Paper Presentations

The Other Benefits of Making AI-resistant Assessments

cdtlsd Paper Presentations , , ,

Olivier LEFEBVRE1,2
1Department of Civil and Environmental Engineering
2NUS Teaching Academy

ceelop@nus.edu.sg

 

Lefebvre, O. (2023). The other benefits of making AI-resistant assessments [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/the-other-benefits-of-making-ai-resistant-assessments/

SUB-THEME

AI and Education 

 

KEYWORDS

AI chatbots, AI-resistant assessments, authentic assessments

 

CATEGORY

Paper Presentation 

 

ABSTRACT

Over the past one year, the world has witnessed growing concerns in relation with the rise in performance of artificial intelligence (AI) chatbots at a rate much faster than our own ability to comprehend all the implications, leading to questions on whether we should slow down or even halt the “race to god-like AI”1. In the academic world, concerns are mostly related about the way to assess students in this new day and age, where ChatGPT has been found to pass entry exams in fields as varied as medicine, law or business schools (Wilde, 2023). Such legitimate concerns have resulted in diverse responses from many universities over the world, from banning AI chatbots altogether, such as in French University Sciences Po (Sciences Po, 2023), to providing guidelines and recommendations for staff and for students, such as the choice made by NUS in our interim policy guidelines (NUS Libraries, n. d.).

 

The plagiarism issues and risks of other acts of academic dishonesty are real, but this is not the first time that we have to face such issues. At the peak of the COVID-19 pandemic, students were asked to take their exams from home, and in many cases, the simple conversion of a pen-and-paper exam into a digital one, without rethinking the entire assessment, had led to a rising number of plagiarism and other cheating cases. Similarly, as with the COVID-19 pandemic, can we once again rethink our assessments and not only proof them against abuse from AI but also take this opportunity to deliver more meaningful assessments, in better adequation with the skills that our students need in this day and age (Mimirinis, 2019)? Instead of banning ChatGPT and the like, should we just acknowledge that AI is here to stay, and design assessments that question higher-order thinking skills, allowing at the same to distinguish between students who engage in surface learning and those who have achieved a real deep understanding of the topic? Such exams would constitute a form of authentic assessment, by recreating the conditions that students will apply their knowledge in their professional environment (Shand, 2020).

 

In this talk, I will present some general guidelines on what kind of exam can at the same time test students for higher-order thinking skills and resist AI chatbots. Real examples will be provided, where students are asked to:

  • Deliver a critical analysis of a scientific paper
  • Interpret graphs or images
  • Solve ill-defined and complex problems

 

I will show how well (or not) these exams resist ChatGPT and compare the AI output to that of real (anonymised) students over a range of performance (excellent, average, marginal). I will conclude with the limitations, e.g., the risk to increase the difficulty of the exam by a too large margin, making it difficult for the weaker students to perform reasonably well.

 

ENDNOTE

  1. Refer to https://www.ft.com/content/03895dc4-a3b7-481e-95cc-336a524f2ac2 for details.

 

REFERENCES

Mimirinis, M. (2019). Qualitative differences in academics’ conceptions of e-assessment. Assessment & Evaluation in Higher Education, 44(2), 233-48. http://dx.doi.org/10.1080/02602938.2018.1493087

NUS Libraries (n. d.). Academic integrity essentials. https://libguides.nus.edu.sg/new2nus/acadintegrity

Sciences Po (2023, January 27). Sciences Po bans the use of ChatGPT without transparent referencing. https://newsroom.sciencespo.fr/sciences-po-bans-the-use-of-chatgpt/

Shand, G. (2020). Bringing OSCEs into the 21st century: Why internet access is a requirement for assessment validity. Medical Teacher, 42(4), 469-71. http://dx.doi.org/10.1080/0142159X.2019.1693527

Wilde, J. (2023, January 27). ChatGPT passes medical, law, and business exams. Morning Brew. https://www.morningbrew.com/daily/stories/2023/01/26/chatgpt-passes-medical-law-business-exams

