academic writing tvl students research

Asian Journal of Advanced Research and Reports

Published: 2023-06-27

DOI: 10.9734/ajarr/2023/v17i9521

Page: 69-90

Issue: 2023 - Volume 17 [Issue 9]

Original Research Article

Lived Experiences in Performance Assessments: From the Lens of the Students in Technical Vocational Livelihood Senior High School

Roxanne Joy C. Olaguer *

University of Mindanao-Professional School, Matina, Davao City, The Philippines.

Ester Jean U. Pelayo

*Author to whom correspondence should be addressed.

Aims:   The study aimed to unveil the experiences, coping mechanisms, and insights of the Senior High School students in performance assessments of the TVL track.

Study Design: Qualitative-Phenomenology research design.

Place and Duration of Study: Three public schools under the division of Digos City, Davao Region, Region XI, which offer a Technical-Vocational-Livelihood strand during the SY 2022-2023.

Methodology: Using purposive sampling, the participants were the Senior High School students of the three identified public schools, which offer the Technical-Vocational-Livelihood track, 15 participants for the FGD and 6 participants for the IDI.

Results: For the experiences, three themes emerged: troubles in task completion during performance assessment, enjoying the tasks while learning, and lack of resources and materials, while for the coping mechanisms, also three themes: self-determination and perseverance, share ideas and materials with peers and teachers and study and perform diligently and insights, three themes emerged: teamwork is the force behind every success, perseverance makes impossible-possible, and it is not about their resources, it is being resourceful.

Implication: Assessment plays an integral role in teaching-learning because it will help improve the performance of each student and the school as a whole. It must be enhanced to improve its content and process significantly and to make evaluation and information a part of the teaching-learning process. These results will be a significant addition to the developing body of knowledge and literature about the impact of K to 12 in the Philippines. Other researchers may assess the effects of K to 12 and TVL curriculum or another qualitative study in other regions.

Keywords: Education, senior high school students, TVL track, performance task, phenomenology, Digos City, Philippines

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Unveiling the Research Mentality: A Deep Dive into TVL Student Attitudes

Surveying the mindset of TVL students towards research is crucial for understanding their engagement and perspectives. This survey delves into their views on the importance of research, their confidence levels, challenges faced, and motivations. Questions on the benefits of research, the use of different research methods, and the impact on society provide valuable insights. Analyzing TVL students' responses can shed light on how to enhance their research skills and support their academic and career growth. From exploring their interests in specific research topics to their preferred sources of information, this survey captures the diverse perspectives of TVL students. As we navigate the world of academia and research, understanding the attitudes of TVL students can pave the way for cultivating a culture of curiosity, innovation, and knowledge seeking. Their feedback serves as a compass guiding educators and institutions in providing the necessary support and resources for an enriching research experience. So, let's embark on this journey of discovery and uncover the research prowess of TVL students. Are you ready to dive into the fascinating world of surveying the surveyors?

Top 100 Research Topics & Titles about Food & TVL

When you look for a good research paper topic, you can easily become the severest critic of any proposed idea. Some topics do not interest you at the very least, while others might shock your teachers. Where is the golden mean?

Check out this list of top 100 research paper questions and you will definitely find among them a captivating and inspiring idea for you. And remember to ask your friends to review your paper or proofread it by Grammarly.

⚒️ Practical Topics for TVL Students

• 🍲 60 TVL Topics on Food & Design
• 🌳 Good Topics Do Not Grow on Trees
• ⚡ Topics to Grab Everyone’s Attention
• 🔍 References

If you think that going to college is a waste of time, then you’re in the right place! Here you can start your TVL journey without any effort!

TVL is a technical-vocational livelihood. Here, you can find the best quantitative research topics for TVL students possible. With the help of the TVL track, you can start working and earning just after graduating high school. Let’s see how it is possible.

