student-centered approach to learning that involves groups of students working to solve a real-world problem, quite different from the direct teaching method of a teacher presenting facts and concepts about a specific subject to a classroom of students. Through PBL, students not only strengthen their teamwork, communication, and research skills, but they also sharpen their critical thinking and problem-solving abilities essential for life-long learning.

By working with PBL, students will:

Become engaged with open-ended situations that assimilate the world of work
Participate in groups to pinpoint what is known/ not known and the methods of finding information to help solve the given problem.
Investigate a problem; through critical thinking and problem solving, brainstorm a list of unique solutions.
Analyze the situation to see if the real problem is framed or if there are other problems that need to be solved.

How to Begin PBL

Establish the learning outcomes (i.e., what is it that you want your students to really learn and to be able to do after completing the learning project).
Find a real-world problem that is relevant to the students; often the problems are ones that students may encounter in their own life or future career.
Discuss pertinent rules for working in groups to maximize learning success.
Practice group processes: listening, involving others, assessing their work/peers.
Explore different roles for students to accomplish the work that needs to be done and/or to see the problem from various perspectives depending on the problem (e.g., for a problem about pollution, different roles may be a mayor, business owner, parent, child, neighboring city government officials, etc.).
Determine how the project will be evaluated and assessed. Most likely, both self-assessment and peer-assessment will factor into the assignment grade.

Designing Classroom Instruction

How to Orchestrate a PBL Activity

Explain Problem-Based Learning to students: its rationale, daily instruction, class expectations, grading.
Serve as a model and resource to the PBL process; work in-tandem through the first problem
Help students secure various resources when needed.
Supply ample class time for collaborative group work.
Give feedback to each group after they share via the established format; critique the solution in quality and thoroughness. Reinforce to the students that the prior thinking and reasoning process in addition to the solution are important as well.

Teacher’s Role in PBL

The Role of the Students

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Problem-Based Learning (PBL) is a teaching method in which complex real-world problems are used as the vehicle to promote student learning of concepts and principles as opposed to direct presentation of facts and concepts. In addition to course content, PBL can promote the development of critical thinking skills, problem-solving abilities, and communication skills. It can also provide opportunities for working in groups, finding and evaluating research materials, and life-long learning (Duch et al, 2001).

PBL can be incorporated into any learning situation. In the strictest definition of PBL, the approach is used over the entire semester as the primary method of teaching. However, broader definitions and uses range from including PBL in lab and design classes, to using it simply to start a single discussion. PBL can also be used to create assessment items. The main thread connecting these various uses is the real-world problem.

Any subject area can be adapted to PBL with a little creativity. While the core problems will vary among disciplines, there are some characteristics of good PBL problems that transcend fields (Duch, Groh, and Allen, 2001):

The problem must motivate students to seek out a deeper understanding of concepts.
The problem should require students to make reasoned decisions and to defend them.
The problem should incorporate the content objectives in such a way as to connect it to previous courses/knowledge.
If used for a group project, the problem needs a level of complexity to ensure that the students must work together to solve it.
If used for a multistage project, the initial steps of the problem should be open-ended and engaging to draw students into the problem.

The problems can come from a variety of sources: newspapers, magazines, journals, books, textbooks, and television/ movies. Some are in such form that they can be used with little editing; however, others need to be rewritten to be of use. The following guidelines from The Power of Problem-Based Learning (Duch et al, 2001) are written for creating PBL problems for a class centered around the method; however, the general ideas can be applied in simpler uses of PBL:

Choose a central idea, concept, or principle that is always taught in a given course, and then think of a typical end-of-chapter problem, assignment, or homework that is usually assigned to students to help them learn that concept. List the learning objectives that students should meet when they work through the problem.
Think of a real-world context for the concept under consideration. Develop a storytelling aspect to an end-of-chapter problem, or research an actual case that can be adapted, adding some motivation for students to solve the problem. More complex problems will challenge students to go beyond simple plug-and-chug to solve it. Look at magazines, newspapers, and articles for ideas on the story line. Some PBL practitioners talk to professionals in the field, searching for ideas of realistic applications of the concept being taught.
What will the first page (or stage) look like? What open-ended questions can be asked? What learning issues will be identified?
How will the problem be structured?
How long will the problem be? How many class periods will it take to complete?
Will students be given information in subsequent pages (or stages) as they work through the problem?
What resources will the students need?
What end product will the students produce at the completion of the problem?
Write a teacher's guide detailing the instructional plans on using the problem in the course. If the course is a medium- to large-size class, a combination of mini-lectures, whole-class discussions, and small group work with regular reporting may be necessary. The teacher's guide can indicate plans or options for cycling through the pages of the problem interspersing the various modes of learning.
The final step is to identify key resources for students. Students need to learn to identify and utilize learning resources on their own, but it can be helpful if the instructor indicates a few good sources to get them started. Many students will want to limit their research to the Internet, so it will be important to guide them toward the library as well.

The method for distributing a PBL problem falls under three closely related teaching techniques: case studies, role-plays, and simulations. Case studies are presented to students in written form. Role-plays have students improvise scenes based on character descriptions given. Today, simulations often involve computer-based programs. Regardless of which technique is used, the heart of the method remains the same: the real-world problem.

Where can I learn more?

PBL through the Institute for Transforming Undergraduate Education at the University of Delaware
Duch, B. J., Groh, S. E, & Allen, D. E. (Eds.). (2001). The power of problem-based learning . Sterling, VA: Stylus.
Grasha, A. F. (1996). Teaching with style: A practical guide to enhancing learning by understanding teaching and learning styles. Pittsburgh: Alliance Publishers.

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Evan Glazer (University of Georgia)

Editor’s Note: Dr. Glazer chose to use the term Problem-based Instruction and Inquiry, but my reading and other references to this chapter also use the term Problem-based Learning. The reader can assume the terms are equivalent.

Description

Problem-based inquiry is an effort to challenge students to address real-world problems and resolve realistic dilemmas.

Such problems create opportunities for meaningful activities that engage students in problem solving and higher-ordered thinking in authentic settings. Many textbooks attempt to promote these skills through contrived settings without relevance to students’ lives or interests. A notorious algebra problem concerns the time at which two railway trains will pass each other:

Two trains leave different stations headed toward each other. Station A is 500 miles west of Station B. Train A leaves station A at 12:00 pm traveling toward Station B at a rate of 60 miles per hour. Train B leaves Station B at 2:30 pm for Station A at a rate of 45 miles per hour. At what time will the trains meet?

Reading this question, one might respond, “Who cares?”, or, “Why do we need to know this?” Such questions have created substantial anxiety among students and have, perhaps, even been the cause of nightmares. Critics would argue that classic “story problems” leave a lasting impression of meaningless efforts to confuse and torment students, as if they have come from hell’s library. Problem-based inquiry, on the other hand, intends to engage students in relevant, realistic problems.

Several changes would need to be made in the above problem to promote problem-based inquiry. It would first have to be acknowledged that the trains are not, in fact, traveling at constant rates when they are in motion; negotiating curves or changing tracks at high speeds can result in accidents.

Further, all of the information about the problem cannot be presented to the learner at the outset; that is, some ambiguity must exist in the context so that students have an opportunity to engage in a problem-solving activity. In addition, the situation should involve a meaningful scenario. Suppose that a person intends to catch a connecting train at the second station and requires a time-efficient itinerary? What if we are not given data about the trains, but instead, the outcome of a particular event, such as an accident?

Why should we use problem-based inquiry to help students learn?

The American educational system has been criticized for having an underachieving curriculum that leads students to memorize and regurgitate facts that do not apply to their lives (Martin, 1987; Paul, 1993). Many claim that the traditional classroom environment, with its orderly conduct and didactic teaching methods in which the teacher dispenses information, has greatly inhibited students’ opportunities to think critically (Dossey et al., 1988; Goodlad, 1984; Wood, 1987). Problem-based inquiry is an attempt to overcome these obstacles and confront the concerns presented by the National Assessment of Educational Progress:

If an unfriendly foreign power had attempted to impose on America the mediocre educational performance that exists today, we might well have viewed it as an act of war. We have, in effect, been committing an act of unthinking, unilateral educational disarmament. (A Nation at Risk, 1983)

Problem-based inquiry emphasizes learning as a process that involves problem solving and critical thinking in situated contexts. It provides opportunities to address broader learning goals that focus on preparing students for active and responsible citizenship. Students gain experience in tackling realistic problems, and emphasis is placed on using communication, cooperation, and resources to formulate ideas and develop reasoning skills.

What is a framework for a problem-based inquiry?

Situated cognition, constructivism, social learning, and communities of practice are assumed theories of learning and cognition in problem-based inquiry environments. These theories have common themes about the context and the process of learning and are often associated.

Characteristics

Some common characteristics in problem-based learning models:

Activity is grounded in a general question about a problem that has multiple possible answers and methods for addressing the question. Each problem has a general question that guides the overall task followed by ill-structured problems or questions that are generated throughout the problem-solving process. That is, to address the larger question, students must derive and investigate smaller problems or questions that relate to the findings and implications of the broader goal. The problems or questions thus created are most likely new to the students and lack known definitive methods or answers that have been predetermined by the teacher.

Learning is student-centered; the teacher acts as facilitator. In essence, the teacher creates an environment where students take ownership in the direction and content of their learning.

Students work collaboratively towards addressing the general question . All of the students work together to attain the shared goal of producing a solution to the problem. Consequently, the groups co-depend on each other’s performance and contributions in order to make their own advances in reasoning toward answering the research questions and the overall problem.

Learning is driven by the context of the problem and is not bound by an established curriculum. In this environment, students determine what and how much they need to learn in order to accomplish a specific task. Consequently, acquired information and learned concepts and strategies are tied directly to the context of the learning situation. Learning is not confined to a preset curriculum. Creation of a final product is not a necessary requirement of all problem-based inquiry models.

Project-based learning models most often include this type of product as an integral part of the learning process, because learning is expected to occur primarily in the act of creating something. Unlike problem based inquiry models, project-based learning does not necessarily address a real-world problem, nor does it focus on providing argumentation for resolution of an issue.

In a problem-based inquiry setting, there is greater emphasis on problem-solving, analysis, resolution, and explanation of an authentic dilemma. Sometimes this analysis and explanation is represented in the form of a project, but it can also take the form of verbal debate and written summary.

Instructional models and applications

There is no single method for designing problem-based inquiry learning environments.

Various techniques have been used to generate the problem and stimulate learning. Promoting student-ownership, using a particular medium to focus attention, telling stories, simulating and recreating events, and utilizing resources and data on the Internet are among them. The instructional model, problem based learning will be discussed next with attention to instructional strategies and practical examples.

Problem-Based Learning

Problem-based learning (PBL) is an instructional strategy in which students actively resolve complex problems in realistic situations.

It can be used to teach individual lessons, units, or even entire curricula. PBL is often approached in a team environment with emphasis on building skills related to consensual decision making, dialogue and discussion, team maintenance, conflict management, and team leadership. While the fundamental approach of problem solving in situated environments has been used throughout the history of schooling, the term PBL did not appear until the 1970s and was devised as an alternative approach to medical education.

In most medical programs, students initially take a series of fact intensive courses in biology and anatomy and then participate in a field experience as a medical resident in a hospital or clinic. However, Barrows reported that, unfortunately, medical residents frequently had difficulty applying knowledge from their classroom experiences in work-related, problem-solving situations. He argued that the classical framework of learning medical knowledge first in classrooms through studying and testing was too passive and removed from context to take on meaning.

Consequently, PBL was first seen as a medical field immersion experience whereby students learned about their medical specialty through direct engagement in realistic problems and gradual apprenticeship in natural or simulated settings. Problem solving is emphasized as an initial area of learning and development in PBL medical programs more so than memorizing a series of facts outside their natural context.

In addition to the field of medicine, PBL is used in many areas of education and training. In academic courses, PBL is used as a tool to help students understand the utility of a particular concept or study. For example, students may learn about recycling and materials as they determine methods that will reduce the county landfill problem.

In addition, alternative education programs have been created with a PBL emphasis to help at-risk students learn in a different way through partnerships with local businesses and government. In vocational education, PBL experiences often emphasize participation in natural settings.

For example, students in architecture address the problem of designing homes for impoverished areas. Many of the residents need safe housing and cannot afford to purchase typical homes. Consequently, students learn about architectural design and resolving the problem as they construct homes made from recycled materials. In business and the military, simulations are used as a means of instruction in PBL. The affective and physiological stress associated with warfare can influence strategic planning, so PBL in military settings promotes the use of “war games” as a tactic for facing authentic crises.

In business settings, simulations of “what if” scenarios are used to train managers in various strategies and problem-solving approaches to conflict resolution. In both military and business settings, the simulation is a tool that provides an opportunity to not only address realistic problems but to learn from mistakes in a more forgiving way than in an authentic context.

Designing the learning environment

The following elements are commonly associated with PBL activities.

Problem generation: The problems must address concepts and principles relevant to the content domain. Problems are not investigated by students solely for problem solving experiences but as a means of understanding the subject area. Some PBL activities incorporate multidisciplinary approaches, assuming the teacher can provide and coordinate needed resources such as additional content, instructional support, and other teachers. In addition, the problems must relate to real issues that are present in society or students’ lives. Contrived scenarios detract from the perceived usefulness of a concept.

Problem presentation: Students must “own” the problem, either by creating or selecting it. Ownership also implies that their contributions affect the outcome of solving the problem. Thus, more than one solution and more than one method of achieving a solution to the problem are often possible. Furthermore, ownership means that students take responsibility for representing and communicating their work in a unique way.

Predetermined formats of problem structure and analysis towards resolution are not recommended; however, the problem should be presented such that the information in the problem does not call attention to critical factors in the case that will lead to immediate resolution. Ownership also suggests that students will ask further questions, reveal further information, and synthesize critical factors throughout the problem-solving process.

Teacher role: Teachers act primarily as cognitive coaches by facilitating learning and modeling higher order thinking and meta cognitive skills. As facilitators, teachers give students control over how they learn and provide support and structure in the direction of their learning. They help the class create a common framework of expectations using tools such as general guidelines and time lines.

As cognitive modelers, teachers think aloud about strategies and questions that influence how students manage the progress of their learning and accomplish group tasks. In addition, teachers continually question students about the concepts they are learning in the context of the problem in order to probe their understanding, challenge their thinking, and help them deepen or extend their ideas.

Student role: Students first define or select an ill-structured problem that has no obvious solution. They develop alternative hypotheses to resolve the problem and discuss and negotiate their conjectures in a group. Next, they access, evaluate, and utilize data from a variety of available sources to support or refute their hypotheses. They may alter, develop, or synthesize hypotheses in light of new information. Finally, they develop clearly stated solutions that fit the problem and its inherent conditions, based upon information and reasoning to support their arguments. Solutions can be in the form of essays, presentations, or projects.

Maine School Engages Kids With Problem-Solving Challenges (11:37)

https://youtu.be/i17F-b5GG94

[PBS NewsHour].(2013, May 6). Maine School Engages Kids with Problem Solving Challenges. [Video File]. Retrieve from https://youtu.be/i17F-b5GG94

Special correspondent John Tulenko of Leaning Matters reports on a public middle school in Portland, Maine that is taking a different approach to teaching students. Teachers have swapped traditional curriculum for an unusually comprehensive science curriculum that emphasizes problem-solving, with a little help from some robots.

Effectiveness of Problem and Inquiry-based learning.

Why does inquiry-based learning only have an effect size of 0.31 when it is an approach to learning that seems to engage students and teachers so readily in the process of learning?

When is the right and wrong time to introduce inquiry and problem based learning?

Watch video from John Hattie on inquiry and problem-based learning, (2:11 minutes).

[Corwin]. (2015, Nov. 9). John Hattie on inquiry-based learning. [Video File]. Retrieved from https://youtu.be/YUooOYbgSUg.

Glazer, E. (2010) Emerging Perspectives on Learning, Teaching, and Technology, Global Text, Michael Orey. (Chapter 14) Attribution CC 3.0. Retrieved from https://textbookequity.org/Textbooks/Orey_Emerging_Perspectives_Learning.pdf

Instructional Methods, Strategies and Technologies to Meet the Needs of All Learners Copyright © 2017 by Evan Glazer (University of Georgia) is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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International Handbook of Psychology Learning and Teaching pp 1235–1253 Cite as

Problem-Based Learning and Case-Based Learning

Joerg Zumbach 5 &
Claudia Prescher 6
Reference work entry
First Online: 17 December 2022

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Part of the book series: Springer International Handbooks of Education ((SIHE))

Problem-based learning (PBL) is a learner-centered small-group learning approach that supports active learning. This chapter provides core definitions of PBL and other forms of case-based learning. To be precise, several aspects of designing PBL are described, such as problem design, process structure, small-group learning, tutoring, and others. Research and evaluation of PBL compared to traditional approaches are summarized mostly based on meta-analyses.

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Zumbach, J., Prescher, C. (2023). Problem-Based Learning and Case-Based Learning. In: Zumbach, J., Bernstein, D.A., Narciss, S., Marsico, G. (eds) International Handbook of Psychology Learning and Teaching. Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-030-28745-0_58

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Problem based learning: a teacher's guide

December 10, 2021

Find out how teachers use problem-based learning models to improve engagement and drive attainment.

Main, P (2021, December 10). Problem based learning: a teacher's guide. Retrieved from https://www.structural-learning.com/post/problem-based-learning-a-teachers-guide

What is problem-based learning?

Problem-based learning (PBL) is a style of teaching that encourages students to become the drivers of their learning process . Problem-based learning involves complex learning issues from real-world problems and makes them the classroom's topic of discussion ; encouraging students to understand concepts through problem-solving skills rather than simply learning facts. When schools find time in the curriculum for this style of teaching it offers students an authentic vehicle for the integration of knowledge .

Embracing this pedagogical approach enables schools to balance subject knowledge acquisition with a skills agenda . Often used in medical education, this approach has equal significance in mainstream education where pupils can apply their knowledge to real-life problems.

PBL is not only helpful in learning course content , but it can also promote the development of problem-solving abilities , critical thinking skills , and communication skills while providing opportunities to work in groups , find and analyse research materials , and take part in life-long learning .

PBL is a student-centred teaching method in which students understand a topic by working in groups. They work out an open-ended problem , which drives the motivation to learn. These sorts of theories of teaching do require schools to invest time and resources into supporting self-directed learning. Not all curriculum knowledge is best acquired through this process, rote learning still has its place in certain situations. In this article, we will look at how we can equip our students to take more ownership of the learning process and utilise more sophisticated ways for the integration of knowledge .

Philosophical Underpinnings of PBL

Problem-Based Learning (PBL), with its roots in the philosophies of John Dewey, Maria Montessori, and Jerome Bruner, aligns closely with the social constructionist view of learning. This approach positions learners as active participants in the construction of knowledge, contrasting with traditional models of instruction where learners are seen as passive recipients of information.

Dewey, a seminal figure in progressive education, advocated for active learning and real-world problem-solving, asserting that learning is grounded in experience and interaction. In PBL, learners tackle complex, real-world problems, which mirrors Dewey's belief in the interconnectedness of education and practical life.

Montessori also endorsed learner-centric, self-directed learning, emphasizing the child's potential to construct their own learning experiences. This parallels with PBL’s emphasis on self-directed learning, where students take ownership of their learning process.

Jerome Bruner’s theories underscored the idea of learning as an active, social process. His concept of a 'spiral curriculum' – where learning is revisited in increasing complexity – can be seen reflected in the iterative problem-solving process in PBL.

Webb’s Depth of Knowledge (DOK) framework aligns with PBL as it encourages higher-order cognitive skills. The complex tasks in PBL often demand analytical and evaluative skills (Webb's DOK levels 3 and 4) as students engage with the problem, devise a solution, and reflect on their work.

The effectiveness of PBL is supported by psychological theories like the information processing theory, which highlights the role of active engagement in enhancing memory and recall. A study by Strobel and Van Barneveld (2009) found that PBL students show improved retention of knowledge, possibly due to the deep cognitive processing involved.

As cognitive scientist Daniel Willingham aptly puts it, "Memory is the residue of thought." PBL encourages learners to think critically and deeply, enhancing both learning and retention.

Here's a quick overview:

John Dewey : Emphasized learning through experience and the importance of problem-solving.
Maria Montessori : Advocated for child-centered, self-directed learning.
Jerome Bruner : Underlined learning as a social process and proposed the spiral curriculum.
Webb’s DOK : Supports PBL's encouragement of higher-order thinking skills.
Information Processing Theory : Reinforces the notion that active engagement in PBL enhances memory and recall.

This deep-rooted philosophical and psychological framework strengthens the validity of the problem-based learning approach, confirming its beneficial role in promoting valuable cognitive skills and fostering positive student learning outcomes.

What are the characteristics of problem-based learning?

Adding a little creativity can change a topic into a problem-based learning activity. The following are some of the characteristics of a good PBL model:

The problem encourages students to search for a deeper understanding of content knowledge;
Students are responsible for their learning. PBL has a student-centred learning approach . Students' motivation increases when responsibility for the process and solution to the problem rests with the learner;
The problem motivates pupils to gain desirable learning skills and to defend well-informed decisions ;
The problem connects the content learning goals with the previous knowledge. PBL allows students to access, integrate and study information from multiple disciplines that might relate to understanding and resolving a specific problem—just as persons in the real world recollect and use the application of knowledge that they have gained from diverse sources in their life.
In a multistage project, the first stage of the problem must be engaging and open-ended to make students interested in the problem. In the real world, problems are poorly-structured. Research suggests that well-structured problems make students less invested and less motivated in the development of the solution. The problem simulations used in problem-based contextual learning are less structured to enable students to make a free inquiry.