 

Opening up the Classroom: Student-led Learning in a Law and Society Course

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George Baylon RADICS
Deparment of Sociology and Anthropology, NUS and NUS College

socrgb@nus.edu.sg

 

Radics, G. B. (2023). Opening up the classroom: Student-led learning in a law and society course [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/opening-up-the-classroom-student-led-learning-in-a-law-and-society-course/

SUB-THEME

Interdisciplinarity and Education 

 

KEYWORDS

Student-led learning, project-based work, active learning, interdisciplinary, independent thinking

 

CATEGORY

Paper Presentation 

 

ABSTRACT

Upon graduation, students are expected to lead as opposed to follow, collaborate as opposed to compete, and think broadly as opposed to narrowly. Thus, university education is changing in response to evolving student needs and the realities of workplace. Traditional lectures, heavily weighted final exams, and research papers on narrow topics do not build the skills students need to survive the increasingly competitive job market. Student-led learning provides an opportunity for students to take ownership over their education through leading class discussions and collaborative project-based work. This presentation will explore a student-led learning course at NUS College entitled “Law in the Making”, where students led discussions on legal issues, set up meetings with lawmakers, and drafted a law that they debated at the end of the course.

 

Student-led teaching involves students teaching to their peers, whilst their peers participate actively in the process to facilitate student-led learning (Marvell et al., 2013). Here, educators seek to empower their students by giving them control of and responsibility for their learning (McKeachie, 1990; Candy, 1991). Business schools experimented with case studies to develop more dynamic, well-rounded problem solvers (Christenson, 1987), while the fields of accountancy (Adler et al., 2007), geography (Marvell et al., 2013), and pharmacy (Po, 1994) have also attempted to create student-led teaching approaches to do the same. “When asked what student skills needed improving there was remarkable agreement across a wide range of employers. All felt that non-technical skills needed further development…namely interpersonal skills, team working, presentation, report writing, CV design, project management, time management” (Sneddon et al., 1995, p. 84). At the same time, there has been a growing recognition that traditional methods of teaching (primarily tutorials and lectures) may perpetuate the opposite, namely dependency and passivity (Kremer & McGuiness, 1998).

 

While NUS has gained international recognition for its research, further efforts can be made to re-envision the classroom and move further away from traditional “chalk and talk” lectures and tutorials. NUS College, the university’s new honours college aims to “break open the classroom” and to provide “rigorous and stimulating interdisciplinary education designed to help students cultivate the necessary skills to work effectively across boundaries, so that they are able to respond to the challenges of the 21st century.” In the NUS College course NHS2059 entitled “Law in the Making,” students were each assigned a reading to discuss in class, worked in groups to set up meetings with lawmakers, and formed teams to draft a law that they debated at the end of the course. While the course attempted to place more control in the hands of the students, certain challenges emerged, such as complaints of being overworked, underdeveloped professional communication skills, and an overreliance on technology to support public speaking.

 

This paper will begin with a review of the literature on student-lead learning, then discuss how it was applied to the course NHS2059 “Law in the Making”. The presentation will then explore some of the challenges encountered in the course, as well as some strategies employed to address them. It will provide a glimpse into how student-led learning has the potential to empower students to become more engaged and interested in learning so long as the right balance of student-led and traditional teacher-led methods are employed. Additionally, it asserts that the right incentives can encourage prompt and professional communication, and teaching students how to become better teachers can reduce their overreliance on technology.

 

REFERENCES

Adler, R. W., Whiting, R. H., Wynn-Williams, K. (2004). Student-led and teacher-led case presentations: empirical evidence about learning styles in an accounting course. Accounting Education, 13(2), 213-29. https://doi.org/10.1080/09639280410001676620

Candy, P. C. (1991). Self-direction for the lifelong learner. Jossey-Bass.

Christensen, C. R. (1987). Teaching and the case method. Harvard Business School.