For example, most students finishing college don’t even know how to apply all the knowledge they gained over three to five years of studying. Some of them don’t also remember topics for practical research papers they wrote…

It creates a problem of too many graduates without practical skills. It takes them years of unpaid internships to finally start meeting the employers’ requirements. Then (maybe) they can begin earning the minimum wage. Later on, they find themselves stuck on the job they don’t like, “waiting for something better.”

But there is another option! And if you’re reading this, you decided to choose a TVL track! Dive deep and pick up a research topic about TVL strand to start your journey. It will provide you with real skills that are 100% relevant at all times! You can go for using a topic maker, too. Not a bad option.

Working on practical qualitative research topics for TVL students is the first step. You can find a list of interesting research titles about TVL strand below.

🍲 60 TVL Research Topics on Food & Design

• Dressmaking: the development of wedding dress models
• What are the most popular techniques of drafting in dressmaking?
• The most efficient pattern-making methods in dressmaking
• Fashion designers that changed the dressmaking forever
• Where do tailors and dressmakers seek for inspiration?
• How is computer modeling applied in the dressmaking process?
• The process of creating corsets that fit: a historical analysis
• The newest technologies in dressmaking: equipment you can’t miss
• The best methods of organizing working space to make dressmaking more efficient
• The development of the sewing machines up to modern times
• How does it fit and everything about sewing patterns?
• How have indie designers changed the fashion industry?
• The most common issues with the incorrectly chosen fabric
• The tricks to check the quality of the fabric and pick the best one
• Dressmaking as a creating culture: interviewing fashion designers

• Aerodynamics issues: designing a perfect Formula One racing car
• Car engineering: how is mileage improved in hybrid cars?
• What are the safest types of airbags in cars?
• Creating a robot car: what technologies are used?
• How to optimize the solar car: overcoming limitations?
• Modern cars and the benefits of automatic transmission
• How would hypercars improve the transportation experience?
• Challenges autonomous cars need to overcome
• What is the role of car engineers during the creation of autonomous cars?
• Car engineering: the future of using cryogenic fuels in cars
• Hydraulic linkages in the concept of the hy-wire cars
• Fuel cell system issues in the hy-wire cars: analyzing hydrogen properties
• Can air-powered cars be a solution for a zero-pollution future?
• Car designing: the role of rearward bias and its connection to aerodynamics
• The development of steam cars: a historical analysis
• How can you make crops immune to diseases?
• Agriculture: the aspects that affect the health of crops
• How does temperature affect the irrigation levels?
• The role GMO in agriculture: a case study of the US fields
• Possible ways to apply artificial intelligence in agriculture
• How do farmers use apps to foresee pest infections?
• Why should farmers keep an eye on export and import details?
• The methods of defining your prices: tracking the crops ratios
• What are the latest improvements in the gestational crates?
• The US regulations regarding the chemicals and pesticides
• Why should farmers be informed about all the changes in the policies?
• The methods of managing and adjusting the livestock population
• Is it better to start an organic farm rather than a conventional plane farming?
• The size matters: the reasons why new generations prefer smaller farms
• Why has hemp become such a popular crop recently?
• Fitting crops to the region: saving water and increasing profits
• How can optimizing tillage reduce the water use for farmers?
• What are the benefits of indoor vertical farming?
• Can covered crops help with controlling weeds?
• Analyzing sustainability of the crops: soil conservation
• Cookery: the benefits of pea protein over whey protein
• Younger generation stops drinking: the future of alcohol
• The rise of fast-food breakfast: overviewing the trends
• The impact of Italian cuisine on American food culture
• Why has intermittent fasting become so popular recently?
• Charcuterie as a part of the daily diet: pros and cons
• The development of a ghost kitchen concept: a case study of the US
• Why is being a flexitarian better than vegetarian?
• Low-sugar vs. stevia: contrast and compare the dietary benefits
• Adaptogens in everyday food: how takeaway can reduce your stress levels?