In a group project, the problem must have some level of complexity that motivates students towards knowledge acquisition and to work together for finding the solution. PBL involves collaboration between learners. In professional life, most people will find themselves in employment where they would work productively and share information with others. PBL leads to the development of such essential skills . In a PBL session, the teacher would ask questions to make sure that knowledge has been shared between pupils;
At the end of each problem or PBL, self and peer assessments are performed. The main purpose of assessments is to sharpen a variety of metacognitive processing skills and to reinforce self-reflective learning.
Student assessments would evaluate student progress towards the objectives of problem-based learning. The learning goals of PBL are both process-based and knowledge-based. Students must be assessed on both these dimensions to ensure that they are prospering as intended from the PBL approach. Students must be able to identify and articulate what they understood and what they learned.

Why is Problem-based learning a significant skill?

Using Problem-Based Learning across a school promotes critical competence, inquiry , and knowledge application in social, behavioural and biological sciences. Practice-based learning holds a strong track record of successful learning outcomes in higher education settings such as graduates of Medical Schools.

Educational models using PBL can improve learning outcomes by teaching students how to implement theory into practice and build problem-solving skills. For example, within the field of health sciences education, PBL makes the learning process for nurses and medical students self-centred and promotes their teamwork and leadership skills. Within primary and secondary education settings, this model of teaching, with the right sort of collaborative tools , can advance the wider skills development valued in society.

At Structural Learning, we have been developing a self-assessment tool designed to monitor the progress of children. Utilising these types of teaching theories curriculum wide can help a school develop the learning behaviours our students will need in the workplace.

Curriculum wide collaborative tools include Writers Block and the Universal Thinking Framework . Along with graphic organisers, these tools enable children to collaborate and entertain different perspectives that they might not otherwise see. Putting learning in action by using the block building methodology enables children to reach their learning goals by experimenting and iterating.

Scaffolding problem based learning with classroom tools

How is problem-based learning different from inquiry-based learning?

The major difference between inquiry-based learning and PBL relates to the role of the teacher . In the case of inquiry-based learning, the teacher is both a provider of classroom knowledge and a facilitator of student learning (expecting/encouraging higher-order thinking). On the other hand, PBL is a deep learning approach, in which the teacher is the supporter of the learning process and expects students to have clear thinking, but the teacher is not the provider of classroom knowledge about the problem—the responsibility of providing information belongs to the learners themselves.

As well as being used systematically in medical education, this approach has significant implications for integrating learning skills into mainstream classrooms .

Using a critical thinking disposition inventory, schools can monitor the wider progress of their students as they apply their learning skills across the traditional curriculum. Authentic problems call students to apply their critical thinking abilities in new and purposeful ways. As students explain their ideas to one another, they develop communication skills that might not otherwise be nurtured.

Depending on the curriculum being delivered by a school, there may well be an emphasis on building critical thinking abilities in the classroom. Within the International Baccalaureate programs, these life-long skills are often cited in the IB learner profile . Critical thinking dispositions are highly valued in the workplace and this pedagogical approach can be used to harness these essential 21st-century skills.

What are the Benefits of Problem-Based Learning?

Student-led Problem-Based Learning is one of the most useful ways to make students drivers of their learning experience. It makes students creative, innovative, logical and open-minded. The educational practice of Problem-Based Learning also provides opportunities for self-directed and collaborative learning with others in an active learning and hands-on process. Below are the most significant benefits of problem-based learning processes:

Self-learning: As a self-directed learning method, problem-based learning encourages children to take responsibility and initiative for their learning processes . As children use creativity and research, they develop skills that will help them in their adulthood.
Engaging : Students don't just listen to the teacher, sit back and take notes. Problem-based learning processes encourages students to take part in learning activities, use learning resources , stay active , think outside the box and apply critical thinking skills to solve problems.
Teamwork : Most of the problem-based learning issues involve students collaborative learning to find a solution. The educational practice of PBL builds interpersonal skills, listening and communication skills and improves the skills of collaboration and compromise.
Intrinsic Rewards: In most problem-based learning projects, the reward is much bigger than good grades. Students gain the pride and satisfaction of finding an innovative solution, solving a riddle, or creating a tangible product.
Transferable Skills: The acquisition of knowledge through problem-based learning strategies don't just help learners in one class or a single subject area. Students can apply these skills to a plethora of subject matter as well as in real life.
Multiple Learning Opportunities : A PBL model offers an open-ended problem-based acquisition of knowledge, which presents a real-world problem and asks learners to come up with well-constructed responses. Students can use multiple sources such as they can access online resources, using their prior knowledge, and asking momentous questions to brainstorm and come up with solid learning outcomes. Unlike traditional approaches , there might be more than a single right way to do something, but this process motivates learners to explore potential solutions whilst staying active.

Solving authentic problems using problem based learning

Embracing problem-based learning

Problem-based learning can be seen as a deep learning approach and when implemented effectively as part of a broad and balanced curriculum , a successful teaching strategy in education. PBL has a solid epistemological and philosophical foundation and a strong track record of success in multiple areas of study. Learners must experience problem-based learning methods and engage in positive solution-finding activities. PBL models allow learners to gain knowledge through real-world problems, which offers more strength to their understanding and helps them find the connection between classroom learning and the real world at large.

As they solve problems, students can evolve as individuals and team-mates. One word of caution, not all classroom tasks will lend themselves to this learning theory. Take spellings , for example, this is usually delivered with low-stakes quizzing through a practice-based learning model. PBL allows students to apply their knowledge creatively but they need to have a certain level of background knowledge to do this, rote learning might still have its place after all.

Key Concepts and considerations for school leaders

1. Problem Based Learning (PBL)

Problem-based learning (PBL) is an educational method that involves active student participation in solving authentic problems. Students are given a task or question that they must answer using their prior knowledge and resources. They then collaborate with each other to come up with solutions to the problem. This collaborative effort leads to deeper learning than traditional lectures or classroom instruction .

Key question: Inside a traditional curriculum , what opportunities across subject areas do you immediately see?

2. Deep Learning

Deep learning is a term used to describe the ability to learn concepts deeply. For example, if you were asked to memorize a list of numbers, you would probably remember the first five numbers easily, but the last number would be difficult to recall. However, if you were taught to understand the concept behind the numbers, you would be able to remember the last number too.

Key question: How will you make sure that students use a full range of learning styles and learning skills ?

3. Epistemology

Epistemology is the branch of philosophy that deals with the nature of knowledge . It examines the conditions under which something counts as knowledge.

Key question: As well as focusing on critical thinking dispositions, what subject knowledge should the students understand?

4. Philosophy

Philosophy is the study of general truths about human life. Philosophers examine questions such as “What makes us happy?”, “How should we live our lives?”, and “Why does anything exist?”

Key question: Are there any opportunities for embracing philosophical enquiry into the project to develop critical thinking abilities ?

5. Curriculum

A curriculum is a set of courses designed to teach specific subjects. These courses may include mathematics , science, social studies, language arts, etc.

Key question: How will subject leaders ensure that the integrity of the curriculum is maintained?

6. Broad and Balanced Curriculum

Broad and balanced curricula are those that cover a wide range of topics. Some examples of these types of curriculums include AP Biology, AP Chemistry, AP English Language, AP Physics 1, AP Psychology , AP Spanish Literature, AP Statistics, AP US History, AP World History, IB Diploma Programme, IB Primary Years Program, IB Middle Years Program, IB Diploma Programme .

Key question: Are the teachers who have identified opportunities for a problem-based curriculum?

7. Successful Teaching Strategy

Successful teaching strategies involve effective communication techniques, clear objectives, and appropriate assessments. Teachers must ensure that their lessons are well-planned and organized. They must also provide opportunities for students to interact with one another and share information.

Key question: What pedagogical approaches and teaching strategies will you use?

8. Positive Solution Finding

Positive solution finding is a type of problem-solving where students actively seek out answers rather than passively accept what others tell them.

Key question: How will you ensure your problem-based curriculum is met with a positive mindset from students and teachers?

9. Real World Application

Real-world application refers to applying what students have learned in class to situations that occur in everyday life.

Key question: Within your local school community , are there any opportunities to apply knowledge and skills to real-life problems?

10. Creativity

Creativity is the ability to think of ideas that no one else has thought of yet. Creative thinking requires divergent thinking, which means thinking in different directions.

Key question: What teaching techniques will you use to enable children to generate their own ideas ?

11. Teamwork

Teamwork is the act of working together towards a common goal. Teams often consist of two or more people who work together to achieve a shared objective.

Key question: What opportunities are there to engage students in dialogic teaching methods where they talk their way through the problem?

12. Knowledge Transfer

Knowledge transfer occurs when teachers use their expertise to help students develop skills and abilities .

Key question: Can teachers be able to track the success of the project using improvement scores?

13. Active Learning

Active learning is any form of instruction that engages students in the learning process. Examples of active learning include group discussions, role-playing, debates, presentations, and simulations .

Key question: Will there be an emphasis on learning to learn and developing independent learning skills ?

14. Student Engagement

Student engagement is the degree to which students feel motivated to participate in academic activities.

Key question: Are there any tools available to monitor student engagement during the problem-based curriculum ?

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Classroom Practice

The Comprehensive Guide to Project-Based Learning: Empowering Student Choice through an Effective Teaching Method

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Resources and Tools

In K-12 education, project-based learning (PBL) has gained momentum as an effective inquiry-based, teaching strategy that encourages students to take ownership of their learning journey.

By integrating authentic projects into the curriculum, project-based learning fosters active engagement, critical thinking, and problem-solving skills. This comprehensive guide explores the principles, benefits, implementation strategies, and evaluation techniques associated with project-based instruction, highlighting its emphasis on student choice and its potential to revolutionize education.

What is Project-Based Learning?

Project-based learning (PBL) is a inquiry-based and learner-centered instructional approach that immerses students in real-world projects that foster deep learning and critical thinking skills. Project-based learning can be implemented in a classroom as single or multiple units or it can be implemented across various subject areas and school-wide.

New Tech Network Elementary School Students

In contrast to teacher led instruction, project-based learning encourages student engagement, collaboration, and problem-solving, empowering students to become active participants in their own learning. Students collaborate to solve a real world problem that requires content knowledge, critical thinking, creativity, and communication skills.

Students aren’t only assessed on their understanding of academic content but on their ability to successfully apply that content when solving authentic problems. Through this process, project-based learning gives students the opportunity to develop the real-life skills required for success in today’s world.

Positive Impacts of Project-Based Learning

By integrating project-based learning into the classroom, educators can unlock a multitude of benefits for students. The research evidence overwhelmingly supports the positive impact of PBL on students, teachers, and school communities. According to numerous studies (see Deutscher et al, 2021 ; Duke et al, 2020 ; Krajick et al, 2022 ; Harris et al, 2015 ) students in PBL classrooms not only outperform non-PBL classrooms academically, such as on state tests and AP exams, but also the benefits of PBL extend beyond academic achievement, as students develop essential skills, including creativity, collaboration, communication, and critical thinking. Additional studies documenting the impact of PBL on K-12 learning are available in the PBL research annotated bibliography on the New Tech Network website.

New Tech Network Project-Based Learning Impacts

Established in 1996, New Tech Network NTN is a leading nonprofit organization dedicated to transforming teaching and learning through innovative instructional practices, with project-based learning at its core.

NTN has an extensive network of schools across the United States that have embraced the power of PBL to engage students in meaningful, relevant, and challenging projects, with professional development to support teachers in deepening understanding of “What is project-based learning?” and “How can we deliver high quality project-based learning to all students?”

With over 20 years of experience in project-based learning, NTN schools have achieved impactful results. Several research studies documented that students in New Tech Network schools outperform their peers in non-NTN schools on SAT/ACT tests and state exams in both math and reading (see Hinnant-Crawford & Virtue, 2019 ; Lynch et al, 2018 ; Stocks et al, 2019 ). Additionally, students in NTN schools are more engaged and more likely to develop skills in collaboration, agency, critical thinking, and communication—skills highly valued in today’s workforce (see Ancess & Kafka, 2020 ; Muller & Hiller, 2020 ; Zeiser, Taylor, et al, 2019 ).

Research conducted at an NTN school within a school documented the positive impact of interdisciplinary courses on the learning environment and academic outcomes. NTN students consistently out-performed their main campus peers on high school graduation rates.

NTN provides comprehensive support to educators, including training, resources, and ongoing coaching, to ensure the effective implementation of problem-based learning and project-based learning. Through their collaborative network, NTN continuously shares best practices, fosters innovation, enables replication across districts, and empowers educators to create transformative learning experiences for their students (see Barnett et al, 2020 ; Hernández et al, 2019 ).

Key Concepts of Project-Based Learning

Project-based learning is rooted in several key principles that distinguish it from other teaching methods. The pedagogical theories that underpin project-based learning and problem-based learning draw from constructivism and socio-cultural learning. Constructivism posits that learners construct knowledge through active learning and real world applications. Project-based learning aligns with this theory by providing students with opportunities to actively construct knowledge through inquiry, hands-on projects, real-world contexts, and collaboration.

Students as active participants

Project-based learning is characterized by learner-centered, inquiry-based, real world learning, which encourages students to take an active role in their own learning. Instead of rote memorization of information, students engage in meaningful learning opportunities, exercise voice and choice, and develop student agency skills. This empowers students to explore their interests, make choices, and take ownership of their learning process, with teachers acting as facilitators rather than the center of instruction.

Real-world and authentic contexts

Project-based learning emphasizes real-world problems that encourage students to connect academic content to meaningful contexts, enabling students to see the practical application of what they are learning. By tackling personally meaningful projects and engaging in hands-on tasks, students develop a deeper understanding of the subject matter and its relevance in their lives.

Collaboration and teamwork

Another essential element of project-based learning is collaborative work. Students collaborating with their peers towards the culmination of a project, mirrors real-world scenarios where teamwork and effective communication are crucial. Through collaboration, students develop essential social and emotional skills, learn from diverse perspectives, and engage in constructive dialogue.

Project-based learning embodies student-centered learning, real-world relevance, and collaborative work. These principles, rooted in pedagogical theories like constructivism, socio-cultural learning, and experiential learning, create a powerful learning environment, across multiple academic domains, that foster active engagement, thinking critically, and the development of essential skills for success in college or career or life beyond school.

A Unique Approach to Project-Based Learning: New Tech Network

New Tech Network schools are committed to these key focus areas: college and career ready outcomes, supportive and inclusive culture, meaningful and equitable instruction, and purposeful assessment.

In the New Tech Network Model, rigorous project-based learning allows students to engage with material in creative, culturally relevant ways, experience it in context, and share their learning with peers.

Why Undertake this Work?

Teachers, administrators, and district leaders undertake this work because it produces critical thinkers, problem-solvers, and collaborators who are vital to the long-term health and wellbeing of our communities.

Reynoldsburg City Schools (RCS) Superintendent Dr. Melvin J. Brown observed that “Prior to (our partnership with New Tech Network) we were just doing the things we’ve always done, while at the same time, our local industry was evolving and changing— and we were not changing with it. We recognized we had to do better to prepare kids for the reality they were going to walk into after high school and beyond.

Students embrace the Model because they feel a sense of belonging. They are challenged to learn in relevant, meaningful ways that shape the way they interact with the world, like these students from Owensboro Innovation Academy in Owensboro, Kentucky .

When change is collectively held and supported rather than siloed, and all stakeholders are engaged rather than alienated, schools and districts build their own capacity to sustain innovation and continuously improve. New Tech Network’s approach to change provides teachers, administrators, and district leaders with clear roles in adopting and adapting student-centered learning.

Part of NTN’s process for equipping schools with the data they need to serve their students involves conducting research surveys about their student’s experiences.

“The information we received back from our NTN surveys about our kids’ experiences was so powerful,” said Amanda Ziaer, Managing Director of Strategic Initiatives for Frisco ISD. “It’s so helpful to be reminded about these types of tactics when you’re trying to develop an authentic student-centered learning experience. It’s just simple things you might skip because we live in such a traditional adult-centered world.”

NTN’s experienced staff lead professional development activities that enable educators to adapt to student needs and strengths, and amplify those strengths while adjusting what is needed to address challenges.

Meaningful and Equitable Instruction

The New Tech Network model is centered on a PBL instructional core. PBL as an instructional method overlaps with key features of equitable pedagogical approaches including student voice, student choice, and authentic contexts. The New Tech Network model extends the power of PBL as a tool for creating more equitable learning by building asset-based equity pedagogical practices into the the design using key practices drawn from the literature on culturally sustaining teaching methods so that PBL instruction leverages the assets of diverse students, supports teachers as warm demanders, and develops critically conscious students in PBL classrooms (see Good teaching, warm and demanding classrooms, and critically conscious students: Measuring student perceptions of asset-based equity pedagogy in the classroom ).

Examples of Project-Based Learning

New Tech Network schools across the country create relevant projects and interdisciplinary learning that bring a learner-centered approach to their school. Examples of NTN Model PBL Projects are available in the NTN Help and Learning Center and enable educators to preview projects and gather project ideas from various grade levels and content areas.

The NTN Project Planning Toolkit is used as a guide in the planning and design of PBL. The Project-based learning examples linked above include a third grade Social Studies/ELA project, a seventh grade Science project, and a high school American Studies project (11th grade English Language Arts/American History).

The Role of Technology in Project-Based Learning

A tool for creativity

Technology plays a vital role in enhancing PBL in schools, facilitating student engagement, collaboration, and access to information. At the forefront, technology provides students with tools and resources to research, analyze data, and create multimedia content for their projects.

A tool for collaboration

Technology tools enable students to express their understanding creatively through digital media, such as videos, presentations, vlogs, blogs and interactive websites, enhancing their communication and presentation skills.

A tool for feedback

Technology offers opportunities for authentic audiences and feedback. Students can showcase their projects to a global audience through online platforms, blogs, or social media, receiving feedback and perspectives from beyond the classroom. This authentic audience keeps students engaged and striving for high-quality work and encourages them to take pride in their accomplishments.

By integrating technology into project-based learning, educators can enhance student engagement, deepen learning, and prepare students for a digitally interconnected world.

Interactive PBL Resources

New Tech Network offers a wealth of resources to support educators in gaining a deeper understanding of project-based learning. One valuable tool is the NTN Help Center, which provides comprehensive articles and resources on the principles and practices of implementing project-based learning.

Educators can explore project examples in the NTN Help Center to gain inspiration and practical insights into designing and implementing PBL projects that align with their curriculum and student needs.

Educators can start with the article “ What are the basic principles and practices of Project-Based Learning? Doing Projects vs. PBL . ” The image within the article clarifies the difference between the traditional education approach of “doing projects” and true project-based learning.

Project Launch

Students are introduced to a project by an Entry Event in the Project Launch (designated in purple on the image) this project component typically requires students to take on a role beyond that of ‘student’ or ‘learner’. This occurs either by placing students in a scenario that has real world applications, in which they simulate tasks performed by adults and/or by requiring learners to address a challenge or problem facing a particular community group.

The Entry Event not only introduces students to a project but also serves as the “hook” that purposefully engages students in the launch of a project. The Entry Event is followed by the Need to Know process in which students name what they already know about a topic and the project ask and what they “need to know” in order to solve the problem named in the project. Next steps are created which support students as they complete the Project Launch phase of a project.

Scaffolding

Shown in the image in red, facilitators ensure students gain content knowledge and skills through ‘scaffolding’. Scaffolding is defined as temporary supports for students to build the skills and knowledge needed to create the final product. Similar to scaffolding in building construction, it is removed when these supports are no longer needed by students.

Scaffolding can take the form of a teacher providing support by hosting small group workshops, students engaging in independent research or groups completing learner-centered activities, lab investigations, formative assessments and more.

Benchmarks (seen in orange in the image) can be checks for understanding that allow educators to give feedback on student work and/or checks to ensure students are progressing in the project as a team. After each benchmark, students should be given time to reflect on their individual goals as well as their team goals. Benchmarks are designed to build on each other to support project teams towards the culminating product at the end of the project.

NTN’s Help Center also provides resources on what effective teaching and learning look like within the context of project-based learning. The article “ What does effective teaching and learning look like? ” outlines the key elements of a successful project-based learning classroom, emphasizing learner-centered learning, collaborative work, and authentic assessments.

Educators can refer to this resource to gain insights into best practices, instructional strategies, and classroom management techniques that foster an engaging and effective project-based learning environment.

From understanding the principles and practices of PBL to accessing examples of a particular project, evaluating project quality, and exploring effective teaching and learning strategies, educators can leverage these resources to enhance their PBL instruction and create meaningful learning experiences for their students.

Preparing Students for the Future with PBL

The power of PBL is the way in which it encourages students to think critically, collaborate, and sharpen communication skills, which are all highly sought-after in today’s rapidly evolving workforce. By engaging in authentic, real-world projects, and collaborating with business and community leaders and community members, students develop the ability to tackle complex problems, think creatively, and adapt to changing circumstances.

New Tech Network graduate with a teacher

These skills are essential in preparing students for the dynamic and unpredictable nature of the future job market, where flexibility, innovation, and adaptability are paramount.

“Joining New Tech Network provides us an opportunity to reframe many things about the school, not just PBL,” said Bay City Public Schools Chief Academic Officer Patrick Malley. “Eliminating the deficit mindset about kids is the first step to establishing a culture that makes sure everyone in that school is focused on next-level readiness for these kids.”

The New Tech Network Learning Outcomes align with the qualities companies are looking for in new hires: Knowledge and Thinking, Oral Communication, Written Communication, Collaboration and Agency.

NTN schools prioritize equipping students with the necessary skills and knowledge to pursue postsecondary education or training successfully. By integrating college readiness and career readiness into the fabric of PBL, NTN ensures that students develop the academic, technical, and professional skills needed for future success.