Kremer, J., & McGuinness, C. (1998). Cutting the cord: student‐led discussion groups in higher education. Education + Training, 40(2), 44-49. https://doi.org/10.1108/00400919810206848

Marvell, A., Simm, D., Schaaf, R., & Harper, R. (2013). Students as scholars: evaluating student-led learning and teaching during fieldwork. Journal of Geography in Higher Education, 37(4), 547-66. https://doi.org/10.1080/03098265.2013.811638

McKeachie, W. J. (1990). Research on college teaching: the historical background. Journal of Educational Psychology, 82(2), 189–200. https://psycnet.apa.org/doi/10.1037/0022-0663.82.2.189

Po, L. A. (1994), Brainstorming a pharmacy syllabus: involving employers in curriculum design, in I. Sneddon, & J. Kremer (eds), An Enterprising Curriculum: Teaching Innovations in Higher Education, HMSO, Belfast.

Sneddon, I., Kremer, J., & Lindsay, B. (1995). Evaluating Enterprise at Queen’s, APAS, Belfast.

 

Teaching Augmentative Uses of ChatGPT and Other Generative AI Tools

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Jonathan Y. H. SIM
Department of Philosophy, Faculty of Arts and Social Sciences (FASS)

jyhsim@nus.edu.sg

 

Sim, J. Y. H. (2023). Teaching augmentative uses of ChatGPT and other generative AI tools [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/teaching-augmentative-uses-of-chatgpt-and-other-generative-ai-tools /

SUB-THEME

AI and Education 

 

KEYWORDS

ChatGPT, generative AI, philosophy of technology, AI augmentation

 

CATEGORY

Paper Presentation 

 

ABSTRACT

Since the rise of generative artificial intelligence (GenAI) like ChatGPT, educators have expressed concerns that students may misuse these tools by growing too reliant on them or use it to take shortcuts in their learning, thus undermining important learning objectives that we set for them.

 

Such concerns are not new in the history of technology. Socrates was one of the first to voice concerns about how the invention of writing would be detrimental to people’s memories:

“[Writing] will implant forgetfulness in their souls; they will cease to exercise memory because they rely on that which is written, calling things to remembrance no longer from within themselves, but by means of external marks.” (Phaedrus, 274b-277a)

 

Common to these complaints is the fear that new technologies will replace existing human processes—as a substitutive tool—leading to a deterioration or loss of certain human abilities. This is not the only approach to technology—we can also use these tools in an augmentative way to enhance existing human abilities and processes (Eors Szathmary et al, 2018). While we may not have memories as strong as the ancients did, writing has since augmented our thinking abilities, allowing us to easily record, recall, transmit, evaluate, analyse, and synthesise far more information than before.

 

This augmentative approach can also be applied to GenAI tools, like ChatGPT. 19.1% of my students (n=351) found ways to use ChatGPT as an augmentative tool rather than as a substitutive tool:

  • As an idea generator or a sounding board to help develop ideas before working on an assignment
  • As a learning resource to teach/explain concepts or clarify confusions
  • As a tool to improve their expression

 

Admittedly, it can be difficult for non-savvy users to think of augmentative uses. Students are commonly exposed to substitutive applications of ChatGPT in learning, and 65.5% of students did not think skills were required to use it well.

 

How can educators encourage effective augmentative uses of GenAI tools? I believe there are three learning objectives we should focus on:

 

(1) Cultivate a collaborative mindset working with GenAI. Knowing how to talk is not the same as knowing how to work well in a team. Learners must feel comfortable and empowered working with GenAI as a collaborative partner if they are to use it as an augmentative tool. One approach is to incorporate activities that involve collaborating with GenAI. In my course, students are to work alongside ChatGPT to develop an evaluation criterion for ride-sharing services, seeking feedback from it while also evaluating its feedback.