🌳 Good Research Paper Topics Do Not Grow on Trees

Surely, it is easier to find a good research paper topic, than to think of one from scratch. However, it might not be that easy to find topics – truly good research questions do not grow on trees. So don’t miss this opportunity and choose your topic from these great ideas (or ask us for professional writing help -all you have to do is just send a message):

• Are cell phones bad for your health?
• Is homosexuality genetic?
• Advertising : information vs. manipulation.
• Should businesses be ethical ?
• Is it possible to replace animal testing with other types of testing ?
• How to throw away our “throw-away” lifestyles?
• Should developed countries help Africa?
• Who is to blame for the European debt crisis ?
• Is the arms race over now?
• Is China a new superpower?
• Should students receive salaries during their studies?
• Can standard tests measure something meaningful, apart from students’ short-term memory?
• Does access to condoms in high schools encourage teen sex?
• Are social networks good or bad for teens?
• Does Internet need censorship?
• Is there a glass ceiling in today’s society ?
• Should prostitutes have their own labor unions?
• Is it possible to eliminate the black market?
• What is the solution to the problem of human trafficking ?
• Online banking : pros and cons.

⚡ Good Topics for Research Papers to Grab Everyone’s Attention

Do you want to grab everyone’s attention? Discover even more good research paper questions below:

• Are fast-food restaurants or fast food eaters to blame for obesity ?
• Is food labeling effective in controlling one’s calorie intake?
• Should parents punish their children for disobedience?
• Should spanking be outlawed?
• Isn’t the gap year between high school and college a waste of time?
• Has the “ American dream ” changed over the last decades?
• Can religious beliefs justify terrorism?
• Do people need a single world religion?
• Can racial profiling be useful?
• Islamophobia after 9/11.
• Emotional difficulties and eating disorders .
• Ways to encourage organ donation .
• Should mothers of Siamese twins have an abortion?
• The problem of personal identity in twins.
• Does their parents’ divorce have long-term consequences for children?
• Gender roles or gender stereotypes : where is the line?
• Is too much competition harmful to students?
• Do men need protection against feminists?
• What should be done about noise pollution ?
• Should people study body language ?

Impress your teachers by using any of these fresh and truly good research project ideas. Writing good research papers does not need to be difficult. Now that you have a brilliant idea, you are halfway to your stunning success.

Learn more on this topic:

• 280 Good Nursing Research Topics & Questions
• 226 Research Topics on Criminal Justice & Criminology
• 204 Research Topics on Technology & Computer Science
• 178 Best Research Titles about Cookery & Food
• 497 Interesting History Topics to Research
• 180 Best Education Research Topics & Ideas
• 110+ Micro- & Macroeconomics Research Topics
• 417 Business Research Topics for ABM Students
• 190+ Research Topics on Psychology & Communication
• 512 Research Topics on HumSS
• 281 Best Health & Medical Research Topics
• 501 Research Questions & Titles about Science
• A List of Research Topics for Students. Unique and Interesting

🔗 References

• Education Research Highlights
• Research Topics from Dartmouth College
• Learning Practical Research Skills Using An Academic Paper Framework – An Innovative, Integrated Approach (ScienceDirect)
• Practical Research and Evaluation: SAGE
• A Background for Practical Research: JSTOR
• Learning cooking skills at different ages: a cross-sectional study (BMC)
• Adolescents’ cooking skills strongly predict future nutritional well-being: ScienceDaily
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Pls give me 2 Quantitative research ralated to TVL strand.

Quantitative research Title related to TVL strand

Kindly give me some idea of quantitative research title in tvl HE strand at least 5 research title

kindly give me some ideas of qualitative research title in tvl strand

Can you give me a 5 research title about HUMSS track Qualitative Research

Hi good afternoon! I just wanted to ask if you can help me with the evaluating the practical skills of TVL students? I really really need your help

Can you give me 5 research title about tvl horticulture with author, year of publication, statement of the problem/purpose and findings

Hi can you give a 5 task about TVL that interest you the most or you find the necessity to venture into research project.