Through authentic projects, students learn to engage in research, analysis, and presentation of their work, mirroring the expectations and demands of postsecondary education and the workplace. NTN’s commitment to college and career readiness ensures that students are well-prepared to transition seamlessly into higher education or enter the workforce with the skills and confidence to excel in their chosen paths.

The Impact of PBL on College and Career Readiness

PBL has a profound impact on college and career readiness. Numerous studies document the academic benefits for students, including performance in AP courses, SAT/ACT tests, and state exams (see Deutscher et al, 2021 ; Duke et al, 2020 ; Krajick et al, 2022 ; Harris et al, 2015 ). New Tech Network schools demonstrate higher graduation rates and college persistence rates than the national average as outlined in the New Tech Network 2022 Impact Report . Over 95% of NTN graduates reported feeling prepared for the expectations and demands of college.

Practices that Support Equitable College Access and Readiness

According to a literature review conducted by New York University’s Metropolitan Center for Research on Equity and the Transformation of Schools ( Perez et al, 2021 ) classroom level, school level, and district level practices can be implemented to create more equitable college access and readiness and these recommendations align with many of the practices built into the the NTN model, including culturally sustaining instructional approaches, foundational literacy, positive student-teacher relationships, and developing shared asset-based mindsets.

About New Tech Network

New Tech Network is committed to meeting schools and districts where they are and helping them achieve their vision of student success. For a full list of our additional paths to impact or to speak with someone about how the NTN Model can make an impact in your district, please send an email to [email protected] .

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Problem Solving in STEM

Solving problems is a key component of many science, math, and engineering classes. If a goal of a class is for students to emerge with the ability to solve new kinds of problems or to use new problem-solving techniques, then students need numerous opportunities to develop the skills necessary to approach and answer different types of problems. Problem solving during section or class allows students to develop their confidence in these skills under your guidance, better preparing them to succeed on their homework and exams. This page offers advice about strategies for facilitating problem solving during class.

How do I decide which problems to cover in section or class?

In-class problem solving should reinforce the major concepts from the class and provide the opportunity for theoretical concepts to become more concrete. If students have a problem set for homework, then in-class problem solving should prepare students for the types of problems that they will see on their homework. You may wish to include some simpler problems both in the interest of time and to help students gain confidence, but it is ideal if the complexity of at least some of the in-class problems mirrors the level of difficulty of the homework. You may also want to ask your students ahead of time which skills or concepts they find confusing, and include some problems that are directly targeted to their concerns.

You have given your students a problem to solve in class. What are some strategies to work through it?

Try to give your students a chance to grapple with the problems as much as possible. Offering them the chance to do the problem themselves allows them to learn from their mistakes in the presence of your expertise as their teacher. (If time is limited, they may not be able to get all the way through multi-step problems, in which case it can help to prioritize giving them a chance to tackle the most challenging steps.)
When you do want to teach by solving the problem yourself at the board, talk through the logic of how you choose to apply certain approaches to solve certain problems. This way you can externalize the type of thinking you hope your students internalize when they solve similar problems themselves.
Start by setting up the problem on the board (e.g you might write down key variables and equations; draw a figure illustrating the question). Ask students to start solving the problem, either independently or in small groups. As they are working on the problem, walk around to hear what they are saying and see what they are writing down. If several students seem stuck, it might be a good to collect the whole class again to clarify any confusion. After students have made progress, bring the everyone back together and have students guide you as to what to write on the board.
It can help to first ask students to work on the problem by themselves for a minute, and then get into small groups to work on the problem collaboratively.
If you have ample board space, have students work in small groups at the board while solving the problem. That way you can monitor their progress by standing back and watching what they put up on the board.
If you have several problems you would like to have the students practice, but not enough time for everyone to do all of them, you can assign different groups of students to work on different – but related - problems.

When do you want students to work in groups to solve problems?

Don’t ask students to work in groups for straightforward problems that most students could solve independently in a short amount of time.
Do have students work in groups for thought-provoking problems, where students will benefit from meaningful collaboration.
Even in cases where you plan to have students work in groups, it can be useful to give students some time to work on their own before collaborating with others. This ensures that every student engages with the problem and is ready to contribute to a discussion.

What are some benefits of having students work in groups?

Students bring different strengths, different knowledge, and different ideas for how to solve a problem; collaboration can help students work through problems that are more challenging than they might be able to tackle on their own.
In working in a group, students might consider multiple ways to approach a problem, thus enriching their repertoire of strategies.
Students who think they understand the material will gain a deeper understanding by explaining concepts to their peers.

What are some strategies for helping students to form groups?

Instruct students to work with the person (or people) sitting next to them.
Count off. (e.g. 1, 2, 3, 4; all the 1’s find each other and form a group, etc)
Hand out playing cards; students need to find the person with the same number card. (There are many variants to this. For example, you can print pictures of images that go together [rain and umbrella]; each person gets a card and needs to find their partner[s].)
Based on what you know about the students, assign groups in advance. List the groups on the board.
Note: Always have students take the time to introduce themselves to each other in a new group.

What should you do while your students are working on problems?

Walk around and talk to students. Observing their work gives you a sense of what people understand and what they are struggling with. Answer students’ questions, and ask them questions that lead in a productive direction if they are stuck.
If you discover that many people have the same question—or that someone has a misunderstanding that others might have—you might stop everyone and discuss a key idea with the entire class.

After students work on a problem during class, what are strategies to have them share their answers and their thinking?

Ask for volunteers to share answers. Depending on the nature of the problem, student might provide answers verbally or by writing on the board. As a variant, for questions where a variety of answers are relevant, ask for at least three volunteers before anyone shares their ideas.
Use online polling software for students to respond to a multiple-choice question anonymously.
If students are working in groups, assign reporters ahead of time. For example, the person with the next birthday could be responsible for sharing their group’s work with the class.
Cold call. To reduce student anxiety about cold calling, it can help to identify students who seem to have the correct answer as you were walking around the class and checking in on their progress solving the assigned problem. You may even want to warn the student ahead of time: "This is a great answer! Do you mind if I call on you when we come back together as a class?"
Have students write an answer on a notecard that they turn in to you. If your goal is to understand whether students in general solved a problem correctly, the notecards could be submitted anonymously; if you wish to assess individual students’ work, you would want to ask students to put their names on their notecard.
Use a jigsaw strategy, where you rearrange groups such that each new group is comprised of people who came from different initial groups and had solved different problems. Students now are responsible for teaching the other students in their new group how to solve their problem.
Have a representative from each group explain their problem to the class.
Have a representative from each group draw or write the answer on the board.

What happens if a student gives a wrong answer?

Ask for their reasoning so that you can understand where they went wrong.
Ask if anyone else has other ideas. You can also ask this sometimes when an answer is right.
Cultivate an environment where it’s okay to be wrong. Emphasize that you are all learning together, and that you learn through making mistakes.
Do make sure that you clarify what the correct answer is before moving on.
Once the correct answer is given, go through some answer-checking techniques that can distinguish between correct and incorrect answers. This can help prepare students to verify their future work.

How can you make your classroom inclusive?

The goal is that everyone is thinking, talking, and sharing their ideas, and that everyone feels valued and respected. Use a variety of teaching strategies (independent work and group work; allow students to talk to each other before they talk to the class). Create an environment where it is normal to struggle and make mistakes.
See Kimberly Tanner’s article on strategies to promoste student engagement and cultivate classroom equity.

A few final notes…

Make sure that you have worked all of the problems and also thought about alternative approaches to solving them.
Board work matters. You should have a plan beforehand of what you will write on the board, where, when, what needs to be added, and what can be erased when. If students are going to write their answers on the board, you need to also have a plan for making sure that everyone gets to the correct answer. Students will copy what is on the board and use it as their notes for later study, so correct and logical information must be written there.

For more information...

Tipsheet: Problem Solving in STEM Sections

Tanner, K. D. (2013). Structure matters: twenty-one teaching strategies to promote student engagement and cultivate classroom equity . CBE-Life Sciences Education, 12(3), 322-331.

Designing Your Course
A Teaching Timeline: From Pre-Term Planning to the Final Exam
The First Day of Class
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Problem-based learning as an instructional method

Affiliation.

1 Department of Anatomy and Cell Biology, College of Medicine, Alfaisal University, Riyadh, KSA. [email protected]
PMID: 23286630

Problem-based learning (PBL) methods have revolutionized the field of medical education, since its introduction almost 40 years ago. However, there are many un-answered questions on the benefits and effectiveness of PBL. The supporters and critics of PBL continue to dispute the merits of cognitive foundation of PBL based approach. This paper performs a literature review of the different systemic reviews and meta-analysis which have addressed the effectiveness of PBL. Evidence presented in these reviews show that PBL does not impact knowledge acquisition, but impacts application of knowledge. There is no unequivocal evidence in favour of PBL that it enhance learning. More work is needed to identify appropriate outcome measures in-order to analyze the effectiveness of PBL.

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Curriculum*
Education, Medical, Undergraduate / methods*
Problem-Based Learning*

Development of problem based learning (PBL) learning tools to improve mathematical problem solving ability of class VIII SMP/MTs students

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Novi Yendra , Ahmad Fauzan , Beni Junedi; Development of problem based learning (PBL) learning tools to improve mathematical problem solving ability of class VIII SMP/MTs students. AIP Conf. Proc. 7 February 2023; 2698 (1): 060011. https://doi.org/10.1063/5.0122385

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Data of preliminary analysis showed that students has low level ability of mathematical problem solving. It can be happened because students were less actively participating in learning process and learning tools that had been used not met the needs to increase students’ activity. The aims of this research is to develop Problem Based Learning (PBL) based learning tools, consist of Learning Implementation Plans (RPP) and Student Worksheets (LKPD) with criteria: valid, practical and effective. Type of research is development research by using Plomp model with three phases, i.e. preliminary research, development or prototyping and assessment. Preliminary research is done by analyzing the needs, curriculum, student characteristics and concept. Prototype stage is done by designing and determinant the validity and practicality of the product, by using formative evaluation. Assessment stage is to assess the practicality and effectiveness tests on VIII grade students at MTs PPM Al-Kautsar Muhammadiyah Sarilamak. Practical data were obtained from students' questionnaires. The effectiveness data were got from students’ final test mathematical problem solving. The results show that PBL-based learning tools are valid, practice (easy to use and understand), efficient, interesting, and contribute in learning. Mathematics problem solving tests show the result that the 83% students pass the passing grades score, viz. score 75.

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Model Pembelajaran Problem Solving (Penjelasan Lengkap)

Pengertian Model Pembelajaran Problem Solving

Model pembelajaran problem solving adalah model yang mengutamakan pemecahan masalah dalam kegiatan belajar untuk memperkuat daya nalar yang digunakan oleh peserta didik agar mendapatkan pemahaman yang lebih mendasar dari materi yang disampaikan. Seperti yang diungkapkan Pepkin (dalam Shoimin, 2017, hlm. 135) bahwa metode problem solving adalah suatu model pembelajaran yang melakukan pemusatan pada pengajaran dan keterampilan pemecahan masalah yang diikuti dengan penguatan keterampilan.

Problem solving dalam pembelajaran memegang peranan yang sangat penting. Mengapa? Karena dengan mengetahui cara menyelesaikan masalahnya, pembelajaran akan merekat jauh lebih dalam dan tidak mudah untuk dilupakan. Dampaknya hampir sama dengan pembelajaran kontekstual, karena pada akhirnya masalah adalah hal sehari-hari yang akan ditemui oleh siswa. Pemecahan masalah merupakan keterampilan penting yang dibutuhkan pada abad-21 .

Sementara itu Purwanto (dalam Chotimah & Fathurrohman, 2018, hlm. 280-281) berpendapat bahwa model problem solving adalah suatu proses dengan menggunakan strategi, cara, atau teknik tertentu untuk menghadapi situasi baru, agar keadaan tersebut dapat dilalui sesuai keinginan yang ditetapkan.

Model ini sering disebut sebagai metode pula karena boleh dibilang merupakan salah satu penerapan problem based learning (PBL) yang sudah memiliki langkah-langkah konkret. Namun di balik itu, metode ini juga cukup dinamis untuk dimodifikasi dan disesuaikan dengan keadaan siswa atau sekolah. Oleh karena sifatnya yang dinamis, terdapat berbagai turunan dari model ini, misalnya model pembelajaran creative problem solving .

Menurut Murray, Hanlie, et al. (dalam Huda, 2015, hlm. 273) model pembelajaran problem solving merupakan salah satu dasar teoretis dari berbagai strategi pembelajaran yang menjadikan masalah (problem) sebagai isu utamanya. Artinya akan terdapat beberapa tipe atau setting yang dapat dinaunginya.

Model problem solving adalah sebuah metode pembelajaran yang mengharuskan siswa berperan aktif dan mampu berpikir. Karena dalam problem solving siswa diharuskan mampu menganalisis materi mulai dengan mencari data sampai dengan menarik kesimpulan. Dapat disimpulkan bahwa model pembelajaran problem solving adalah model yang memusatkan pembelajaran pada pemecahan masalah sehingga siswa dapat memperkuat daya nalar dengan menyusun cara, strategi, atau teknik baru untuk menyelesaikan suatu permasalahan.

Lalu seperti apa prosedur, sintaks, atau langkah-langkah dari model ini? Berikut adalah penjelasannya.

Sintaks Pembelajaran Problem Solving

Terdapat sintaks atau acuan dasar dari seluruh fase yang harus dilakukan dalam menyelenggarakan model pembelajaran problem solving. Menurut Chotimah & Fathurrohman (2018, hlm. 287-288) sintaks model pembelajaran problem solving terdiri dari 6 tahap sebagai berikut.

Merumuskan masalah Kemampuan ini diperlukan untuk mengetahui dan merumuskan masalah secara jelas.
Menelaah masalah Untuk menggunakan model problem solving, menelaah masalah diperlukan agar peserta didik dapat menggunakan pengetahuan untuk memerinci dan menganalisis masalah dari berbagai sudut.
Merumuskan hipotesis Kemampuan yang diperlukan lainnya adalah berimajinasi dan menghayati ruang lingkup, sebab-akibat, dan alternatif penyelesaian.
Mengumpulkan dan mengelompokkan data (sebagai bahan pembuktian hipotesis) Tahap ini berfungsi untuk memancing kecakapan mencari dan menyusun data serta menyajikan data dalam bentuk diagram, gambar, atau tabel.
Pembuktian hipotesis Kecakapan menelaah dan membahas data, kecakapan menghubung-hubungkan dan menghitung, serta keterampilan mengambil keputusan dan kesimpulan.
Menentukan pilihan penyelesaian Tahap ini akan membuat peserta didik mampu untuk membuat alternatif penyelesaian serta kecakapan menilai pilihan dengan memperhitungkan akibat yang akan terjadi pada setiap pilihan.

Langkah Langkah Model Pembelajaran Problem Solving

Terdapat langkah-langkah konkret yang dapat digunakan untuk menyelenggarakan model pembelajaran problem solving. Langkah-langkah pembelajaran menggunakan model pembelajaran problem solving menurut Sani (2019, hlm. 243) adalah sebagai berikut.

Pendidik menjelaskan tujuan pembelajaran.
Guru memberikan permasalahan yang perlu dicari solusinya.
Pendidik (guru) menjelaskan prosedur pemecahan masalah yang benar.
Peserta didik mencari literatur yang mendukung untuk menyelesaikan permasalahan yang diberikan guru.
Siswa atau peserta didik menetapkan beberapa solusi yang dapat diambil untuk menyelesaikan permasalahan.
Peserta didik melaporkan tugas yang diberikan guru.

Tujuan Model Problem Solving

Dalam metode pembelajaran problem solving, pembelajaran tidak hanya difokuskan dalam upaya mendapatkan pengetahuan sebanyak-banyaknya. Justru bagaimana menggunakan segenap pengetahuan yang didapat tersebut adalah fokusnya. Dengan kata lain, model pembelajaran ini mengutamakan peningkatan keterampilan untuk menggunakan pengetahuan sebagiamana nantinya akan digunakan pada dunia nyata atau kehidupan sehari-hari.

Siswa yang dapat mengerjakan atau dapat memecahkan masalah yang diberikan oleh guru dapat dikatakan telah telah menguasai pelajaran dengan baik. Bersinggungan dengan hal tersebut, menurut Chotimah & Fathurrohman (2018, hlm. 282) tujuan dari pembelajaran problem solving adalah sebagai berikut.

Peserta didik menjadi terampil menyeleksi informasi yang relevan kemudian menganalisisnya dan akhirnya meneliti kembali hasilnya.
Kepuasan intelektual akan timbul dari dalam sebagai hasil intrinsik bagi peserta didik.
Potensi intelektual peserta didik meningkat.
Peserta didik belajar bagaimana melakukan penemuan dengan melalui proses melakukan penemuan.

Kelebihan dan Kekurangan Pembelajaran Problem Solving

Setiap model pembelajaran pasti mempunyai kelebihan masing-masing. Salah satunya yakni model pembelajaran problem solving yang tentunya mempunyai kelebihan dan kekurangan pula. Di bawah ini akan dipaparkan beberapa kelebihan dan kekurangan dari model ini.

Secara umum salah satu kelebihan dari model pembelajaran problem solving adalah meningkatnya daya kritis siswa dalam pembelajaran. Selain itu, menurut Shoimin (2017, hlm. 137-138) kelebihan dari model pembelajaran problem solving adalah sebagai berikut.

Membuat peserta didik lebih menghayati pembelajaran berdasarkan kehidupan sehari-hari.
Melatih dan membiasakan para peserta didik untuk menghadapi dan memecahkan masalah secara terampil.
Dapat mengembangkan kemampuan berpikir peserta didik secara kreatif.
Peserta didik sudah mulai dilatih untuk memecahkan masalahnya dari semenjak sekolah (sebelum memasuki kehidupan nyata).
Melatih siswa untuk mendesain suatu penemuan.
Membuat peserta didik berpikir dan bertindak kreatif.
Memecahkan masalah yang dihadapi secara realistis.
Mengidentifikasi dan melakukan penyelidikan.
Menafsirkan dan mengevaluasi hasil pengamatan.
Merangsang perkembangan kemajuan berpikir siswa untuk menyelesaikan masalah yang dihadapi dengan cara yang tepat.
Dapat membuat pendidikan sekolah lebih relevan dengan kehidupan, khususnya dunia kerja.

Sementara itu, menurut Sanjaya (2016, hlm. 220) keunggulan dari metode problem solving adalah sebagai berikut.

Merupakan teknik pembelajaran yang cukup bagus agar siswa lebih memahami isi pelajaran.
Menantang kemampuan siswa serta memberikan kepuasan untuk menemukan pengetahuan baru bagi siswa.
Dapat meningkatkan aktivitas pembelajaran siswa.
Membantu siswa bagaimana mentransfer pengetahuan mereka untuk memahami masalah dalam kehidupan nyata.
Dianggap lebih menyenangkan dan disukai siswa.

Menurut Sanjaya (2016, hlm. 220) kelemahan dari metode problem solving adalah sebagai berikut ini.

Manakala siswa tidak memiliki minat atau tidak mempunyai kepercayaan bahwa masalah yang dipelajari sulit untuk dipecahkan, maka mereka akan merasa enggan untuk mencoba.
Keberhasilan strategi pembelajaran melalui PBL membutuhkan cukup waktu untuk persiapan.
Tanpa pemahaman mengapa mereka berusaha untuk memecahkan masalah yang sedang dipelajari, maka mereka tidak akan belajar apa yang mereka ingin dipelajari.
Chotimah, C., & Fathurrohman, M. (2018). Paradigma Baru Sistem Pembelajaran dari Teori, Metode, Model, Media, Hingga Evaluasi Pembelajaran. Yogyakarta: Ar-Ruzz Media.
Huda, Miftahul. (2015). Model-model Pengajaran dan Pembelajaran: Isu-Isu Metodis dan Paradigmatis. Yogyakarta: Pustaka Pelajar.
Sani, R.A. (2019). Inovasi Pembelajaran. Jakarta: Bumi Aksara.
Sanjaya, Wina (2016). Strategi Pembelajaran Berorientasi Standar Proses Pendidikan ( Cetakan ke 12). Jakarta: Kencana Prenada Media.
Shoimin, A. (2017). 68 Model Pembelajaran Inovatif dalam Kurikulum 2013. Yogyakarta: Ar-Ruzz Media.

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Problem Solving and Problem-based Learning in the Geosciences

2012 Journal Club

From January to May, 2012, the Problem Solving and Problem-based Learning Journal Club will meet once a month to discuss readings from the geoscience, other natural sciences and cognitive science literature. We will explore aspects of problem solving and problem-based learning in the classroom that includes introducing problem solving, levels of scaffolding, and assessing students' success.

Resources for Teaching Problem Solving and Problem-based Learning

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Teaching activities with a strong problem solving or problem-based learning
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Documented Problem Solving
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Faculty-coached, In-class Problem Solving
Investigative Case-Based Learning
The Case Method
Process-Oriented, Guided Inquiry Learning
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Problem-Solving Method of Teaching: All You Need to Know

What is Problem-Solving Method of Teaching?

Ever wondered about the problem-solving method of teaching? We’ve got you covered, from its core principles to practical tips, benefits, and real-world examples.

The problem-solving method of teaching is a student-centered approach to learning that focuses on developing students’ problem-solving skills. In this method, students are presented with real-world problems to solve, and they are encouraged to use their own knowledge and skills to come up with solutions. The teacher acts as a facilitator, providing guidance and support as needed, but ultimately the students are responsible for finding their own solutions.

Problem-Solving Method of Teaching – Agenda of the Day

5 most important benefits of problem-solving method of teaching, find out examples of the problem-solving method of teaching, 5 how tos for using the problem-solving method of teaching, how to choose: let’s draw a comparison.

Problem-Solving Method of Teaching Example

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The new way of teaching primarily helps students develop critical thinking skills and real-world application abilities. It also promotes independence and self-confidence in problem-solving.

The problem-solving method of teaching has a number of benefits. It helps students to:

1. Enhances critical thinking: By presenting students with real-world problems to solve, the problem-solving method of teaching forces them to think critically about the situation and to come up with their own solutions. This process helps students to develop their critical thinking skills, which are essential for success in school and in life.

2. Fosters creativity: The problem-solving method of teaching encourages students to be creative in their approach to solving problems. There is often no one right answer to a problem, so students are free to come up with their own unique solutions. This process helps students to develop their creativity, which is an important skill in all areas of life.

3. Encourages real-world application: The problem-solving method of teaching helps students learn how to apply their knowledge to real-world situations. By solving real-world problems, students are able to see how their knowledge is relevant to their lives and to the world around them. This helps students to become more motivated and engaged learners.

4. Builds student confidence: When students are able to successfully solve problems, they gain confidence in their abilities. This confidence is essential for success in all areas of life, both academic and personal.

5. Promotes collaborative learning: The problem-solving method of teaching often involves students working together to solve problems. This collaborative learning process helps students to develop their teamwork skills and to learn from each other.

Know 6 Steps in the Problem-Solving Method of Teaching

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The problem-solving method of teaching typically involves the following steps:

Identifying the problem. The first step is to identify the problem that students will be working on. This can be done by presenting students with a real-world problem, or by asking them to come up with their own problems.
Understanding the problem. Once students have identified the problem, they need to understand it fully. This may involve breaking the problem down into smaller parts or gathering more information about the problem.
Generating solutions. Once students understand the problem, they need to generate possible solutions. This can be done by brainstorming, or by using problem-solving techniques such as root cause analysis or the decision matrix.
Evaluating solutions. Students need to evaluate the pros and cons of each solution before choosing one to implement.
Implementing the solution. Once students have chosen a solution, they need to implement it. This may involve taking action or developing a plan.
Evaluating the results. Once students have implemented the solution, they need to evaluate the results to see if it was successful. If the solution is not successful, students may need to go back to step 3 and generate new solutions.

Here are a few examples of how the problem-solving method of teaching can be used in different subjects:

Math: Students could be presented with a real-world problem such as budgeting for a family or designing a new product. Students would then need to use their math skills to solve the problem.
Science: Students could be presented with a science experiment, or asked to research a scientific topic and come up with a solution to a problem. Students would then need to use their science knowledge and skills to solve the problem.
Social studies: Students could be presented with a historical event or current social issue, and asked to come up with a solution. Students would then need to use their social studies knowledge and skills to solve the problem.

Here are a few tips for using the problem-solving method of teaching effectively:

Choose problems that are relevant to students’ lives and interests.
Make sure that the problems are challenging but achievable.
Provide students with the resources they need to solve the problems, such as books, websites, or experts.
Encourage students to work collaboratively and to share their ideas.
Be patient and supportive. Problem-solving can be a challenging process, but it is also a rewarding one.

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The following table compares the different problem-solving methods:

Which Method is the Most Suitable?

The most suitable method of teaching will depend on a number of factors, such as the subject matter, the student’s age and ability level, and the teacher’s own preferences. However, the problem-solving method of teaching is a valuable approach that can be used in any subject area and with students of all ages.

Here are some additional tips for using the problem-solving method of teaching effectively:

Differentiate instruction. Not all students learn at the same pace or in the same way. Teachers can differentiate instruction to meet the needs of all learners by providing different levels of support and scaffolding.
Use formative assessment. Formative assessment can be used to monitor students’ progress and to identify areas where they need additional support. Teachers can then use this information to provide students with targeted instruction.
Create a positive learning environment. Students need to feel safe and supported in order to learn effectively. Teachers can create a positive learning environment by providing students with opportunities for collaboration, celebrating their successes, and creating a classroom culture where mistakes are seen as learning opportunities.

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Some Unique Examples to Refer to Before We Conclude

Here are a few unique examples of how the problem-solving method of teaching can be used in different subjects:

English: Students could be presented with a challenging text, such as a poem or a short story, and asked to analyze the text and come up with their own interpretation.
Art: Students could be asked to design a new product or to create a piece of art that addresses a social issue.
Music: Students could be asked to write a song about a current event or to create a new piece of music that reflects their cultural heritage.

The problem-solving method of teaching is a powerful tool that can be used to help students develop the skills they need to succeed in school and in life. By creating a learning environment where students are encouraged to think critically and solve problems, teachers can help students to become lifelong learners.

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35 problem-solving techniques and methods for solving complex problems

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How do you identify problems?

How do you identify the right solution.

Tips for more effective problem-solving

Complete problem-solving methods

Problem-solving techniques to identify and analyze problems
Problem-solving techniques for developing solutions

Problem-solving warm-up activities

Closing activities for a problem-solving process.

Before you can move towards finding the right solution for a given problem, you first need to identify and define the problem you wish to solve.

Here, you want to clearly articulate what the problem is and allow your group to do the same. Remember that everyone in a group is likely to have differing perspectives and alignment is necessary in order to help the group move forward.

Identifying a problem accurately also requires that all members of a group are able to contribute their views in an open and safe manner. It can be scary for people to stand up and contribute, especially if the problems or challenges are emotive or personal in nature. Be sure to try and create a psychologically safe space for these kinds of discussions.

Remember that problem analysis and further discussion are also important. Not taking the time to fully analyze and discuss a challenge can result in the development of solutions that are not fit for purpose or do not address the underlying issue.

Successfully identifying and then analyzing a problem means facilitating a group through activities designed to help them clearly and honestly articulate their thoughts and produce usable insight.

With this data, you might then produce a problem statement that clearly describes the problem you wish to be addressed and also state the goal of any process you undertake to tackle this issue.

Finding solutions is the end goal of any process. Complex organizational challenges can only be solved with an appropriate solution but discovering them requires using the right problem-solving tool.

After you’ve explored a problem and discussed ideas, you need to help a team discuss and choose the right solution. Consensus tools and methods such as those below help a group explore possible solutions before then voting for the best. They’re a great way to tap into the collective intelligence of the group for great results!

Remember that the process is often iterative. Great problem solvers often roadtest a viable solution in a measured way to see what works too. While you might not get the right solution on your first try, the methods below help teams land on the most likely to succeed solution while also holding space for improvement.

Every effective problem solving process begins with an agenda . A well-structured workshop is one of the best methods for successfully guiding a group from exploring a problem to implementing a solution.

In SessionLab, it’s easy to go from an idea to a complete agenda . Start by dragging and dropping your core problem solving activities into place . Add timings, breaks and necessary materials before sharing your agenda with your colleagues.

The resulting agenda will be your guide to an effective and productive problem solving session that will also help you stay organized on the day!

Tips for more effective problem solving

Problem-solving activities are only one part of the puzzle. While a great method can help unlock your team’s ability to solve problems, without a thoughtful approach and strong facilitation the solutions may not be fit for purpose.

Let’s take a look at some problem-solving tips you can apply to any process to help it be a success!

Clearly define the problem

Jumping straight to solutions can be tempting, though without first clearly articulating a problem, the solution might not be the right one. Many of the problem-solving activities below include sections where the problem is explored and clearly defined before moving on.

This is a vital part of the problem-solving process and taking the time to fully define an issue can save time and effort later. A clear definition helps identify irrelevant information and it also ensures that your team sets off on the right track.

Don’t jump to conclusions

It’s easy for groups to exhibit cognitive bias or have preconceived ideas about both problems and potential solutions. Be sure to back up any problem statements or potential solutions with facts, research, and adequate forethought.

The best techniques ask participants to be methodical and challenge preconceived notions. Make sure you give the group enough time and space to collect relevant information and consider the problem in a new way. By approaching the process with a clear, rational mindset, you’ll often find that better solutions are more forthcoming.

Try different approaches

Problems come in all shapes and sizes and so too should the methods you use to solve them. If you find that one approach isn’t yielding results and your team isn’t finding different solutions, try mixing it up. You’ll be surprised at how using a new creative activity can unblock your team and generate great solutions.

Don’t take it personally

Depending on the nature of your team or organizational problems, it’s easy for conversations to get heated. While it’s good for participants to be engaged in the discussions, ensure that emotions don’t run too high and that blame isn’t thrown around while finding solutions.

You’re all in it together, and even if your team or area is seeing problems, that isn’t necessarily a disparagement of you personally. Using facilitation skills to manage group dynamics is one effective method of helping conversations be more constructive.

Get the right people in the room

Your problem-solving method is often only as effective as the group using it. Getting the right people on the job and managing the number of people present is important too!

If the group is too small, you may not get enough different perspectives to effectively solve a problem. If the group is too large, you can go round and round during the ideation stages.

Creating the right group makeup is also important in ensuring you have the necessary expertise and skillset to both identify and follow up on potential solutions. Carefully consider who to include at each stage to help ensure your problem-solving method is followed and positioned for success.

Document everything

The best solutions can take refinement, iteration, and reflection to come out. Get into a habit of documenting your process in order to keep all the learnings from the session and to allow ideas to mature and develop. Many of the methods below involve the creation of documents or shared resources. Be sure to keep and share these so everyone can benefit from the work done!

Bring a facilitator

Facilitation is all about making group processes easier. With a subject as potentially emotive and important as problem-solving, having an impartial third party in the form of a facilitator can make all the difference in finding great solutions and keeping the process moving. Consider bringing a facilitator to your problem-solving session to get better results and generate meaningful solutions!

Develop your problem-solving skills

It takes time and practice to be an effective problem solver. While some roles or participants might more naturally gravitate towards problem-solving, it can take development and planning to help everyone create better solutions.

You might develop a training program, run a problem-solving workshop or simply ask your team to practice using the techniques below. Check out our post on problem-solving skills to see how you and your group can develop the right mental process and be more resilient to issues too!

Design a great agenda

Workshops are a great format for solving problems. With the right approach, you can focus a group and help them find the solutions to their own problems. But designing a process can be time-consuming and finding the right activities can be difficult.

Check out our workshop planning guide to level-up your agenda design and start running more effective workshops. Need inspiration? Check out templates designed by expert facilitators to help you kickstart your process!

In this section, we’ll look at in-depth problem-solving methods that provide a complete end-to-end process for developing effective solutions. These will help guide your team from the discovery and definition of a problem through to delivering the right solution.

If you’re looking for an all-encompassing method or problem-solving model, these processes are a great place to start. They’ll ask your team to challenge preconceived ideas and adopt a mindset for solving problems more effectively.

Six Thinking Hats
Lightning Decision Jam
Problem Definition Process
Discovery & Action Dialogue

Design Sprint 2.0

Open Space Technology

1. Six Thinking Hats

Individual approaches to solving a problem can be very different based on what team or role an individual holds. It can be easy for existing biases or perspectives to find their way into the mix, or for internal politics to direct a conversation.

Six Thinking Hats is a classic method for identifying the problems that need to be solved and enables your team to consider them from different angles, whether that is by focusing on facts and data, creative solutions, or by considering why a particular solution might not work.

Like all problem-solving frameworks, Six Thinking Hats is effective at helping teams remove roadblocks from a conversation or discussion and come to terms with all the aspects necessary to solve complex problems.

2. Lightning Decision Jam

Featured courtesy of Jonathan Courtney of AJ&Smart Berlin, Lightning Decision Jam is one of those strategies that should be in every facilitation toolbox. Exploring problems and finding solutions is often creative in nature, though as with any creative process, there is the potential to lose focus and get lost.

Unstructured discussions might get you there in the end, but it’s much more effective to use a method that creates a clear process and team focus.

In Lightning Decision Jam, participants are invited to begin by writing challenges, concerns, or mistakes on post-its without discussing them before then being invited by the moderator to present them to the group.

From there, the team vote on which problems to solve and are guided through steps that will allow them to reframe those problems, create solutions and then decide what to execute on.

By deciding the problems that need to be solved as a team before moving on, this group process is great for ensuring the whole team is aligned and can take ownership over the next stages.

Lightning Decision Jam (LDJ) #action #decision making #problem solving #issue analysis #innovation #design #remote-friendly The problem with anything that requires creative thinking is that it’s easy to get lost—lose focus and fall into the trap of having useless, open-ended, unstructured discussions. Here’s the most effective solution I’ve found: Replace all open, unstructured discussion with a clear process. What to use this exercise for: Anything which requires a group of people to make decisions, solve problems or discuss challenges. It’s always good to frame an LDJ session with a broad topic, here are some examples: The conversion flow of our checkout Our internal design process How we organise events Keeping up with our competition Improving sales flow

3. Problem Definition Process

While problems can be complex, the problem-solving methods you use to identify and solve those problems can often be simple in design.

By taking the time to truly identify and define a problem before asking the group to reframe the challenge as an opportunity, this method is a great way to enable change.

Begin by identifying a focus question and exploring the ways in which it manifests before splitting into five teams who will each consider the problem using a different method: escape, reversal, exaggeration, distortion or wishful. Teams develop a problem objective and create ideas in line with their method before then feeding them back to the group.

This method is great for enabling in-depth discussions while also creating space for finding creative solutions too!

Problem Definition #problem solving #idea generation #creativity #online #remote-friendly A problem solving technique to define a problem, challenge or opportunity and to generate ideas.

4. The 5 Whys

Sometimes, a group needs to go further with their strategies and analyze the root cause at the heart of organizational issues. An RCA or root cause analysis is the process of identifying what is at the heart of business problems or recurring challenges.

The 5 Whys is a simple and effective method of helping a group go find the root cause of any problem or challenge and conduct analysis that will deliver results.

By beginning with the creation of a problem statement and going through five stages to refine it, The 5 Whys provides everything you need to truly discover the cause of an issue.

The 5 Whys #hyperisland #innovation This simple and powerful method is useful for getting to the core of a problem or challenge. As the title suggests, the group defines a problems, then asks the question “why” five times, often using the resulting explanation as a starting point for creative problem solving.

5. World Cafe

World Cafe is a simple but powerful facilitation technique to help bigger groups to focus their energy and attention on solving complex problems.

World Cafe enables this approach by creating a relaxed atmosphere where participants are able to self-organize and explore topics relevant and important to them which are themed around a central problem-solving purpose. Create the right atmosphere by modeling your space after a cafe and after guiding the group through the method, let them take the lead!

Making problem-solving a part of your organization’s culture in the long term can be a difficult undertaking. More approachable formats like World Cafe can be especially effective in bringing people unfamiliar with workshops into the fold.

World Cafe #hyperisland #innovation #issue analysis World Café is a simple yet powerful method, originated by Juanita Brown, for enabling meaningful conversations driven completely by participants and the topics that are relevant and important to them. Facilitators create a cafe-style space and provide simple guidelines. Participants then self-organize and explore a set of relevant topics or questions for conversation.

6. Discovery & Action Dialogue (DAD)

One of the best approaches is to create a safe space for a group to share and discover practices and behaviors that can help them find their own solutions.

With DAD, you can help a group choose which problems they wish to solve and which approaches they will take to do so. It’s great at helping remove resistance to change and can help get buy-in at every level too!

This process of enabling frontline ownership is great in ensuring follow-through and is one of the methods you will want in your toolbox as a facilitator.

Discovery & Action Dialogue (DAD) #idea generation #liberating structures #action #issue analysis #remote-friendly DADs make it easy for a group or community to discover practices and behaviors that enable some individuals (without access to special resources and facing the same constraints) to find better solutions than their peers to common problems. These are called positive deviant (PD) behaviors and practices. DADs make it possible for people in the group, unit, or community to discover by themselves these PD practices. DADs also create favorable conditions for stimulating participants’ creativity in spaces where they can feel safe to invent new and more effective practices. Resistance to change evaporates as participants are unleashed to choose freely which practices they will adopt or try and which problems they will tackle. DADs make it possible to achieve frontline ownership of solutions.

7. Design Sprint 2.0

Want to see how a team can solve big problems and move forward with prototyping and testing solutions in a few days? The Design Sprint 2.0 template from Jake Knapp, author of Sprint, is a complete agenda for a with proven results.

Developing the right agenda can involve difficult but necessary planning. Ensuring all the correct steps are followed can also be stressful or time-consuming depending on your level of experience.

Use this complete 4-day workshop template if you are finding there is no obvious solution to your challenge and want to focus your team around a specific problem that might require a shortcut to launching a minimum viable product or waiting for the organization-wide implementation of a solution.

8. Open space technology

Open space technology- developed by Harrison Owen – creates a space where large groups are invited to take ownership of their problem solving and lead individual sessions. Open space technology is a great format when you have a great deal of expertise and insight in the room and want to allow for different takes and approaches on a particular theme or problem you need to be solved.

Start by bringing your participants together to align around a central theme and focus their efforts. Explain the ground rules to help guide the problem-solving process and then invite members to identify any issue connecting to the central theme that they are interested in and are prepared to take responsibility for.

Once participants have decided on their approach to the core theme, they write their issue on a piece of paper, announce it to the group, pick a session time and place, and post the paper on the wall. As the wall fills up with sessions, the group is then invited to join the sessions that interest them the most and which they can contribute to, then you’re ready to begin!

Everyone joins the problem-solving group they’ve signed up to, record the discussion and if appropriate, findings can then be shared with the rest of the group afterward.

Open Space Technology #action plan #idea generation #problem solving #issue analysis #large group #online #remote-friendly Open Space is a methodology for large groups to create their agenda discerning important topics for discussion, suitable for conferences, community gatherings and whole system facilitation

Techniques to identify and analyze problems

Using a problem-solving method to help a team identify and analyze a problem can be a quick and effective addition to any workshop or meeting.

While further actions are always necessary, you can generate momentum and alignment easily, and these activities are a great place to get started.

We’ve put together this list of techniques to help you and your team with problem identification, analysis, and discussion that sets the foundation for developing effective solutions.

Let’s take a look!

The Creativity Dice
Fishbone Analysis
Problem Tree
SWOT Analysis
Agreement-Certainty Matrix
The Journalistic Six
LEGO Challenge
What, So What, Now What?
Journalists

Individual and group perspectives are incredibly important, but what happens if people are set in their minds and need a change of perspective in order to approach a problem more effectively?

Flip It is a method we love because it is both simple to understand and run, and allows groups to understand how their perspectives and biases are formed.

Participants in Flip It are first invited to consider concerns, issues, or problems from a perspective of fear and write them on a flip chart. Then, the group is asked to consider those same issues from a perspective of hope and flip their understanding.

No problem and solution is free from existing bias and by changing perspectives with Flip It, you can then develop a problem solving model quickly and effectively.

Flip It! #gamestorming #problem solving #action Often, a change in a problem or situation comes simply from a change in our perspectives. Flip It! is a quick game designed to show players that perspectives are made, not born.

10. The Creativity Dice

One of the most useful problem solving skills you can teach your team is of approaching challenges with creativity, flexibility, and openness. Games like The Creativity Dice allow teams to overcome the potential hurdle of too much linear thinking and approach the process with a sense of fun and speed.

In The Creativity Dice, participants are organized around a topic and roll a dice to determine what they will work on for a period of 3 minutes at a time. They might roll a 3 and work on investigating factual information on the chosen topic. They might roll a 1 and work on identifying the specific goals, standards, or criteria for the session.

Encouraging rapid work and iteration while asking participants to be flexible are great skills to cultivate. Having a stage for idea incubation in this game is also important. Moments of pause can help ensure the ideas that are put forward are the most suitable.

The Creativity Dice #creativity #problem solving #thiagi #issue analysis Too much linear thinking is hazardous to creative problem solving. To be creative, you should approach the problem (or the opportunity) from different points of view. You should leave a thought hanging in mid-air and move to another. This skipping around prevents premature closure and lets your brain incubate one line of thought while you consciously pursue another.

11. Fishbone Analysis

Organizational or team challenges are rarely simple, and it’s important to remember that one problem can be an indication of something that goes deeper and may require further consideration to be solved.

Fishbone Analysis helps groups to dig deeper and understand the origins of a problem. It’s a great example of a root cause analysis method that is simple for everyone on a team to get their head around.

Participants in this activity are asked to annotate a diagram of a fish, first adding the problem or issue to be worked on at the head of a fish before then brainstorming the root causes of the problem and adding them as bones on the fish.

Using abstractions such as a diagram of a fish can really help a team break out of their regular thinking and develop a creative approach.

Fishbone Analysis #problem solving ##root cause analysis #decision making #online facilitation A process to help identify and understand the origins of problems, issues or observations.

12. Problem Tree

Encouraging visual thinking can be an essential part of many strategies. By simply reframing and clarifying problems, a group can move towards developing a problem solving model that works for them.

In Problem Tree, groups are asked to first brainstorm a list of problems – these can be design problems, team problems or larger business problems – and then organize them into a hierarchy. The hierarchy could be from most important to least important or abstract to practical, though the key thing with problem solving games that involve this aspect is that your group has some way of managing and sorting all the issues that are raised.

Once you have a list of problems that need to be solved and have organized them accordingly, you’re then well-positioned for the next problem solving steps.

Problem tree #define intentions #create #design #issue analysis A problem tree is a tool to clarify the hierarchy of problems addressed by the team within a design project; it represents high level problems or related sublevel problems.

13. SWOT Analysis

Chances are you’ve heard of the SWOT Analysis before. This problem-solving method focuses on identifying strengths, weaknesses, opportunities, and threats is a tried and tested method for both individuals and teams.

Start by creating a desired end state or outcome and bare this in mind – any process solving model is made more effective by knowing what you are moving towards. Create a quadrant made up of the four categories of a SWOT analysis and ask participants to generate ideas based on each of those quadrants.

Once you have those ideas assembled in their quadrants, cluster them together based on their affinity with other ideas. These clusters are then used to facilitate group conversations and move things forward.