Research Topic about TVL strand

Experimental Research Title about TLE

Writing as Research and Research through Writing

This project reflects on the processes and products of designing a pilot course in academic and research writing in English for PhD research scholars in Sree Sankara University of Sanskrit (SSUS), Kalady, Kerala, India. The one-week (40 hours) intensive course was designed for my pedagogy-based Capstone Project for the IWT CLASP Fellows Program to investigate through a pilot designing of an Academic Writing in English Course for doctoral researchers from various disciplines in the humanities and social sciences, ranging from classical Indian music to European Philosophy and Sanskrit. The students are all non-native speakers of English who had their school education in the regional language of Kerala, Malayalam. They had not attended any academic writing course in their previous education. My goal was to test the relevance and appropriateness of some of the Bard College Institute for Writing & Thinking (IWT) Writing practices in such a multilingual and interdisciplinary classroom of doctoral researchers and reflect on the larger implications for designing academic writing courses based on practice for multilingual students in India. My primary conclusion is that Bard IWT practices, especially private freewriting, focused freewriting and writing to read in the zones are effective in generative writing inside and outside the classroom, facilitating discussion of academic writing processes, and significantly increasing the learner’s ability to generate more academic research-based text, as evident from the different kinds of feedback. Finally, I recommend that a skills-based (adapting IWT writing practices) content course can be a positive intervention in improving academic literacies for multilingual and inter-disciplinary learners in a setting like the state of Kerala, India.

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AI-assisted writing is quietly booming in academic journals. Here’s why that’s OK

Lecturer in Bioethics, Monash University & Honorary fellow, Melbourne Law School, Monash University

Disclosure statement

Julian Koplin does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

Monash University provides funding as a founding partner of The Conversation AU.

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If you search Google Scholar for the phrase “ as an AI language model ”, you’ll find plenty of AI research literature and also some rather suspicious results. For example, one paper on agricultural technology says:

As an AI language model, I don’t have direct access to current research articles or studies. However, I can provide you with an overview of some recent trends and advancements …

Obvious gaffes like this aren’t the only signs that researchers are increasingly turning to generative AI tools when writing up their research. A recent study examined the frequency of certain words in academic writing (such as “commendable”, “meticulously” and “intricate”), and found they became far more common after the launch of ChatGPT – so much so that 1% of all journal articles published in 2023 may have contained AI-generated text.

(Why do AI models overuse these words? There is speculation it’s because they are more common in English as spoken in Nigeria, where key elements of model training often occur.)

The aforementioned study also looks at preliminary data from 2024, which indicates that AI writing assistance is only becoming more common. Is this a crisis for modern scholarship, or a boon for academic productivity?

Who should take credit for AI writing?

Many people are worried by the use of AI in academic papers. Indeed, the practice has been described as “ contaminating ” scholarly literature.

Some argue that using AI output amounts to plagiarism. If your ideas are copy-pasted from ChatGPT, it is questionable whether you really deserve credit for them.

But there are important differences between “plagiarising” text authored by humans and text authored by AI. Those who plagiarise humans’ work receive credit for ideas that ought to have gone to the original author.

By contrast, it is debatable whether AI systems like ChatGPT can have ideas, let alone deserve credit for them. An AI tool is more like your phone’s autocomplete function than a human researcher.

The question of bias

Another worry is that AI outputs might be biased in ways that could seep into the scholarly record. Infamously, older language models tended to portray people who are female, black and/or gay in distinctly unflattering ways, compared with people who are male, white and/or straight.

This kind of bias is less pronounced in the current version of ChatGPT.

However, other studies have found a different kind of bias in ChatGPT and other large language models : a tendency to reflect a left-liberal political ideology.

Any such bias could subtly distort scholarly writing produced using these tools.

The hallucination problem

The most serious worry relates to a well-known limitation of generative AI systems: that they often make serious mistakes.

For example, when I asked ChatGPT-4 to generate an ASCII image of a mushroom, it provided me with the following output.

It then confidently told me I could use this image of a “mushroom” for my own purposes.

These kinds of overconfident mistakes have been referred to as “ AI hallucinations ” and “ AI bullshit ”. While it is easy to spot that the above ASCII image looks nothing like a mushroom (and quite a bit like a snail), it may be much harder to identify any mistakes ChatGPT makes when surveying scientific literature or describing the state of a philosophical debate.