SWOT analysis #gamestorming #problem solving #action #meeting facilitation The SWOT Analysis is a long-standing technique of looking at what we have, with respect to the desired end state, as well as what we could improve on. It gives us an opportunity to gauge approaching opportunities and dangers, and assess the seriousness of the conditions that affect our future. When we understand those conditions, we can influence what comes next.

14. Agreement-Certainty Matrix

Not every problem-solving approach is right for every challenge, and deciding on the right method for the challenge at hand is a key part of being an effective team.

The Agreement Certainty matrix helps teams align on the nature of the challenges facing them. By sorting problems from simple to chaotic, your team can understand what methods are suitable for each problem and what they can do to ensure effective results.

If you are already using Liberating Structures techniques as part of your problem-solving strategy, the Agreement-Certainty Matrix can be an invaluable addition to your process. We’ve found it particularly if you are having issues with recurring problems in your organization and want to go deeper in understanding the root cause.

Agreement-Certainty Matrix #issue analysis #liberating structures #problem solving You can help individuals or groups avoid the frequent mistake of trying to solve a problem with methods that are not adapted to the nature of their challenge. The combination of two questions makes it possible to easily sort challenges into four categories: simple, complicated, complex , and chaotic . A problem is simple when it can be solved reliably with practices that are easy to duplicate. It is complicated when experts are required to devise a sophisticated solution that will yield the desired results predictably. A problem is complex when there are several valid ways to proceed but outcomes are not predictable in detail. Chaotic is when the context is too turbulent to identify a path forward. A loose analogy may be used to describe these differences: simple is like following a recipe, complicated like sending a rocket to the moon, complex like raising a child, and chaotic is like the game “Pin the Tail on the Donkey.” The Liberating Structures Matching Matrix in Chapter 5 can be used as the first step to clarify the nature of a challenge and avoid the mismatches between problems and solutions that are frequently at the root of chronic, recurring problems.

Organizing and charting a team’s progress can be important in ensuring its success. SQUID (Sequential Question and Insight Diagram) is a great model that allows a team to effectively switch between giving questions and answers and develop the skills they need to stay on track throughout the process.

Begin with two different colored sticky notes – one for questions and one for answers – and with your central topic (the head of the squid) on the board. Ask the group to first come up with a series of questions connected to their best guess of how to approach the topic. Ask the group to come up with answers to those questions, fix them to the board and connect them with a line. After some discussion, go back to question mode by responding to the generated answers or other points on the board.

It’s rewarding to see a diagram grow throughout the exercise, and a completed SQUID can provide a visual resource for future effort and as an example for other teams.

SQUID #gamestorming #project planning #issue analysis #problem solving When exploring an information space, it’s important for a group to know where they are at any given time. By using SQUID, a group charts out the territory as they go and can navigate accordingly. SQUID stands for Sequential Question and Insight Diagram.

16. Speed Boat

To continue with our nautical theme, Speed Boat is a short and sweet activity that can help a team quickly identify what employees, clients or service users might have a problem with and analyze what might be standing in the way of achieving a solution.

Methods that allow for a group to make observations, have insights and obtain those eureka moments quickly are invaluable when trying to solve complex problems.

In Speed Boat, the approach is to first consider what anchors and challenges might be holding an organization (or boat) back. Bonus points if you are able to identify any sharks in the water and develop ideas that can also deal with competitors!

Speed Boat #gamestorming #problem solving #action Speedboat is a short and sweet way to identify what your employees or clients don’t like about your product/service or what’s standing in the way of a desired goal.

17. The Journalistic Six

Some of the most effective ways of solving problems is by encouraging teams to be more inclusive and diverse in their thinking.

Based on the six key questions journalism students are taught to answer in articles and news stories, The Journalistic Six helps create teams to see the whole picture. By using who, what, when, where, why, and how to facilitate the conversation and encourage creative thinking, your team can make sure that the problem identification and problem analysis stages of the are covered exhaustively and thoughtfully. Reporter’s notebook and dictaphone optional.

The Journalistic Six – Who What When Where Why How #idea generation #issue analysis #problem solving #online #creative thinking #remote-friendly A questioning method for generating, explaining, investigating ideas.

18. LEGO Challenge

Now for an activity that is a little out of the (toy) box. LEGO Serious Play is a facilitation methodology that can be used to improve creative thinking and problem-solving skills.

The LEGO Challenge includes giving each member of the team an assignment that is hidden from the rest of the group while they create a structure without speaking.

What the LEGO challenge brings to the table is a fun working example of working with stakeholders who might not be on the same page to solve problems. Also, it’s LEGO! Who doesn’t love LEGO!

LEGO Challenge #hyperisland #team A team-building activity in which groups must work together to build a structure out of LEGO, but each individual has a secret “assignment” which makes the collaborative process more challenging. It emphasizes group communication, leadership dynamics, conflict, cooperation, patience and problem solving strategy.

19. What, So What, Now What?

If not carefully managed, the problem identification and problem analysis stages of the problem-solving process can actually create more problems and misunderstandings.

The What, So What, Now What? problem-solving activity is designed to help collect insights and move forward while also eliminating the possibility of disagreement when it comes to identifying, clarifying, and analyzing organizational or work problems.

Facilitation is all about bringing groups together so that might work on a shared goal and the best problem-solving strategies ensure that teams are aligned in purpose, if not initially in opinion or insight.

Throughout the three steps of this game, you give everyone on a team to reflect on a problem by asking what happened, why it is important, and what actions should then be taken.

This can be a great activity for bringing our individual perceptions about a problem or challenge and contextualizing it in a larger group setting. This is one of the most important problem-solving skills you can bring to your organization.

W³ – What, So What, Now What? #issue analysis #innovation #liberating structures You can help groups reflect on a shared experience in a way that builds understanding and spurs coordinated action while avoiding unproductive conflict. It is possible for every voice to be heard while simultaneously sifting for insights and shaping new direction. Progressing in stages makes this practical—from collecting facts about What Happened to making sense of these facts with So What and finally to what actions logically follow with Now What . The shared progression eliminates most of the misunderstandings that otherwise fuel disagreements about what to do. Voila!

20. Journalists

Problem analysis can be one of the most important and decisive stages of all problem-solving tools. Sometimes, a team can become bogged down in the details and are unable to move forward.

Journalists is an activity that can avoid a group from getting stuck in the problem identification or problem analysis stages of the process.

In Journalists, the group is invited to draft the front page of a fictional newspaper and figure out what stories deserve to be on the cover and what headlines those stories will have. By reframing how your problems and challenges are approached, you can help a team move productively through the process and be better prepared for the steps to follow.

Journalists #vision #big picture #issue analysis #remote-friendly This is an exercise to use when the group gets stuck in details and struggles to see the big picture. Also good for defining a vision.

Problem-solving techniques for developing solutions

The success of any problem-solving process can be measured by the solutions it produces. After you’ve defined the issue, explored existing ideas, and ideated, it’s time to narrow down to the correct solution.

Use these problem-solving techniques when you want to help your team find consensus, compare possible solutions, and move towards taking action on a particular problem.

Improved Solutions
Four-Step Sketch
15% Solutions
How-Now-Wow matrix
Impact Effort Matrix

21. Mindspin

Brainstorming is part of the bread and butter of the problem-solving process and all problem-solving strategies benefit from getting ideas out and challenging a team to generate solutions quickly.

With Mindspin, participants are encouraged not only to generate ideas but to do so under time constraints and by slamming down cards and passing them on. By doing multiple rounds, your team can begin with a free generation of possible solutions before moving on to developing those solutions and encouraging further ideation.

This is one of our favorite problem-solving activities and can be great for keeping the energy up throughout the workshop. Remember the importance of helping people become engaged in the process – energizing problem-solving techniques like Mindspin can help ensure your team stays engaged and happy, even when the problems they’re coming together to solve are complex.

MindSpin #teampedia #idea generation #problem solving #action A fast and loud method to enhance brainstorming within a team. Since this activity has more than round ideas that are repetitive can be ruled out leaving more creative and innovative answers to the challenge.

22. Improved Solutions

After a team has successfully identified a problem and come up with a few solutions, it can be tempting to call the work of the problem-solving process complete. That said, the first solution is not necessarily the best, and by including a further review and reflection activity into your problem-solving model, you can ensure your group reaches the best possible result.

One of a number of problem-solving games from Thiagi Group, Improved Solutions helps you go the extra mile and develop suggested solutions with close consideration and peer review. By supporting the discussion of several problems at once and by shifting team roles throughout, this problem-solving technique is a dynamic way of finding the best solution.

Improved Solutions #creativity #thiagi #problem solving #action #team You can improve any solution by objectively reviewing its strengths and weaknesses and making suitable adjustments. In this creativity framegame, you improve the solutions to several problems. To maintain objective detachment, you deal with a different problem during each of six rounds and assume different roles (problem owner, consultant, basher, booster, enhancer, and evaluator) during each round. At the conclusion of the activity, each player ends up with two solutions to her problem.

23. Four Step Sketch

Creative thinking and visual ideation does not need to be confined to the opening stages of your problem-solving strategies. Exercises that include sketching and prototyping on paper can be effective at the solution finding and development stage of the process, and can be great for keeping a team engaged.

By going from simple notes to a crazy 8s round that involves rapidly sketching 8 variations on their ideas before then producing a final solution sketch, the group is able to iterate quickly and visually. Problem-solving techniques like Four-Step Sketch are great if you have a group of different thinkers and want to change things up from a more textual or discussion-based approach.

Four-Step Sketch #design sprint #innovation #idea generation #remote-friendly The four-step sketch is an exercise that helps people to create well-formed concepts through a structured process that includes: Review key information Start design work on paper, Consider multiple variations , Create a detailed solution . This exercise is preceded by a set of other activities allowing the group to clarify the challenge they want to solve. See how the Four Step Sketch exercise fits into a Design Sprint

24. 15% Solutions

Some problems are simpler than others and with the right problem-solving activities, you can empower people to take immediate actions that can help create organizational change.

Part of the liberating structures toolkit, 15% solutions is a problem-solving technique that focuses on finding and implementing solutions quickly. A process of iterating and making small changes quickly can help generate momentum and an appetite for solving complex problems.

Problem-solving strategies can live and die on whether people are onboard. Getting some quick wins is a great way of getting people behind the process.

It can be extremely empowering for a team to realize that problem-solving techniques can be deployed quickly and easily and delineate between things they can positively impact and those things they cannot change.

15% Solutions #action #liberating structures #remote-friendly You can reveal the actions, however small, that everyone can do immediately. At a minimum, these will create momentum, and that may make a BIG difference. 15% Solutions show that there is no reason to wait around, feel powerless, or fearful. They help people pick it up a level. They get individuals and the group to focus on what is within their discretion instead of what they cannot change. With a very simple question, you can flip the conversation to what can be done and find solutions to big problems that are often distributed widely in places not known in advance. Shifting a few grains of sand may trigger a landslide and change the whole landscape.

25. How-Now-Wow Matrix

The problem-solving process is often creative, as complex problems usually require a change of thinking and creative response in order to find the best solutions. While it’s common for the first stages to encourage creative thinking, groups can often gravitate to familiar solutions when it comes to the end of the process.

When selecting solutions, you don’t want to lose your creative energy! The How-Now-Wow Matrix from Gamestorming is a great problem-solving activity that enables a group to stay creative and think out of the box when it comes to selecting the right solution for a given problem.

Problem-solving techniques that encourage creative thinking and the ideation and selection of new solutions can be the most effective in organisational change. Give the How-Now-Wow Matrix a go, and not just for how pleasant it is to say out loud.

How-Now-Wow Matrix #gamestorming #idea generation #remote-friendly When people want to develop new ideas, they most often think out of the box in the brainstorming or divergent phase. However, when it comes to convergence, people often end up picking ideas that are most familiar to them. This is called a ‘creative paradox’ or a ‘creadox’. The How-Now-Wow matrix is an idea selection tool that breaks the creadox by forcing people to weigh each idea on 2 parameters.

26. Impact and Effort Matrix

All problem-solving techniques hope to not only find solutions to a given problem or challenge but to find the best solution. When it comes to finding a solution, groups are invited to put on their decision-making hats and really think about how a proposed idea would work in practice.

The Impact and Effort Matrix is one of the problem-solving techniques that fall into this camp, empowering participants to first generate ideas and then categorize them into a 2×2 matrix based on impact and effort.

Activities that invite critical thinking while remaining simple are invaluable. Use the Impact and Effort Matrix to move from ideation and towards evaluating potential solutions before then committing to them.

Impact and Effort Matrix #gamestorming #decision making #action #remote-friendly In this decision-making exercise, possible actions are mapped based on two factors: effort required to implement and potential impact. Categorizing ideas along these lines is a useful technique in decision making, as it obliges contributors to balance and evaluate suggested actions before committing to them.

27. Dotmocracy

If you’ve followed each of the problem-solving steps with your group successfully, you should move towards the end of your process with heaps of possible solutions developed with a specific problem in mind. But how do you help a group go from ideation to putting a solution into action?

Dotmocracy – or Dot Voting -is a tried and tested method of helping a team in the problem-solving process make decisions and put actions in place with a degree of oversight and consensus.

One of the problem-solving techniques that should be in every facilitator’s toolbox, Dot Voting is fast and effective and can help identify the most popular and best solutions and help bring a group to a decision effectively.

Dotmocracy #action #decision making #group prioritization #hyperisland #remote-friendly Dotmocracy is a simple method for group prioritization or decision-making. It is not an activity on its own, but a method to use in processes where prioritization or decision-making is the aim. The method supports a group to quickly see which options are most popular or relevant. The options or ideas are written on post-its and stuck up on a wall for the whole group to see. Each person votes for the options they think are the strongest, and that information is used to inform a decision.

All facilitators know that warm-ups and icebreakers are useful for any workshop or group process. Problem-solving workshops are no different.

Use these problem-solving techniques to warm up a group and prepare them for the rest of the process. Activating your group by tapping into some of the top problem-solving skills can be one of the best ways to see great outcomes from your session.

Check-in/Check-out
Doodling Together
Show and Tell
Constellations
Draw a Tree

28. Check-in / Check-out

Solid processes are planned from beginning to end, and the best facilitators know that setting the tone and establishing a safe, open environment can be integral to a successful problem-solving process.

Check-in / Check-out is a great way to begin and/or bookend a problem-solving workshop. Checking in to a session emphasizes that everyone will be seen, heard, and expected to contribute.

If you are running a series of meetings, setting a consistent pattern of checking in and checking out can really help your team get into a groove. We recommend this opening-closing activity for small to medium-sized groups though it can work with large groups if they’re disciplined!

Check-in / Check-out #team #opening #closing #hyperisland #remote-friendly Either checking-in or checking-out is a simple way for a team to open or close a process, symbolically and in a collaborative way. Checking-in/out invites each member in a group to be present, seen and heard, and to express a reflection or a feeling. Checking-in emphasizes presence, focus and group commitment; checking-out emphasizes reflection and symbolic closure.

29. Doodling Together

Thinking creatively and not being afraid to make suggestions are important problem-solving skills for any group or team, and warming up by encouraging these behaviors is a great way to start.

Doodling Together is one of our favorite creative ice breaker games – it’s quick, effective, and fun and can make all following problem-solving steps easier by encouraging a group to collaborate visually. By passing cards and adding additional items as they go, the workshop group gets into a groove of co-creation and idea development that is crucial to finding solutions to problems.

Doodling Together #collaboration #creativity #teamwork #fun #team #visual methods #energiser #icebreaker #remote-friendly Create wild, weird and often funny postcards together & establish a group’s creative confidence.

30. Show and Tell

You might remember some version of Show and Tell from being a kid in school and it’s a great problem-solving activity to kick off a session.

Asking participants to prepare a little something before a workshop by bringing an object for show and tell can help them warm up before the session has even begun! Games that include a physical object can also help encourage early engagement before moving onto more big-picture thinking.

By asking your participants to tell stories about why they chose to bring a particular item to the group, you can help teams see things from new perspectives and see both differences and similarities in the way they approach a topic. Great groundwork for approaching a problem-solving process as a team!

Show and Tell #gamestorming #action #opening #meeting facilitation Show and Tell taps into the power of metaphors to reveal players’ underlying assumptions and associations around a topic The aim of the game is to get a deeper understanding of stakeholders’ perspectives on anything—a new project, an organizational restructuring, a shift in the company’s vision or team dynamic.

31. Constellations

Who doesn’t love stars? Constellations is a great warm-up activity for any workshop as it gets people up off their feet, energized, and ready to engage in new ways with established topics. It’s also great for showing existing beliefs, biases, and patterns that can come into play as part of your session.

Using warm-up games that help build trust and connection while also allowing for non-verbal responses can be great for easing people into the problem-solving process and encouraging engagement from everyone in the group. Constellations is great in large spaces that allow for movement and is definitely a practical exercise to allow the group to see patterns that are otherwise invisible.

Constellations #trust #connection #opening #coaching #patterns #system Individuals express their response to a statement or idea by standing closer or further from a central object. Used with teams to reveal system, hidden patterns, perspectives.

32. Draw a Tree

Problem-solving games that help raise group awareness through a central, unifying metaphor can be effective ways to warm-up a group in any problem-solving model.

Draw a Tree is a simple warm-up activity you can use in any group and which can provide a quick jolt of energy. Start by asking your participants to draw a tree in just 45 seconds – they can choose whether it will be abstract or realistic.

Once the timer is up, ask the group how many people included the roots of the tree and use this as a means to discuss how we can ignore important parts of any system simply because they are not visible.

All problem-solving strategies are made more effective by thinking of problems critically and by exposing things that may not normally come to light. Warm-up games like Draw a Tree are great in that they quickly demonstrate some key problem-solving skills in an accessible and effective way.

Draw a Tree #thiagi #opening #perspectives #remote-friendly With this game you can raise awarness about being more mindful, and aware of the environment we live in.

Each step of the problem-solving workshop benefits from an intelligent deployment of activities, games, and techniques. Bringing your session to an effective close helps ensure that solutions are followed through on and that you also celebrate what has been achieved.

Here are some problem-solving activities you can use to effectively close a workshop or meeting and ensure the great work you’ve done can continue afterward.

One Breath Feedback
Who What When Matrix
Response Cards

How do I conclude a problem-solving process?

All good things must come to an end. With the bulk of the work done, it can be tempting to conclude your workshop swiftly and without a moment to debrief and align. This can be problematic in that it doesn’t allow your team to fully process the results or reflect on the process.

At the end of an effective session, your team will have gone through a process that, while productive, can be exhausting. It’s important to give your group a moment to take a breath, ensure that they are clear on future actions, and provide short feedback before leaving the space.

The primary purpose of any problem-solving method is to generate solutions and then implement them. Be sure to take the opportunity to ensure everyone is aligned and ready to effectively implement the solutions you produced in the workshop.

Remember that every process can be improved and by giving a short moment to collect feedback in the session, you can further refine your problem-solving methods and see further success in the future too.

33. One Breath Feedback

Maintaining attention and focus during the closing stages of a problem-solving workshop can be tricky and so being concise when giving feedback can be important. It’s easy to incur “death by feedback” should some team members go on for too long sharing their perspectives in a quick feedback round.

One Breath Feedback is a great closing activity for workshops. You give everyone an opportunity to provide feedback on what they’ve done but only in the space of a single breath. This keeps feedback short and to the point and means that everyone is encouraged to provide the most important piece of feedback to them.

One breath feedback #closing #feedback #action This is a feedback round in just one breath that excels in maintaining attention: each participants is able to speak during just one breath … for most people that’s around 20 to 25 seconds … unless of course you’ve been a deep sea diver in which case you’ll be able to do it for longer.

34. Who What When Matrix

Matrices feature as part of many effective problem-solving strategies and with good reason. They are easily recognizable, simple to use, and generate results.

The Who What When Matrix is a great tool to use when closing your problem-solving session by attributing a who, what and when to the actions and solutions you have decided upon. The resulting matrix is a simple, easy-to-follow way of ensuring your team can move forward.

Great solutions can’t be enacted without action and ownership. Your problem-solving process should include a stage for allocating tasks to individuals or teams and creating a realistic timeframe for those solutions to be implemented or checked out. Use this method to keep the solution implementation process clear and simple for all involved.

Who/What/When Matrix #gamestorming #action #project planning With Who/What/When matrix, you can connect people with clear actions they have defined and have committed to.

35. Response cards

Group discussion can comprise the bulk of most problem-solving activities and by the end of the process, you might find that your team is talked out!

Providing a means for your team to give feedback with short written notes can ensure everyone is head and can contribute without the need to stand up and talk. Depending on the needs of the group, giving an alternative can help ensure everyone can contribute to your problem-solving model in the way that makes the most sense for them.

Response Cards is a great way to close a workshop if you are looking for a gentle warm-down and want to get some swift discussion around some of the feedback that is raised.

Response Cards #debriefing #closing #structured sharing #questions and answers #thiagi #action It can be hard to involve everyone during a closing of a session. Some might stay in the background or get unheard because of louder participants. However, with the use of Response Cards, everyone will be involved in providing feedback or clarify questions at the end of a session.

Save time and effort discovering the right solutions

A structured problem solving process is a surefire way of solving tough problems, discovering creative solutions and driving organizational change. But how can you design for successful outcomes?

With SessionLab, it’s easy to design engaging workshops that deliver results. Drag, drop and reorder blocks to build your agenda. When you make changes or update your agenda, your session timing adjusts automatically , saving you time on manual adjustments.

Collaborating with stakeholders or clients? Share your agenda with a single click and collaborate in real-time. No more sending documents back and forth over email.

Explore how to use SessionLab to design effective problem solving workshops or watch this five minute video to see the planner in action!

Over to you

The problem-solving process can often be as complicated and multifaceted as the problems they are set-up to solve. With the right problem-solving techniques and a mix of creative exercises designed to guide discussion and generate purposeful ideas, we hope we’ve given you the tools to find the best solutions as simply and easily as possible.

Is there a problem-solving technique that you are missing here? Do you have a favorite activity or method you use when facilitating? Let us know in the comments below, we’d love to hear from you!

thank you very much for these excellent techniques

Certainly wonderful article, very detailed. Shared!

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Perbedaan PBL dan Problem Solving: Mana yang Lebih Efektif dalam Pembelajaran?

Saat belajar atau menghadapi masalah, mungkin kamu sering kali mendengar istilah PBL dan Problem Solving. Namun, apa sebenarnya perbedaan antara PBL dan problem solving tersebut? Sebelumnya, PBL atau Problem-Based Learning merupakan salah satu metode pembelajaran di mana siswa akan bersama-sama mengidentifikasi masalah dan merancang solusi untuk memecahkannya. Sedangkan, Problem Solving adalah kemampuan untuk mengatasi masalah dengan cara yang efektif dan efisien, dari tahap analisis hingga implementasi solusi.

Meski tampak serupa, PBL dan Problem Solving memiliki perbedaan yang cukup signifikan. PBL lebih menekankan pada proses pembelajaran dan kemampuan siswa dalam menjawab pertanyaan-pertanyaan yang muncul. Pada teknik ini, siswa dihadapkan pada masalah yang diharapkan dapat menggugah material dasar yang sedang dipelajari. Sementara itu, Problem Solving pada dasarnya merupakan bagian dari proses pembelajaran di mana seseorang memecahkan masalah yang sedang dihadapinya dengan kemampuan dan pengetahuan yang dimilikinya.

Bagaimana dengan cara belajar yang cocok dengan kamu? Apakah lebih memilih dihadapkan pada masalah atau menyelesaikannya? Salam belajar! Perbedaan PBL dan Problem Solving

Metode Pembelajaran Berbasis Masalah (PBL) dan metode Problem Solving merupakan dua pendekatan pembelajaran yang sering digunakan di dunia pendidikan dan bisnis. Meskipun keduanya memiliki kesamaan dalam menyelesaikan masalah, namun pada dasarnya terdapat perbedaan signifikan antara PBL dan Problem Solving.

PBL adalah pendekatan pembelajaran yang menekankan pada pengembangan kemampuan berpikir kritis dan kreatif siswa. Dalam metode ini, siswa diberikan masalah kompleks dan realistis untuk dipecahkan secara mandiri atau dalam kelompok. Siswa diharapkan untuk dapat melibatkan diri secara aktif dalam memecahkan masalah tersebut dan mengintegrasikan pengetahuan dan keterampilan yang telah diperoleh.
Sedangkan Problem Solving adalah suatu pendekatan untuk menyelesaikan masalah dengan konsep dan strategi yang sistematis. Pendekatan ini biasanya digunakan dalam konteks bisnis, dimana tim atau individu harus mencari solusi terbaik untuk masalah yang dihadapi. Dalam Problem Solving, para profesional memanfaatkan pengetahuan dan keterampilan yang dimiliki untuk memecahkan masalah dengan cara yang efektif dan efisien.

Perbedaan utama antara PBL dan Problem Solving adalah dalam konteks penggunaannya. PBL lebih sering digunakan dalam dunia pendidikan untuk mempromosikan pembelajaran yang aktif, sementara Problem Solving lebih sering dipraktikkan di dalam konteks profesional untuk menyelesaikan masalah bisnis. Meskipun begitu, keduanya memiliki unsur yang sama yaitu proses berpikir yang sistematis dan strategis untuk mencari solusi terbaik.

Seperti yang dapat dilihat pada tabel berikut, terdapat perbedaan lain antara PBL dan Problem Solving:

Secara keseluruhan, PBL dan metode Problem Solving adalah dua pendekatan pembelajaran yang berbeda. Keduanya memiliki manfaat yang unik tergantung pada konteks penggunaannya. PBL dapat membantu siswa untuk belajar secara mandiri dan meningkatkan keterampilan berpikir kritis, sedangkan Problem Solving dapat membantu profesional dan bisnis untuk menyelesaikan masalah dengan cara yang efektif dan efisien.

Pada setiap metode pembelajaran, tentunya memiliki tujuan yang ingin dicapai. Begitu pula dengan PBL (Problem Based Learning) yang memiliki tujuan yang spesifik dalam pengaplikasiannya di dalam dunia pendidikan. Tujuan PBL antara lain:

Melatih keterampilan pemecahan masalah.
Meningkatkan kemampuan kritis dan kreatif siswa.
Melatih keterampilan kerjasama dan komunikasi diantara sesama siswa.

Tujuan-tujuan tersebut tentunya menjadi hal yang penting dalam dunia pendidikan, dimana dengan memperkuat keterampilan-keterampilan tersebut, siswa diharapkan dapat menjadi pribadi yang tangkas dan mampu menghadapi tantangan yang ada di masyarakat.

Jenis-jenis Problem Solving

Problem solving adalah aktivitas yang dilakukan oleh seseorang atau kelompok untuk menyelesaikan masalah yang dihadapi. Ada banyak jenis-jenis problem solving yang ada, di antaranya:

Heuristik: Jenis problem solving ini dilakukan dengan cara menggunakan pengetahuan dan pengalaman untuk menyelesaikan masalah.
Algoritma: Jenis problem solving ini dilakukan dengan cara mengikuti langkah-langkah tertentu yang sudah ditentukan untuk menyelesaikan masalah.
Metode trial dan error: Jenis problem solving ini dilakukan dengan mencoba-coba dan melakukan kesalahan untuk menyelesaikan masalah.
Pemecahan masalah sistematis: Jenis problem solving ini dilakukan dengan cara mengidentifikasi, menganalisis, dan menyelesaikan masalah secara sistematis.
Collaborative problem solving: Jenis problem solving ini dilakukan oleh kelompok atau tim, di mana setiap anggota saling berkolaborasi untuk menyelesaikan masalah.

Pemecahan Masalah Sistematis

Pemecahan masalah sistematis adalah metode problem solving yang populer dan banyak digunakan di berbagai bidang, seperti bisnis, teknologi, dan pendidikan. Pemecahan masalah sistematis dilakukan dengan cara mengikuti langkah-langkah tertentu, yaitu:

Mengidentifikasi masalah atau situasi yang memerlukan penyelesaian.
Mengumpulkan data dan informasi yang diperlukan untuk menganalisis masalah.
Menganalisis masalah dengan cara mengevaluasi informasi dan mengidentifikasi akar masalah.
Mengembangkan alternatif solusi yang dapat diimplementasikan.
Memilih solusi terbaik dan mengimplementasikannya.
Mengevaluasi solusi yang telah diterapkan untuk memberikan umpan balik dan melihat apakah solusi tersebut efektif atau tidak.

Pemecahan masalah sistematis dapat membantu seseorang atau kelompok untuk menyelesaikan masalah dengan lebih tepat dan efektif. Dengan menggunakan pendekatan sistematis, masalah akan dipahami dan dipecahkan dengan cara yang lebih terorganisir dan terstruktur.

Collaborative Problem Solving

Collaborative problem solving adalah metode problem solving yang melibatkan tim atau kelompok yang bekerja sama untuk menyelesaikan masalah. Metode ini dapat meningkatkan kemampuan dan keterampilan dalam menyelesaikan masalah secara efektif. Ada banyak keuntungan yang didapat dari collaborative problem solving, di antaranya:

Meningkatkan kualitas solusi yang dihasilkan.
Meningkatkan kreativitas dan inovasi dalam menyelesaikan masalah.
Meningkatkan dukungan sosial yang diberikan oleh tim atau kelompok.
Meningkatkan kepercayaan diri dan motivasi untuk menyelesaikan masalah.
Meningkatkan kemampuan untuk bekerja sama dalam suatu tim atau kelompok.

Dalam collaborative problem solving, setiap anggota tim atau kelompok akan berkontribusi dengan cara yang berbeda untuk mencapai tujuan bersama. Mereka akan membagikan pengetahuan, pengalaman, dan keterampilan dalam menyelesaikan masalah. Hal ini dapat membantu untuk menghasilkan solusi yang lebih inovatif dan efektif.

Dalam memilih metode problem solving yang tepat, seseorang atau kelompok harus mempertimbangkan sumber daya yang tersedia, waktu yang tersedia, dan tujuan yang ingin dicapai. Setiap jenis problem solving memiliki kelebihan dan kekurangan masing-masing, oleh karena itu penting untuk memilih metode yang sesuai dengan kebutuhan dan kondisi yang ada.

Langkah-langkah PBL

Project-Based Learning atau PBL merupakan suatu metode belajar yang memungkinkan siswa untuk memecahkan masalah dengan mengerjakan proyek-relevan di lingkungan sekitar mereka. Ada beberapa langkah yang harus dilakukan dalam PBL untuk mencapai target dan tujuan pembelajaran. Dalam artikel ini, kita akan membahas setiap langkah dari PBL secara rinci.

Langkah 1 – Identifikasi topik dan masalah

Siswa harus memilih topik dan masalah yang relevan dalam kehidupan sehari-hari. Hal ini akan membantu siswa untuk memecahkan masalah yang nyata dan signifikan. Sebagai contoh, siswa dapat memilih topik seputar lingkungan atau masalah sosial dalam masyarakat.

Langkah 2 – Perencanaan proyek

Pada langkah ini, siswa perlu merencanakan proyek yang akan mereka kerjakan. Siswa perlu mengidentifikasi sumber daya yang dibutuhkan dan menentukan bagaimana tugas akan diselesaikan mengikuti batas waktu yang ditentukan.

Langkah 3 – Penyelesaian proyek

Setelah merencanakan proyek, siswa melanjutkan dengan menyelesaikan proyek tersebut. Siswa akan bekerja sama dalam tim untuk mencapai tujuan mereka dan menyelesaikan tugas secara efisien.

Langkah 4 – Evaluasi proyek

Perbedaan antara PBL dan Problem Solving

Kedua metodologi belajar ini serupa dalam hal siswa menyelesaikan masalah. Akan tetapi, perbedaan yang utama adalah dalam pendekatan yang digunakan. Problem Solving adalah sebuah teknik yang menggunakan pendekatan kritis untuk memecahkan masalah, sedangkan PBL lebih menekankan pada keterampilan bekerja sama dalam tim dan memberikan pengalaman langsung dalam menyelesaikan masalah nyata.

Melalui PBL, siswa dapat memecahkan masalah nyata sambil belajar dan mengembangkan keterampilan seperti bekerja sama dalam tim, berkomunikasi, dan kepemimpinan. Melalui langkah-langkah PBL, siswa dapat meningkatkan keterampilan multitasking, mempercepat proses pembelajaran, dan membentuk rasa percaya diri serta mandiri dalam memecahkan masalah.

Tabel 1. Perbedaan antara PBL dan Problem Solving.

Keunggulan PBL Perbedaan antara metode pembelajaran PBL dan problem solving terletak pada pendekatan dan fokus pembelajarannya. PBL berfokus pada pembelajaran dengan melibatkan siswa dalam proses riset dan kolaborasi untuk menyelesaikan sebuah masalah kompleks. Sedangkan problem solving fokus pada pembelajaran dengan menyelesaikan masalah yang diberikan tanpa melibatkan riset mendalam.

Namun, terdapat beberapa keunggulan PBL dibandingkan problem solving:

Peningkatan rasa percaya diri: Siswa yang terlibat dalam PBL merasa lebih percaya diri dengan kemampuan mereka dalam memecahkan masalah kompleks sehingga meningkatkan keterampilan problem solving mereka secara umum.
Meningkatkan kemampuan berpikir kritis: Dalam PBL, siswa dihadapkan pada masalah yang tidak memiliki satu jawaban pasti sehingga mereka harus berpikir kritis dan kreatif dalam mencari solusi.
Menumbuhkan kemampuan kolaborasi: Pembelajaran PBL melibatkan kolaborasi antar siswa dalam mencari solusi masalah sehingga mereka dapat belajar bagaimana bekerja dalam tim dan menyampaikan ide secara efektif.

Pada akhirnya, salah satu keunggulan terbesar dari PBL adalah dukungan yang diberikan pada siswa dalam mengembangkan keterampilan problem solving dan menciptakan lingkungan pembelajaran yang aktif dan interaktif. Oleh karena itu, method PBL adalah pilihan yang tepat untuk siswa yang ingin meningkatkan kemampuan problem solving mereka secara efektif dan menyenangkan.

Sumber: The Tim Ferriss Show Podcast: PBL vs Problem Solving

Perbedaan PBL dan Problem Solving

Problem-based learning (PBL) dan problem solving adalah dua metode pembelajaran yang berfokus pada pemecahan masalah, namun keduanya memiliki perbedaan utama.

PBL adalah pendekatan pembelajaran yang menempatkan mahasiswa sebagai pengambil keputusan aktif dalam memecahkan masalah melalui diskusi dan kolaborasi dengan sesama mahasiswa.
Problem solving, di sisi lain, fokus pada solusi dari masalah yang diberikan, dengan pendekatan yang lebih struktural dan terstruktur
Meskipun keduanya berfokus pada pemecahan masalah, PBL memiliki aspek berorientasi pada masalah yang lebih kuat daripada problem solving.

PBL sebagai Pembelajaran Berbasis Masalah

Dalam PBL, mahasiswa diberikan masalah nyata dan kompleks, kemudian diberikan waktu dan sumber daya untuk mengembangkan pemahaman mereka sendiri tentang masalah tersebut dan mencari solusi.

Mahasiswa melakukan diskusi dalam kelompok untuk mencari solusi masalah serta menyusun ide-ide untuk mulai menyelesaikan masalah tersebut. Misalnya, dalam kasus matematika, mahasiswa diminta untuk menyelesaikan perhitungan matematika rumit yang melibatkan banyak variabel dan faktor.

Problem Solving Sebagai Metode Struktural

Problem solving, pada dasarnya, adalah sekelompok teknik yang digunakan untuk mengidentifikasi, menganalisis, dan menyelesaikan masalah. Pendekatan struktural digunakan untuk mengontrol solusi dari masalah yang diberikan dan pastinya lebih terstruktur dari PBL.

Berikut adalah contoh tabel yang membandingkan PBL dan Proble Solving

Dari tabel tersebut, dapat dilihat bahwa meskipun keduanya berfokus pada pemecahan masalah, PBL dan problem solving memiliki perbedaan yang signifikan dalam pendekatan dan fokus mereka.

Problem-based Learning (PBL) dan Problem Solving adalah dua pendekatan pembelajaran yang sering digunakan di sekolah dan universitas. Meskipun terdengar mirip, kedua konsep ini memiliki perbedaan dalam pendekatannya dan cara mereka diterapkan. Di bawah ini adalah beberapa perbedaan antara PBL dan Problem Solving:

Perbedaan Pendekatan dan Tujuan

PBL adalah pendekatan pembelajaran di mana siswa bekerja sama dalam kelompok untuk menemukan solusi atas masalah yang mereka hadapi. Tujuannya adalah untuk mengembangkan keterampilan berpikir kritis, keterampilan sosial, dan kemampuan belajar sepanjang hayat.
Problem Solving adalah proses untuk menyelesaikan masalah dengan mengidentifikasi, menganalisis, dan menyelesaikan masalah yang dihadapi. Tujuannya adalah untuk mengembangkan keterampilan analitis dan pemecahan masalah.

Perbedaan pada Jenis Masalah

PBL mengarah pada masalah yang kompleks dan lebih luas. Masalahnya biasanya tidak memiliki satu jawaban benar dan mengharuskan siswa untuk melakukan penelitian yang mendalam. Proble Solving terfokus pada masalah yang lebih spesifik dengan solusi yang jelas.

Perbedaan pada Pembelajaran Berbasis Proyek

PBL cenderung mengintegrasikan pembelajaran ke dalam proyek untuk memecahkan masalah yang kompleks. Siswa akan mengembangkan proyek mereka sendiri, mengeksplorasi isu-isu yang terkait dengan masalah, dan mempresentasikan solusi mereka. Sebaliknya, Problem Solving tidak selalu terkait dengan proyek lebih banyak berfokus pada pembuatan keputusan dari solusi yang ada.

Perbedaan pada Keterlibatan Dosen

Dosen lebih terlibat dalam memberikan panduan dan umpan balik dalam PBL karena ada penggunaan kelompok yang berinteraksi, meskipun banyak belajar juga bisa dilakukan oleh murid itu sendiri. Di sisi lain, pada Problem Solving, dosennya hanya membantu dalam menetapkan batasan masalah yang akan diselesaikan oleh siswa.

Perbedaan pada Evaluasi

Dalam pengajaran, penting untuk memahami perbedaan antara PBL dan Problem Solving. PBL mendorong siswa untuk berpikir dan belajar secara kritis dalam konteks kehidupan nyata, sementara Problem Solving membantu siswa mengembangkan keterampilan analitis ketika mereka menemukan solusi atas masalah yang diberikan.

Konsep dan Prinsip Dasar PBL

PBL atau Problem Based Learning adalah pendekatan pembelajaran yang mengutamakan pemecahan masalah sebagai landasan utama dalam proses pembelajaran. Terdapat beberapa prinsip dasar yang mendasari PBL.

Pembelajaran berpusat pada peserta didik
Peserta didik menjadi aktif dalam proses pembelajaran
Peserta didik bekerja dalam kelompok untuk memecahkan masalah
Problem solving menjadi fokus utama pembelajaran
Pembelajaran dilakukan dengan pendekatan interdisipliner
Materi pembelajaran bersifat autentik dan relevan dengan kehidupan nyata

Dalam PBL, peserta didik akan dihadapkan pada masalah atau situasi yang kompleks dan berbeda-beda pada setiap kesempatan. Peserta didik kemudian diminta untuk mencari solusi dari masalah tersebut melalui proses pengamatan, pemikiran, dan refleksi secara kritis dan kreatif.

Didalam PBL, prinsip dasar tersebut menjadi pedoman bagi pengajar untuk merancang pembelajaran yang menantang dan membangun kemampuan berpikir siswa secara holistik. Selain itu, PBL juga dapat meningkatkan kemampuan siswa dalam berkomunikasi, bekerja sama, dan memecahkan masalah yang berkaitan dengan kehidupan sehari-hari.

Jadi, PBL dan problem solving memang memiliki kesamaan dalam hal fokus pada masalah. Namun, PBL lebih menekankan pada proses pemecahan masalah secara kreatif dan holistik, sedangkan problem solving hanya berfokus pada solusi dari masalah itu sendiri. Selain itu, PBL juga memberikan peran yang lebih aktif pada peserta didik, baik dalam merancang materi maupun mengambil keputusan.

Peran Guru dalam PBL

Problem-Based Learning (PBL) adalah metode pembelajaran yang memperkenalkan siswa pada kasus atau masalah dunia nyata sebagai titik awal untuk belajar. Proses belajar berpusat pada pemecahan masalah untuk menyelesaikan kasus tersebut. Guru memiliki peran penting dalam menjalankan metode pembelajaran PBL agar dapat efektif dan efisien.

Sebagai fasilitator pembelajaran: Guru berperan sebagai fasilitator dalam proses pembelajaran PBL. Mereka tidak lagi hanya memberikan materi, tetapi membantu siswa dalam memahami materi dan menunjukkan cara untuk memecahkan masalah.
Memilih kasus yang relevan: Guru juga memiliki peran dalam memilih kasus atau masalah dunia nyata yang relevan dengan materi pembelajaran. Kasus yang dipilih harus menarik dan menggugah minat siswa untuk belajar lebih dalam.
Mendorong kolaborasi antar siswa: Pada metode pembelajaran PBL, siswa bekerja sama dalam kelompok untuk menyelesaikan masalah. Guru berperan dalam memastikan adanya kolaborasi antar siswa, sehingga mereka dapat memecahkan masalah dengan lebih efektif.

Guru juga perlu memberikan bimbingan kepada siswa dalam menerapkan metode PBL. Berikut adalah beberapa hal yang dapat dilakukan oleh guru untuk memberikan bimbingan secara efektif:

Memberikan arahan: Guru memberikan arahan atau petunjuk yang jelas mengenai langkah-langkah yang perlu diambil untuk memecahkan masalah.
Mendorong refleksi: Guru mendorong siswa untuk merefleksikan proses pembelajaran dan mengevaluasi hasil yang telah dicapai.
Mendorong kreativitas: Selama proses pembelajaran, guru perlu mendorong siswa untuk berpikir kreatif dan memunculkan ide-ide terbaru.

Pada dasarnya, PBL dan Problem Solving memiliki konsep yang sama, yaitu memecahkan masalah. Namun, terdapat perbedaan mendasar antara keduanya:

PBL lebih fokus pada proses pembelajaran, sedangkan Problem Solving lebih fokus pada pencarian solusi.
PBL melibatkan kelompok siswa dalam pemecahan masalah, sedangkan Problem Solving lebih sering dilakukan secara individu.
PBL menggunakan masalah dunia nyata sebagai titik awal pembelajaran, sedangkan Problem Solving dapat menggunakan masalah apa saja sebagai bahan untuk mencari solusi.

Tabel Perbedaan antara PBL dan Problem Solving

Dengan mengetahui perbedaan antara PBL dan Problem Solving, guru dapat memutuskan metode pembelajaran mana yang sesuai untuk diimplementasikan pada materi pembelajaran yang dimiliki.