Unlike (most) humans, AI systems are fundamentally unconcerned with the truth of what they say. If used carelessly, their hallucinations could corrupt the scholarly record.

Should AI-produced text be banned?

One response to the rise of text generators has been to ban them outright. For example, Science – one of the world’s most influential academic journals – disallows any use of AI-generated text .

I see two problems with this approach.

The first problem is a practical one: current tools for detecting AI-generated text are highly unreliable. This includes the detector created by ChatGPT’s own developers, which was taken offline after it was found to have only a 26% accuracy rate (and a 9% false positive rate ). Humans also make mistakes when assessing whether something was written by AI.

It is also possible to circumvent AI text detectors. Online communities are actively exploring how to prompt ChatGPT in ways that allow the user to evade detection. Human users can also superficially rewrite AI outputs, effectively scrubbing away the traces of AI (like its overuse of the words “commendable”, “meticulously” and “intricate”).

The second problem is that banning generative AI outright prevents us from realising these technologies’ benefits. Used well, generative AI can boost academic productivity by streamlining the writing process. In this way, it could help further human knowledge. Ideally, we should try to reap these benefits while avoiding the problems.

The problem is poor quality control, not AI

The most serious problem with AI is the risk of introducing unnoticed errors, leading to sloppy scholarship. Instead of banning AI, we should try to ensure that mistaken, implausible or biased claims cannot make it onto the academic record.

After all, humans can also produce writing with serious errors, and mechanisms such as peer review often fail to prevent its publication.

We need to get better at ensuring academic papers are free from serious mistakes, regardless of whether these mistakes are caused by careless use of AI or sloppy human scholarship. Not only is this more achievable than policing AI usage, it will improve the standards of academic research as a whole.

This would be (as ChatGPT might say) a commendable and meticulously intricate solution.

• Artificial intelligence (AI)
• Academic journals
• Academic publishing
• Hallucinations
• Scholarly publishing
• Academic writing
• Large language models
• Generative AI

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How Much Research Is Being Written by Large Language Models?

New studies show a marked spike in LLM usage in academia, especially in computer science. What does this mean for researchers and reviewers?

In March of this year, a  tweet about an academic paper went viral for all the wrong reasons. The introduction section of the paper, published in  Elsevier’s  Surfaces and Interfaces , began with this line:  Certainly, here is a possible introduction for your topic. 

Look familiar? 

It should, if you are a user of ChatGPT and have applied its talents for the purpose of content generation. LLMs are being increasingly used to assist with writing tasks, but examples like this in academia are largely anecdotal and had not been quantified before now. 

“While this is an egregious example,” says  James Zou , associate professor of biomedical data science and, by courtesy, of computer science and of electrical engineering at Stanford, “in many cases, it’s less obvious, and that’s why we need to develop more granular and robust statistical methods to estimate the frequency and magnitude of LLM usage. At this particular moment, people want to know what content around us is written by AI. This is especially important in the context of research, for the papers we author and read and the reviews we get on our papers. That’s why we wanted to study how much of those have been written with the help of AI.”

In two papers looking at LLM use in scientific publishings, Zou and his team* found that 17.5% of computer science papers and 16.9% of peer review text had at least some content drafted by AI. The paper on LLM usage in peer reviews will be presented at the International Conference on Machine Learning.

Read  Mapping the Increasing Use of LLMs in Scientific Papers and  Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews  

Here Zou discusses the findings and implications of this work, which was supported through a Stanford HAI Hoffman Yee Research Grant . 

How did you determine whether AI wrote sections of a paper or a review?