Peran Siswa dalam PBL

Problem-based learning (PBL) dapat dikatakan sebagai metode pembelajaran aktif yang menekankan pada peran siswa dalam memecahkan masalah. Oleh karena itu, peran siswa dalam PBL sangat penting dan harus dimengerti dengan baik. Berikut ini adalah penjelasan mengenai peran siswa dalam PBL:

Siswa sebagai pemecah masalah: Dalam PBL, siswa adalah pemecah masalah yang sebenarnya. Mereka dituntut untuk memecahkan suatu masalah atau tantangan yang diberikan dengan menggunakan berbagai macam sumber informasi.
Siswa sebagai pembelajar aktif: Siswa diharapkan untuk sangat aktif dalam pembelajaran karena mereka harus memecahkan suatu masalah. Mereka harus mencari sumber daya, berfikir kritis, dan mempresentasikan hasil pekerjaan mereka.
Siswa sebagai pengorganisasi: Siswa harus bertanggung jawab dalam mengorganisir pekerjaan mereka. Mereka harus merencanakan dan menjadwalkan kegiatan mulai dari analisis awal hingga presentasi akhir.
Siswa sebagai pemimpin: Dalam PBL, siswa diberi kebebasan untuk menentukan dan memimpin tim mereka sendiri. Hal ini menuntut siswa untuk bisa bekerja dalam kelompok dan memimpin kelompok tersebut agar dapat mencapai tujuan bersama.
Siswa sebagai evaluator: Siswa harus mengevaluasi pekerjaan mereka sendiri dan juga pekerjaan anggota tim mereka. Hal ini bertujuan untuk memastikan bahwa pekerjaan yang dihasilkan memenuhi standar yang diharapkan.

Selain peran di atas, siswa juga harus memiliki kemampuan-kemampuan tertentu agar dapat berhasil dalam PBL, antara lain:

Kemampuan mencari sumber daya: Siswa harus mampu mencari dan mengambil sumber daya secara efektif dan efisien untuk memecahkan masalah yang diberikan.
Kemampuan berkolaborasi: Siswa harus mampu bekerja sama dengan anggota tim mereka dan berkolaborasi dengan baik.
Kemampuan berfikir kritis: Siswa harus mampu mengembangkan kemampuan berfikir kritis untuk mengidentifikasi isu-isu yang muncul dalam pemecahan masalah.
Kemampuan presentasi: Siswa harus mampu membuat presentasi yang baik dan efektif untuk mempresentasikan hasil pekerjaan mereka.

Berdasarkan tabel di bawah ini, dapat dilihat bahwa keberhasilan PBL sangat bergantung pada peran siswa dalam proses pembelajaran:

Dalam PBL, siswa memiliki peran yang sangat penting dalam memecahkan masalah dan mencapai tujuan pembelajaran. Oleh karena itu, siswa harus berperan aktif dan memiliki kemampuan-kemampuan tertentu agar dapat berhasil dalam PBL.

Penggunaan Teknologi dalam PBL

PBL atau problem-based learning adalah metode pembelajaran di mana siswa diajak untuk menyelesaikan masalah dalam dunia nyata sebagai sarana untuk belajar. Penggunaan teknologi di dalam PBL memainkan peran penting dalam membantu siswa mencapai tujuan pembelajaran yang telah ditetapkan. Berikut adalah beberapa cara di mana teknologi dapat digunakan di dalam PBL:

Mempelajari dasar-dasar teknologi: Setiap proyek PBL menuntut siswa untuk menggunakan beberapa jenis teknologi, misalnya untuk membangun website atau membuat video. Penting bagi siswa untuk memahami dasar-dasar teknologi ini agar dapat melaksanakan proyek dengan baik. Maka, guru dapat menyediakan panduan tutorial video atau live demo untuk membantu siswa memahami penggunaan teknologi secara tepat.
Menyelesaikan masalah menggunakan software: Ada berbagai jenis software yang dapat membantu siswa memecahkan masalah yang mereka hadapi. Misalnya, Microsoft Excel dapat membantu mengelola data dan mengekstrak informasi dari data tersebut. Software presentasi seperti Powerpoint dan Prezi dapat membantu siswa menyusun informasi mereka ke dalam presentasi yang efektif. Guru dapat melatih siswa dalam penggunaan software tersebut agar mereka dapat memanfaatkan teknologi sebaik mungkin.
Penggunaan internet: Internet menyediakan sumber informasi yang melimpah yang dapat membantu siswa dalam menyelesaikan masalah mereka. Misalnya, mereka dapat melakukan penelitian tentang topik tertentu atau mencari solusi bagi masalah yang dihadapi. Meskipun seperti itu, guru harus memperhatikan untuk memberi panduan tentang bagaimana siswa dapat mengakses dan menggunakan informasi yang tepat dan berkualitas dari internet.

Penggunaan Teknologi secara Global

Penggunaan teknologi dalam PBL dapat membantu siswa memperluas pandangan mereka secara global. Beberapa cara di mana teknologi dapat membantu siswa lebih memahami dunia adalah sebagai berikut:

Komunikasi: Teknologi seperti Skype dan e-mail memungkinkan siswa untuk berkomunikasi secara online dengan orang seluruh dunia. Hal ini membuka peluang untuk menjalin hubungan dengan orang-orang dari budaya yang berbeda dan dapat membantu meningkatkan wawasan siswa tentang cara berpikir dan bekerja di negara lain.
Platform pembelajaran online: Ada banyak platform pembelajaran online yang tersedia, misalnya seperti Edmodo, Moodle, dan Google Classroom. Platform-platform ini dapat membantu siswa belajar melalui kursus online yang tersedia dari mana saja di dunia dan belajar melalui diskusi dan tugas yang terstruktur.
Penggunaan media sosial: Media sosial dapat membantu siswa membangun jaringan dan koneksi dengan orang-orang di seluruh dunia. Melalui media sosial, siswa dapat berhubungan dengan peneliti atau ahli dalam bidang tertentu untuk memperdalam pemahaman mereka tentang proyek PBL yang sedang dilakukan.

Tabel Perbandingan PBL dan Problem Solving

PBL dan problem solving adalah metode pembelajaran yang mirip, namun ada perbedaan utama antara keduanya. Berikut adalah tabel perbandingan di antara keduanya:

PBL versus Metode Konvensional

Problem Based Learning (PBL) dan problem solving merupakan dua metode pembelajaran yang sering digunakan di dalam pendidikan. Dalam hal ini, PBL dan problem solving memiliki beberapa perbedaan yang signifikan.

PBL mengajarkan para siswa untuk belajar dari pengalaman dan mencari solusi terhadap masalah yang dihadapi. Sedangkan metode konvensional lebih cenderung pada pemberian materi secara teoritis dan memberikan tes atau tugas yang berkaitan langsung dengan materi tersebut.
PBL lebih menekankan pada kemampuan berpikir kritis, kreatif, dan berkolaborasi dari para siswa. Sedangkan metode konvensional lebih fokus pada penguasaan materi dan keterampilan berhitung.
Para siswa pada PBL harus belajar bagaimana menyelesaikan masalah, sedangkan pada metode konvensional lebih banyak mengerjakan soal yang serupa.

Secara keseluruhan, perbedaan paling signifikan antara PBL dan metode konvensional terletak pada pendekatan pembelajaran yang digunakan. PBL lebih menekankan pada pengalaman dan penerapan nyata dalam menyelesaikan masalah, sedangkan metode konvensional lebih menekankan pada penguasaan konsep dan keterampilan.

Hasil penelitian menunjukkan bahwa siswa yang belajar dengan metode PBL cenderung memiliki tingkat pemahaman yang lebih baik dan kemampuan berpikir kritis yang lebih tinggi daripada mereka yang belajar dengan metode konvensional. Namun, pada saat yang sama, PBL juga memiliki kelemahan, seperti memerlukan waktu lebih lama untuk menyelesaikan tugas dan memerlukan upaya lebih besar dari para siswa untuk mencari solusi terhadap masalah yang diberikan.

Jadi, PBL dan metode konvensional memiliki kelebihan dan kekurangan masing-masing. Namun, ketika dipilih dengan tepat dan disesuaikan dengan karakteristik siswa, kedua metode ini dapat menjadi cara yang efektif untuk meningkatkan kemampuan siswa dalam menghadapi permasalahan dan memperkuat pemahaman konsep yang diperoleh.

Sampai Jumpa Lagi, Teman-Teman!

Itulah perbedaan antara PBL dan problem solving, teman-teman. Semoga artikel ini dapat memberikan manfaat bagi kalian yang sedang belajar, terutama dalam memilih metode pembelajaran yang tepat. Terima kasih sudah membaca artikel ini sampai selesai. Jangan lupa untuk selalu kunjungi website kami untuk mendapatkan informasi menarik dan bermanfaat lainnya. Sampai jumpa lagi!

Perbedaan PBL dan PJBL: Apa yang Harus Anda Ketahui? Apa Itu Strategi Pembelajaran dan Bagaimana Cara Memilih yang Tepat? Perbedaan CTL dan PBL: Metode Pembelajaran yang Berbeda Namun Efektif Perbedaan PBL dan PJBL PDF: Membedah Kelebihan dan Kekurangan Kedua Metode Pembelajaran

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Published: 20 April 2024

A novel method-based reinforcement learning with deep temporal difference network for flexible double shop scheduling problem

Xiao Wang 1 ,
Peisi Zhong 1 ,
Mei Liu 2 ,
Chao Zhang 1 &
Shihao Yang 1

Scientific Reports volume 14 , Article number: 9047 ( 2024 ) Cite this article

Metrics details

Computer science
Mechanical engineering

This paper studies the flexible double shop scheduling problem (FDSSP) that considers simultaneously job shop and assembly shop. It brings about the problem of scheduling association of the related tasks. To this end, a reinforcement learning algorithm with a deep temporal difference network is proposed to minimize the makespan. Firstly, the FDSSP is defined as the mathematical model of the flexible job-shop scheduling problem joined to the assembly constraint level. It is translated into a Markov decision process that directly selects behavioral strategies according to historical machining state data. Secondly, the proposed ten generic state features are input into the deep neural network model to fit the state value function. Similarly, eight simple constructive heuristics are used as candidate actions for scheduling decisions. From the greedy mechanism, optimally combined actions of all machines are obtained for each decision step. Finally, a deep temporal difference reinforcement learning framework is established, and a large number of comparative experiments are designed to analyze the basic performance of this algorithm. The results showed that the proposed algorithm was better than most other methods, which contributed to solving the practical production problem of the manufacturing industry.

Introduction

With the development of artificial intelligence and big data technologies, intelligent scheduling plays a decision-making role in resource allocation and equipment management of advanced manufacturing systems 1 . Flexible job-shop scheduling problem (FJSP), covering operation research, sequencing theory, and optimization methods, is mainly to determine the processing equipment and process path planning. It is one of the hot topics in the scheduling system 2 . Especially, flexible double shop scheduling problem (FDSSP) that considers job shop and assembly shop is a kind of practical extension of FJSP 3 . Compared to FJSP where assembly-associated jobs can start only after machining is completed, FDSSP is the essential key to collaborating with the scheduling of associated jobs. It can reduce the assembly waiting time of associated jobs when they enter the assembly workshop at the same time as possible, which is conducive to prioritizing the processing of urgent jobs and improving production efficiency.

Over recent decades, FDSSP relatively less studied. It is mainly divided into two categories: non-assembly scheduling (Lu et al. 4 ; Thurer et al. 5 ) and assembly scheduling (Zou et al. 6 ). The former, not involving specific assembly constraints, is to accomplish all tasks of the job shop before assembly operation with only a certain extra assembly period. It is suitable for simple products or short assembly time relative to processing time. The latter should be considered to process and assemble all jobs at the same time. Hence, it has high complexity and practical application.

FDSSP is a comprehensive scheduling problem that offers a subtle fusion of flexible process plans with assembly operations in the two adjacent working shops. It is a hierarchical coupling-constrained optimization problem (HCC). Researchers have spent quite a considerable effort on FJSP, which can be divided into two categories: exact methods (EM) and approximation methods (AM). EM can guarantee the global optimal solution, but usually only solves small-scale problems such as mathematical programming (Zhang and Wang 7 ; Nourali et al. 8 , 9 ) and Branch and Bound (B&B) (Brucker and Schlie 10 ; Carlos Soto et al. 11 ; Özgüven 12 ). AM can get the solution to the problem quickly, but it can't guarantee the best explanation. It is very suitable for solving large-scale problems, such as genetic algorithm (GA) (Tian et al. 13 ), particle swarm optimization (PSO) (Nouiri et al. 14 ), ant colony optimization (ACO) (Huang and Yu 15 ; Zhu et al. 16 ; Zhang et al. 17 ), multi-agent system algorithm (Cheng et al. 18 , 19 ).

These scheduling algorithms are designed along the lines of “modeling, analysis, and optimization”. It cannot effectively use real-time data and historical data, which makes it difficult to deal with the complex and changeable production scheduling problem. However, reinforcement learning (RL) has the advantages of real-time and flexibility. It can directly select behavior strategies according to the input processing state. One of the earliest studies was from Riedmiller and Riedmiller 20 , who proposed a Q-learning algorithm in RL to develop the single-machine scheduling problem to minimize the summed tardiness. The agents used the common scheduling rules as the behavior of the system such as earliest due date (EDD), longest processing time (LPT), minimal slack (MS), etc. Later, some scholars have carried out remarkable in this field, followed by more detail in later sections.

In this paper, the application of DRL, namely deep temporal difference network (DTDN) to scheduling problems in the flexible double shop system is presented. The main contributions of this work are summarized below. (1) The flexible job-shop scheduling model with the assembly constraint level was proposed to redefine the flexible double-shop scheduling problem. Specifically, the jobs assembly constraint level was designed for the assembly shop. (2) We established a deep temporal difference network reinforcement learning framework that defined state space, action space, and rewards space. (3) We applied a deep neural network that inputs the proposed generic state features to fit the state value function.

Related work

Related work is reviewed under two parts: (1) the flexible double shop scheduling problem and (2) the DRL scheduling.

Flexible double shop scheduling problem

The flexible job shop scheduling problem, which was introduced by Brucker and Schlie 10 in 1990, has received widespread attention. However, the flexible double shop scheduling problem has been little studied. Nourali and Imanipour 8 firstly introduced the assembly job scheduling problem with sequence-dependent setup times. Zhang et al. 7 deeply investigated distributed particle swarm optimization to solve multi-objective optimization problems (makespan, total tardiness, and total workload). Zheng et al. applied the master-apprentice evolutionary algorithm to cope with the assembly job-shop scheduling problem with random machine breakdown and uncertain processing time. Tian et al. 13 , utilizing a genetic algorithm with variable neighborhood search, studied the distributed assembly job shop scheduling problem to minimize maximum completion time. Cheng et al. 18 established the adaptive simulated annealing algorithm to solve the mathematical model of the assembly job-shop scheduling with lot streaming. Later, they 19 discussed the spatial temporal links among three stages with differentiated lot size. Demir and Erden 21 proposed Genetic Algorithm and Ant Colony Optimization Algorithm to minimize the earliness, tardiness, and due-dates for the dynamic integrated process plan, scheduling, and due date assignment problem. Fan et al. 22 studied FJSP with lot-streaming and machine reconfigurations (FJSP-LSMR) to minimize the total weighted tardiness. To deal with the two decision steps for FJSP, namely, the job sequencing and the job routing, Zhang et al. 23 presented a new deep reinforcement learning with multi-agent graphs model. Erden et al. 24 designed an improved integer and categorical particle swarm optimization algorithm to solve the dynamic integrated process planning, scheduling, and due date assignment problem, in which the earliness, tardiness, and due dates in practical problems are fully considered. Su et al. 25 established a framework that used the graph neural network and deep reinforcement learning to solve JSP with dynamic events and uncertainty. Fontes et al. 26 utilized a hybrid particle swarm optimization and simulated annealing algorithm to deal with the JSP with transport resources. Burmeister et al. 27 , applying a multi-objective memetic algorithm with non-dominated sorting genetic algorithm, proposed an energy cost-aware FJSP model based on minimization of both makespan and energy costs. Carlucci et al. 28 presented a decision scheduling model that simultaneously handled the power constraint and the variable speed of machine tools.

DRL scheduling problem

In recent years, RL, one of the three types of machine learning, has been successfully applied in some fields such as computing resource scheduling, robot control, and elevator scheduling. Among them, many scholars focused on the production scheduling system by RL. Liu et al. 29 proposed a parallel algorithm that utilizes asynchronous updates and deep deterministic policy gradients to solve the job shop scheduling problem. Using MMDP to build this model, the state space is represented in the JSSP environment by the processing time matrix, allocation matrix and activation matrix. And, action spaces are denoted by simple scheduling rules. Wei and Zhao 30 suggested the conception of the production pressure and the job’s estimated mean lateness for respectively defining the system feature and the policy of reward or penalty. The Q-learning algorithm was applied to the determination of the composite machine rules. However, this method can’t describe the actual complex machining process. Luo et al. 31 used the PPO algorithm to select processes in a discrete action space and verified its superiority in solving flexible job shop scheduling problems. However, the PPO algorithm has not been studied more thoroughly to improve its performance. Mouelhi-Chibani and Pierreval 32 proposed a neural network (NN) to dynamically select dispatching rules according to the current system status and the workshop parameters. RL can take the scheduling strategy which adapts to the actual system state. Song et al. 33 presented a method using DRL to learn priority dispatch rules (PDRs) and graph neural networks (GNNs) for FJSP. A new kind of heterogeneous graph scheduling state representation was employed to combine operation selection and machine allocation into one composite decision, which achieved high-quality learning of PDRs. Chen et al. 34 presented a rule-driven dispatching method based on the data envelopment analysis to solve the multi-objective dynamic job shop scheduling problem. An agent was trained to obtain the elementary rules with the WIP fluctuation of a machine. Shahrabi et al. 35 introduced the dynamic job shop scheduling problem (DJSSP) that considered machine breakdowns and random job arrivals. In their work, the dispatching rules were based on variable neighborhood search (VNS) and compared with some common dispatching rules and the general variable neighborhood search. Wang 36 designed an improved Q-learning with the clustering and greedy search policy. A dynamic scheduling system model with multi-agent technology was built including buffer, machine, state, and job agent to maximize the weighted mean of the fuzzy earning. Shiue et al. 37 established a procedure in which they planned the real-time scheduling knowledge base (RTSKB) using multiple dispatching rules (MDRs). Significantly, MDRs incorporated two mechanisms including an off-online learning module and a Q-learning-based RL module. So far, these algorithms have lacked a unified scheduling problem name. Che et al. 38 , applying a deep reinforcement learning based multi-objective evolutionary algorithm, proposed a multi-objective optimization model for the scheduling problem of oxygen production system. Yuan et al. 39 suggested a novel framework that translated a combined optimization problem into a multi-stage sequential decision-making problem. This framework is used a multi-agent double Deep Q-network algorithm for FJSP.

This research on the application of RL in these scheduling problems (Table 1 ) shows that RL is an effective method to solve the scheduling problem. This algorithm has the following characteristics:

RL is a decision-making algorithm directly oriented to long-term goals based on state or action value.

RL doesn’t need a complete mathematical model of the learning environment. It can imitate human experience, and learn and accumulate experience from the examples or simulation experiments that have been solved.

RL needs supervision and teaching. It adjusts the policy according to the evaluation reward obtained in the interaction process. So, it makes optimal responses to different system states.

Problem formulation

Mathematical model.

We introduce FDSSP by considering the production scheduling problem of the hydraulic cylinder. The hydraulic cylinder processes flow diagram is simplified to a production scheduling model in Fig. 1 . Each cylinder 40 , 41 is assembled from several components: body, bottom, piston, piston rod, lifting lug, O-ring, seal ring, piston pin, and wiper, as shown in Fig. 1 a. The cylinder body 3 is generally made of seamless steel pipe. Its internal machining accuracy is highly required. Piston 4 and piston rod 6 are connected using snap ring 2. The piston rod 6 is guided by guide sleeve 7 and sealed by seal ring 5. Cylinder bottom 1 and body 3 are respectively opened with oil inlet and outlet ports. When the right chamber of the hydraulic cylinder is filled with oil, the piston moves left. Inversely, the piston moves right.

Integrated production of hydraulic cylinder: ( a ) structure charts; ( b ) production layout; ( c ) job shop; ( d ) assembly shop.

The shop floor is divided into two areas, namely the job shop and the assembly shop. The product is started from the order and is finished with the assembly (Fig. 1 b). The job shop is equipped with three machines (fine turning, CNC milling, and electric spark) (Fig. 1 c). The assembly workshop has two assembly robots ( \(A_{1}\) , \(A_{2}\) ) (Fig. 1 d). Each operation can be completed by multiple alternative machines. After each operation k is completed, job j needs to enter the quality control center for quality inspection. If the quality is acceptable, a job is moved to the next operation k + 1; if instead, it is returned to the current operation to be queued and reworked again. The assembly operation is a complete kit assembly, which means that the assembly operation does not begin until the all job is completed.

Since the assembly operation may be relatively short and fixed, the planned start time of the assembly operation can be extrapolated from the delivery date of the order. In this paper, we concentrate on the job shop scheduling in a way that the completion time of each job is as close to the planned start time of the assembly as possible. The assembly shop is defined as the assembly constraint level.

Based on the above example, the FDSSP can be described as follows: supposing that there are n jobs to be processed in the job shop equipped with \(m\) machines. Each job j ( \(j \in \{ 1,2, \ldots ,N\}\) ) including \(O\) operations k ( \(k \in \{ 1,2, \ldots ,O\}\) ) needs to be processed according to the specified route. Each operation k can be selected processing on any powerful machines m ( \(m \in \{ 1,2, \ldots ,M_{ij} \}\) ) in \(M_{ij}\) machines. Meanwhile, the machine m can process different operations k of different jobs. Hence, there is a great discrepancy in the processing time of the operation \(k\) on different machines , which makes the study of scheduling algorithms particularly significant. The model parameters and indices are shown in Table 2 .

Assembly restraint level definition

The job after assembly is referred to as the constrained job, and the job before assembly is referenced as the front job. Firstly, according to the assembly constraint relationship, all jobs constraint levels that have no tight front constraint are set to 1. Jobs with undefined constraint levels make up the job set, which is denoted by U . Then, the job set \(J_{set}\) is formed from U in sequence taking out all tight front jobs \(J_{k}\) . Determining whether the constraint levels in \({J}_{set}\) have all been determined. If so, the level of the job \(J_{k}\) is set to \(\max (L(J_{set} ) + 1)\) , i.e., \(L(J_{k} ) = \max (L(J_{set} )) + 1\) . When not, it puts the job \(J_{k}\) back into U until the constraint levels of all jobs have been determined.

Other assumptions are considered as follows:

The processing times of each operation by each machine are determined and known.

Each job can select only one process path. And, one operation can only be processed by one machine at a time.

The sum of the start time and processing time of an operation is less than or equal to the makespan of the operation.

The makespan of the previous operation is less than or equal to the start time of the next operation.

Completion time of products is the sum of processing time and assembly time.

The operation of each machine is cyclic.

Intermediate conversion time of the job, transferring from the job shop to the assembly shop, is omitted.

Decision variables:

According to the literature reviewed 7 , 42 , 43 , 44 , 45 makespan is the most sufficiently studied objective. In this study, the objective of the model is as follows:

Transformation of scheduling problem

Definition of state-space.

The state features can reflect the main features of the production environment. The division of state space is the basis for the reasonable selection of scheduling rules for the system. Nevertheless, owing to the constantly changing production environment, the complete system state is continuous and often described by tens or even dozens of state characteristics on the job shop.

To describe the state space in detail, the following state features are defined:

The state features can describe the main features and changes of the scheduling environment in detail, including the global features and local features of the system.

The states of all problems are represented by a common feature set.

Different scheduling problems can be represented and summarized by state features.

State feature is a numerical representation of state variables.

The state should be easy to calculate.

To facilitate the expression with the formula, the processing state of the processes is recorded as \({P}_{jk}=\{\mathrm{0,1}\}\) , i.e., the operations are not processed is \(P_{jk} = 0\) , and has been processed is recorded as \(P_{jk} = 1\) . The operations to be processed on the machine are arranged in descending order of time length, and the resulting process sequence is denoted as \(list(m) = \{ J_{m1} ,J_{m2} ,...,J_{{mv_{m} }} \}\) , where \(v_{m}\) is the number of processes to be processed on machine m . As shown in Table 3 , we define ten state features of the shop environment.

Definition of action space

Panwalker and Iskander 46 , summarizing the previous studies, elaborated 113 different combinations of dispatching rules. These rules defined the useful types of problems and measures of performance. The SCH is chosen to define a candidate set of behaviors for each machine, where priority assignment rules for reinforcement learning can overcome short-sighted natures. Behaviors that are relevant or irrelevant to the conversion should be adopted to take full advantage of existing scheduling theory and the ability of the intelligence to learn from it. In Table 4 , eight common behaviors are selected as candidate sets.

Definition of rewards

The definition of the reward function is closely related to the objective function. The agent is rewarded according to the result of the change of the system state after the implementation of the synthetic behavior and the reward function. The reward function is chosen to be defined according to the following rules.

The immediate reward for each state transition reflects the immediate effect of the action performed, which results in a short-term impact on the scheduling plan.

The cumulative total reward result reflects the long-term outcome of the execution strategy, denoted as the optimal value of the objective function.

This reward function can be applied to scheduling problems of different sizes.

The literature 47 shows a direct relationship between \({C}_{max}\) and machine utilization (e.g., minimizing the makespan is equal to maximum machine utilization). This study is devoted to addressing minimizing the makespan. The immediate reward earned for each state transition reflects the immediate impact of the action performed. It also represents the short-term impact of the action on the scheduling scheme. Cumulative rewards reflect the long-term effects, which is the goal of RL maximization.

where \(U_{ave} (t)\) is the average machine utilization rate. Let \(C_{\max } (t)\) denotes the completion time of the last operation assigned on machine m at scheduling point t . \(O_{t}\) is the current number of operations for the job i that have been assigned. Define the machine m utilization rate as \(U_{k} (t)\) , which can be calculated by \(U_{k} (t) = \frac{{\sum\nolimits_{1}^{n} {\sum\nolimits_{k = 1}^{{O_{i} (t)}} {t_{jkm} x_{jkm} } } }}{{C_{\max } (t)}}\) . Let \(r_{k} = U_{k} (t) - U_{k - 1} (t)\) , then the cumulative reward R can be calculated as follows:

where k is the counter for the allocation operation. It can be considered as a discrete-time step in RL. \(P = \sum\nolimits_{1}^{n} {\sum\nolimits_{k = 1}^{{o_{i} (t)}} {t_{jkm} x_{jkm} } }\) . \(U_{k} (t)\) and \(C_{\max } (t)\) are machine utilization and makespan at time step k .

Proposed methods for the FDSSP

Related work of rl.

RL is a specific class of machine learning (ML) problems that can achieve global optimality 48 , 49 , 50 . In an RL model 51 , the decision-maker chooses an appropriate action by observing the environment and is rewarded for doing so. RL algorithms needn’t know many states and the state transfer probability matrix during iterations. RL is transformed into the model of solving the optimal solution of Markov decision models, which is mainly used to solve sequential decision problems. The most important feature of RL is that there is no correct answer in the learning process, rather learning is done through reward signals.

Procedure of TD with evaluating state value

Markov decision processes (MDP)

Markov is the property that the next state \(s_{t + 1}\) in an RL system is related only to the current state \(s_{t}\) . The Markov decision process is described by 5-tuple as follows:

where S is a finite set of states, characterizing the description of the environmental state; A is a finite set of action spaces, representing the set of behaviors that can be taken; P is a state transfer rate function; R is a reward function; \(\gamma\) is a discount factor.

The objective of RL is to enable the agent to find an optimal strategy \(\pi^{ * }\) through continuous experimentation in the environment that maximizes the expected cumulative reward function obtained by following the strategy from any state. The reward function is determined by further defining the value function. The state-value function \(v_{\pi } (s)\) and the action-value function \(q_{\pi } (s)\) under the strategy are defined as follows.

Updating Bellman's expectation equation with the optimal strategy yields the optimal equation as follows:

Temporal difference algorithm

The TD algorithm 52 , combining Monte Carlo and dynamic planning methods, uses the classical Bellman formula to iterate until the value function converges. The basic iteration formula is as follows:

where \(r_{t + 1} { + }\gamma V(s_{t + 1} )\) is the objective of TD; \(r_{t + 1} { + }\gamma V(s_{t + 1} ) - V(s_{t} )\) is the deviation of TD; \(\alpha\) is the learning rate. The procedure to calculate \(v(s)\) is given in Algorithm 1.

Deep learning model

Deep neural network.

Deep learning 53 is a type of representation learning that is based on artificial neural networks. Deep neural network structures have greater capacity and exponential representation space, which makes it easier to learn and represent a variety of features with a significantly reduced number of neurons.

The recent success of deep learning relies heavily on massive amounts of training data, flexible models, sufficient computing power, and prior experience to fight against dimensional disasters. Hinton 54 has proposed a technique combining pre-training and fine-tuning to drastically reduce the time training a multi-layer neural network. Various optimization techniques have emerged to further alleviate the gradient disappearance problem. In particular, an application of a technique known as “Deep Residuals” 55 can enable more than a hundred network layers.Algorithm 1

Procedure of DTDN

Activation function

The activation function, a central unit in the design of neural networks, gives the ability to learn and adapt for the neurons 56 , 57 . It incorporates nonlinear factors in the neural network to address the defect of expression ability of the linear model. If the activation function isn’t used, the output of each layer is a linear function of the inputs of the previous layer. No matter how many layers the neural network has, the output is a linear combination of the inputs. Common activation functions include step functions, Sigmoid functions, Tanh functions, and approximate biological neuronal activation functions such as Relu, Leaky-Relu, and Softplus. Because approximate biological neuronal activation functions are better than traditional functions in most network applications, Relu is used in this paper.

Optimization function

Optimization function 58 , one of the core problems in neural network training, not only speeds up the solution process but also reduces the influence of hyperparameters on the solution process. Common optimization algorithms used in research applications are the stochastic gradient descent algorithm (SGD), adaptive gradient algorithm (AdaGrad), root mean square prop algorithm (RMSProp), and Adam algorithm.

In this paper, the deep neural network is made up of seven connection layers, which contain one input layer, five implicit layers, and one output layer. Figure 2 b gives the structure of the neural network.

DTDN algorithm running model (3 × 3): Deep neural network model of state perception in agent: ( a ) Deep neural network model of state perception; ( b ) Deep neural network structure.

Exploration and exploitation

FDSSP can be classified as a multi-stage decision-making problem with terminals. To balance the allocation of exploration and exploitation of the agent in environmental interactions, a greedy strategy \(\varepsilon\) is used as a strategy for selecting behavior. Greedy strategy is the selection of a greedy behavior with probability \(1 - \varepsilon\) ( \(0 < \varepsilon < 1\) ) and the random selection of any optional behavior with probability \(\varepsilon\) , where \(\varepsilon\) is the exploration factor. Suppose \(P(s,a)\) denotes the probability of selecting a behavior at the decision state. The expression is as follows:

where \(A(s)\) is the set of combinatorial behaviors that are candidates in the state \(s\) ; \(|A\left(s\right)|\) is the number of behaviors that can be chosen in the state \(s\) ; \({a}^{*}(s)\) is the greedy behavior of the state. It denotes Eq. ( 7 ) as follows:

where \({r}_{ss{\prime}}^{a}\) is the immediate reward that takes a combination of actions from state \(s\) to state \({s}^{,}\) .

Deep temporal difference network model

To briefly describe the implementation process, a workshop visualization ( \(m = 3,n = 3\) ) is proposed in Fig. 2 . The hexagonal shape represents the jobs. Hexahedra represents waiting for queues of sufficient capacity.

At the start of processing, the scheduling system is in the initial state \({S}_{0}\) , i.e., all jobs are in the first waiting queue \(Q_{1}\) with all machines free. Then the first machine selects an action \(a(k)\) ( \(1 < k < 8\) ). A job in the queue \(Q_{1}\) is selected for processing while other machines select the action \(a(8)\) . Whenever any machines complete an operation, the system moves to a new state \(S_{t}\) . In this state, each machine selects an action to perform. When another operation is completed, the system moves to a new state \(S_{{t{ + }1}}\) , which gives the agent one reward \(r_{t + 1}\) . \(r_{t + 1}\) can be calculated by the time interval between the two states. Since at each decision moment, each machine simultaneously selects one act to execute. In actuality, the system implements a multidimensional behavior with a combination of m sub-activities at a time in the state \(S_{t} (a_{t + 1} = (a_{1} ,a_{2} ,...,a_{m} ))\) . When the system reaches the termination state \(S_{T}\) , it means that all queues are empty and that all jobs have been processed. Hence, a scheduling plan is obtained.

The deep Q-network (DQN) output layer uses several nodes to represent a finite number of discrete action values. However, it cannot cover the exponential multidimensional action space. When the Q-learning online evaluates action values for heterogeneous strategies, it results in over-estimation that optimal value replaces actual interaction values. Hence the method is not directly applied to the multi-dimensional action space problem. Temporal difference learning with the same strategy, state-values indirectly calculating action-values, is proposed to replace Q learning and state values are indirectly calculated for behavior values, which is suitable for selecting multi-dimensional action in Algorithm 2.

Experiment study

To evaluate the validity of the proposed algorithm, the experiments have been conducted utilizing different test cases in four parts. First of all, according to the standard test set established in Kacem 59 , we use eight small-scale cases to compare with other algorithms 17 , 32 , 60 , 61 in “ Small scale FDSSP " section. Then, in “ Comparisons with the proposed dispatching rules " section, we compare the proposed DTDN algorithm with the Q-Learning (QL) algorithm (Jiménez 62 ) and deep deterministic policy gradient (DDPG) algorithm (Liu 63 ) on different performances in Brandimarte 64 . Moreover, for large-scale instances, we designed our test cases, which included 30 FDSSP problems of varying complexity, as shown in Section " Large-scale instances of FDSSP ". Last but not least, in " Case Study: production scheduling problem " section, we illustrate in detail the application of our algorithm in a case study of solving the hydraulic cylinder production scheduling problem.

The DTDN algorithm is coded in Python 3.7 language on JetBrains PyCharm Community Edition 2019.2.1 × 64 and runs on Intel Core i9-10900x @ 3.7GHz CPU and 16 GB RAM. First of all, we build FDSSP environment classes, machine classes, and job classes in an object-oriented manner on the RL platform OpenAI Gym. Gym specifies the main member methods of environment classes as a framework, including init, reset, step, render, and close. Then, an agent that executes the algorithm iterates interactively with the environment. The deep neural network model of the agent is implemented with the back-end TensorFlow. The experimental data are shown in Table 5 .

The selection of parameters may affect the quality of the solution, thus general principles can be followed. The discount factor \(\gamma\) measures the weight of the subsequent state value on the total return, which is why it generally takes a value close to 1 (i.e., \(\gamma = 0.95\) ). To facilitate full exploration of the strategy space during the initial phase of the iteration, the \(\varepsilon\) -greedy strategy sets the initial value of \(\varepsilon = 1\) and decays with the discount rate of 0.995. Set the learning rate: \(\alpha = 5 \times 10^{ - 4}\) ; the maximum number of interactions: \(MAX - EPISODE = 800\) ; memory D capacity: \(N = 6000\) ; and sample batch: \(BATCH - SIZE = 64\) . The deep neural network of the agent is shown in Fig. 2 b, in which the network parameters adopt a random initialization strategy.

Performance metrics: The relative percentage deviation (RPD) and average relative percentage deviation (ARPD) are described as follows:

where \(C_{\max }\) are the optimal results of algorithms; \(LB\) is the optimal results of the Branch and Bound algorithm. It represents the most ideal solution result and is not possible to achieve.

Small scale FDSSP

To prove the validity of the solution process in this study, the cases proposed by Kacem. are validated. Where, the number of jobs ( n ), the number of machines ( m ), and each operation of jobs ( \(O_{ij}\) ) are represented. For example, \(n \times m\) is a case of a set consisting of jobs and machines. The literature with the same case study as this paper is selected for comparison [Zhang 17 (DACS); Xing et al. 60 (SM); Moslehi 32 (PSO); Li et al. 61 (HTSA)], which ensures the credibility of the comparison results. Meanwhile, each case is run ten times to obtain the combined optimal solution. CPU times of various algorithms are calculated by the “relative ratio” downloaded from https://www.cpubenchmark.net/ (Table 6 ). The results show that the optimal solution of DTDN and other algorithms are the same as LB, but CPU running time is very significantly different for small-scale problems (Kacem) in Table 7 .

As designed in Table 8 a, it can be seen that the algorithm progressively generates an optimal production schedule (35). An optimal policy set \(\{ \pi^{ * } \} = \{ (6,8,8,8),(2,1,8,8), \ldots ,(8,8,8,1)\}\) is the operation sequence of each job on the machine. Where the number of parentheses in the policy set indicates the combined behavior of the four machines consisting of the behavior number taken in the corresponding state. Where the number in parentheses in the policy set indicates that the four machines in the corresponding state consisting of the behavior number adopt the combined action. At each decision time point, since most of the machine waiting queues are empty or in-process, their feasible action space includes only \(a(8)\) , which saves computation time. Moreover, the comparison of test results for Problem 2 (Table 8 b) shows that the optimal solution of the DTDN algorithm (426) is improved by 4.3% and 2.7% compared to the Nawaz Encore Han (NEH) (445) algorithms and NEH-KK algorithms (438), respectively.

Comparisons with the proposed dispatching rules

To verify the efficiency and generality of the proposed DTDN, we planned the Brandimarte 64 data set as our adopted data set. Scores and RPD of the seven dispatching rules on each data case are tallied. As known from Table 9 , the proposed DTDN algorithm compared with other algorithms can obtain better solutions, and some of them are already below the upper bound of the original cases. The actions that are used more than 10% are FIFO, SPT, LPT, SRRT, LRPT, MOR, and EDD in Fig. 3 . It is known that these actions have a greater contribution to obtaining the optimal solution and thus have a greater utilization value. The frequency distribution of other actions was relatively even, but the performance was not obvious. Therefore, it can be considered to add other heuristic behaviors to the candidate action space, which eliminates some underutilized behaviors to streamline the actions.

Performance comparison of action space (dispatching rules) under different data cases.

Large-scale instances of FDSSP

In this study, to study the performance of DTDN on large-scale problems, the results of Brandimarte cases are further compared with problem sizes ranging from BC, DP, and BR data cases in a total of 30 data cases. The solution results of the proposed DTDN are compared with Gao et al. 65 (HGA), Mastrolilli and Gambardella 66 (MG), Sun et al. 67 (HMEA), Chen et al.69 (SLGA), and Reddy 68 [teaching–learning based optimization (TLBO)], which are shown in Table 10 and Fig. 4 . The test results show that the proposed DTDN algorithm can find better computational results globally through a large amount of trial and error in the solution procedure. The obtained performance index results are better than traditional optimization methods for different scales of arithmetic cases, demonstrating the validity of the DTDN algorithm for FDSSP.

Box plots based on the results in Tables 10 and 11 .

Case study: production scheduling problem

Nourali 8 , 9 proposed a useful benchmark of FDSSP, including 40 different data cases. The solution results of the proposed DTDN are compared with Huang et al 69 [particle swarm optimization (PSO)]; Zhang and Wong 7 (constraint programming (CP)), and Zhang et al. 17 [distributed ant colony system (DACS)]. The results are displayed in Table 11 and Fig. 4 , and the following conclusions can be summarized. The optimal solutions of this algorithm are all within [LB, UB], indicating that the solutions are valid. The performance of DTDN is close to that of the other three algorithms. The run time from CPU Time is about as long as the other algorithms for small-scale cases, but the large-scale problems are much more efficient than the other method. Lastly, in general, this algorithm is slightly less capable of solving large-scale problems because of the large scheduling state space for large-scale problems, the large learning error using the same network structure, and the need for more iterations and a more optimized network structure to reduce the training error.

The main contribution of this paper is to propose an efficient DTDN method for FDSSP in a flexible shop production environment to minimize makespan. The Q learning in the deep reinforcement learning algorithm DQN is transformed into the temporal differential TD learning with state value. Hence, the deep temporal differential reinforcement learning algorithm is obtained, which is successfully applied to the shop scheduling problem. As shown by experiments, the algorithm can obtain a better solution in a smaller number of iterations compared to simply constructed heuristic or population intelligence algorithms. Because of the introduction of state features, heuristic behaviors, and deep neural networks, the algorithm is highly flexible and dynamic. The advantages of the proposed algorithm include as following:

The algorithm can learn and real-time. Since the selection from the input state to the neural network is made by the SCH Algorithm with basic rules. When the neural network is successfully trained, the previous empirical patterns are stored in the network parameters that can make scheduling decisions in real time.

The algorithm model is more flexible. The state features, behavior rules, and neural network size can be flexibly modified as needed. The constructive process is closer to the actual scheduling, which is not only applicable to NPFS problems with greater computational complexity but also suitable for solving dynamic scheduling problems from the principle.

Limitations and future work

Due to the shortcomings of the study, further work can be considered in the following aspects.

Scheduling model. Significantly, RL can add and subtract state features to better describe the processing state with minimal redundancy. Searching for more efficient and practical heuristic behaviors can fit and generalize stronger value function generalizer structures. What's more, adding or subtracting candidate behavior sets can be considered to add more highly utilized constructive heuristic behaviors.

Algorithm procedure. The DTDN algorithm itself has been proposed after many types of improvements. For example, the DTDN algorithm with priority playback memory for memory sampling priority can improve the efficiency of algorithm iteration.

Algorithm application. There is a large development space for the algorithm with the continuous progress of deep neural network theory and the increasing computer computing power. The algorithm can be extended to apply to more complex job shop scheduling problems and other dynamic scheduling problems.

Data availability

All data mentioned in the paper are available through Xiao Wang. Email: [email protected].

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This research was funded by the Supported by the Natural Science Foundation of Shandong Province (No. ZR202103070107) and the National Natural Science Foundation of China (52234005).

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Conceptualization, X.W.; Methodology, X.W and M.L.; Software, X.W and C.Z.; Validation, M.L. and P.Z.; formal analysis, X.W.; data curation, X.W.; Resources, C.Z.; visualization, S.Y. All authors have reviewed and agreed to the published version of the manuscript.

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Wang, X., Zhong, P., Liu, M. et al. A novel method-based reinforcement learning with deep temporal difference network for flexible double shop scheduling problem. Sci Rep 14 , 9047 (2024). https://doi.org/10.1038/s41598-024-59414-8

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Embracing problem-based learning

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Classroom Practice

The Comprehensive Guide to Project-Based Learning: Empowering Student Choice through an Effective Teaching Method

What is Project-Based Learning?

Positive Impacts of Project-Based Learning

New Tech Network Project-Based Learning Impacts

Key Concepts of Project-Based Learning

A Unique Approach to Project-Based Learning: New Tech Network

Why Undertake this Work?

Meaningful and Equitable Instruction

Examples of Project-Based Learning

The Role of Technology in Project-Based Learning

Interactive PBL Resources

Preparing Students for the Future with PBL

The Impact of PBL on College and Career Readiness

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Problem-based learning as an instructional method

Publication types

Development of problem based learning (PBL) learning tools to improve mathematical problem solving ability of class VIII SMP/MTs students

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Model Pembelajaran Problem Solving (Penjelasan Lengkap)

Pengertian Model Pembelajaran Problem Solving

Sintaks Pembelajaran Problem Solving

Langkah Langkah Model Pembelajaran Problem Solving

Tujuan Model Problem Solving

Kelebihan dan Kekurangan Pembelajaran Problem Solving

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