We first saw that there are these specific worlds – like commendable, innovative, meticulous, pivotal, intricate, realm, and showcasing – whose frequency in reviews sharply spiked, coinciding with the release of ChatGPT. Additionally, we know that these words are much more likely to be used by LLMs than by humans. The reason we know this is that we actually did an experiment where we took many papers, used LLMs to write reviews of them, and compared those reviews to reviews written by human reviewers on the same papers. Then we quantified which words are more likely to be used by LLMs vs. humans, and those are exactly the words listed. The fact that they are more likely to be used by an LLM and that they have also seen a sharp spike coinciding with the release of LLMs is strong evidence.

Some journals permit the use of LLMs in academic writing, as long as it’s noted, while others, including  Science and the ICML conference, prohibit it. How are the ethics perceived in academia?

This is an important and timely topic because the policies of various journals are changing very quickly. For example,  Science said in the beginning that they would not allow authors to use language models in their submissions, but they later changed their policy and said that people could use language models, but authors have to explicitly note where the language model is being used. All the journals are struggling with how to define this and what’s the right way going forward.

You observed an increase in usage of LLMs in academic writing, particularly in computer science papers (up to 17.5%). Math and  Nature family papers, meanwhile, used AI text about 6.3% of the time. What do you think accounts for the discrepancy between these disciplines? 

Artificial intelligence and computer science disciplines have seen an explosion in the number of papers submitted to conferences like ICLR and NeurIPS. And I think that’s really caused a strong burden, in many ways, to reviewers and to authors. So now it’s increasingly difficult to find qualified reviewers who have time to review all these papers. And some authors may feel more competition that they need to keep up and keep writing more and faster. 

You analyzed close to a million papers on arXiv, bioRxiv, and  Nature from January 2020 to February 2024. Do any of these journals include humanities papers or anything in the social sciences?  

We mostly wanted to focus more on CS and engineering and biomedical areas and interdisciplinary areas, like  Nature family journals, which also publish some social science papers. Availability mattered in this case. So, it’s relatively easy for us to get data from arXiv, bioRxiv, and  Nature . A lot of AI conferences also make reviews publicly available. That’s not the case for humanities journals.

Did any results surprise you?

A few months after ChatGPT’s launch, we started to see a rapid, linear increase in the usage pattern in academic writing. This tells us how quickly these LLM technologies diffuse into the community and become adopted by researchers. The most surprising finding is the magnitude and speed of the increase in language model usage. Nearly a fifth of papers and peer review text use LLM modification. We also found that peer reviews submitted closer to the deadline and those less likely to engage with author rebuttal were more likely to use LLMs. 

This suggests a couple of things. Perhaps some of these reviewers are not as engaged with reviewing these papers, and that’s why they are offloading some of the work to AI to help. This could be problematic if reviewers are not fully involved. As one of the pillars of the scientific process, it is still necessary to have human experts providing objective and rigorous evaluations. If this is being diluted, that’s not great for the scientific community.

What do your findings mean for the broader research community?

LLMs are transforming how we do research. It’s clear from our work that many papers we read are written with the help of LLMs. There needs to be more transparency, and people should state explicitly how LLMs are used and if they are used substantially. I don’t think it’s always a bad thing for people to use LLMs. In many areas, this can be very useful. For someone who is not a native English speaker, having the model polish their writing can be helpful. There are constructive ways for people to use LLMs in the research process; for example, in earlier stages of their draft. You could get useful feedback from a LLM in real time instead of waiting weeks or months to get external feedback. 

But I think it’s still very important for the human researchers to be accountable for everything that is submitted and presented. They should be able to say, “Yes, I will stand behind the statements that are written in this paper.”

*Collaborators include:  Weixin Liang ,  Yaohui Zhang ,  Zhengxuan Wu ,  Haley Lepp ,  Wenlong Ji ,  Xuandong Zhao ,  Hancheng Cao ,  Sheng Liu ,  Siyu He ,  Zhi Huang ,  Diyi Yang ,  Christopher Potts ,  Christopher D. Manning ,  Zachary Izzo ,  Yaohui Zhang ,  Lingjiao Chen ,  Haotian Ye , and Daniel A. McFarland .

Stanford HAI’s mission is to advance AI research, education, policy and practice to improve the human condition.  Learn more . 

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