 

(2) Develop critical questioning skills. Learners need to learn how to scrutinise GenAI output as the content may be inaccurate or shallow. Throughout the same tutorial, students were challenged to find flaws with ChatGPT’s suggestions, and to find areas where they can improve the quality of ChatGPT’s output. The exercise helped them to recognise that an AI’s answer is far from perfect, and that they cannot take a seemingly well-written work as the final answer. Human intervention and scrutiny is still necessary as the AI’s work is, at best, a draft suggestion.

 

(3) Master the art of prompting. The quality of AI output is dependent on the quality and clarity of instructions given to it. Learners need to hone their ability to articulate their requirements well. Later in the same tutorial, students were given a prompt for ChatGPT to generate a pitch. They were then tasked with identifying shortcomings to the output and to produce better prompts to overcome those issues.

 

After the tutorial, many students reported newfound confidence and competency in utilising ChatGPT (n=351):

Table 1
Students’ perception of ChatGPT competency before and after tutorial

I considered myself very competent in using ChatGPT
Before Tutorial
(Average 2.76)		 After Tutorial
(Average 3.71)
5 – Strongly Agree  5.41% 15.67%
4 22.79% 47.29%
3 27.07% 29.91%
2 31.91% 6.84%
1–Strongly Disagree 12.82% 0.28%

 

Table 1
Students’ perception of ChatGPT competency before and after tutorial

The tutorial taught me how to effectively collaborate and work with an AI for work.
(Average 4.19)		 The tutorial taught me how to effectively critique and evaluate AI generated output so that I don’t take the answers for granted.
(Average 4.34)		 The tutorial taught me how to design better prompts to get better results.
(Average 4.38)		 I believe the skills taught in Tutorial 4 are useful for me when I go out to work.
(Average 4.28)
30.77% 40.46% 43.87% 38.46%
58.69% 53.56% 50.43% 52.71%
9.69% 5.70% 5.41% 7.41%
0.85% 0.28% 0.28% 1.42%
0% 0% 0% 0%

 

Overall, students had positive experiences learning this new approach to AI. They felt empowered and even an optimism about their future—knowledge of using AI in an augmentative way opens doors of opportunities that seemed too distant previously. In one case, a social science major shared how he felt so empowered by the tutorial that he took on a coding internship (despite being new to coding). He used ChatGPT to learn how to code which facilitated him to handle coding projects at work. This augmentative approach not only allowed him to produce solutions but also evaluate them much faster than if he did it on his own.

 

I firmly believe that teaching students how to augment their learning with GenAI tools holds immense potential in empowering our students for the future.

 

REFERENCES

Eors Szathmary et al. (2018). Artificial or augmented intelligence? the ethical and societal implications. In J. W. Vasbinder, B. Gulyas. & J. W. H Sim (Eds.), Grand Challenges for Science in the 21st Century. World Scientific.

Plato. (1952). Phaedrus. Trans. Reginald Hackforth. Cambridge University Press.

 

Teaching a Large-class Transdisciplinary Course—Challenges and Enablers

cdtlsd Paper Presentations , , , ,

Aaron Eng Seng CHIA
Department of Industrial Systems Engineering and Management,
College of Design and Engineering (CDE)

aaron_chia@nus.edu.sg

 

Chia, A. E. S. (2023). Teaching a large-class transdisciplinary course—Challenges and enablers [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/teaching-a-large-class-transdisciplinary-course-challenges-and-enablers/

SUB-THEME

Interdisciplinarity and Education 

 

KEYWORDS

Transdisciplinary, interdisciplinary, large-scale systems engineering, systems thinking

 

CATEGORY

Paper Presentation 

 

INTRODUCTION

A master’s elective, IE5404 “Large Scale Systems Engineering (LSSE)” was converted into a core course this year. As such, the class size ballooned from about 30 students to 82 students. This requires rethinking on how to teach already challenging systems concepts to large classes. This paper describes the challenges and enablers of conducting such a course.

 

LSSE deals with the complexities of large-scale systems using systems approach and systems engineering to understand and conceptualise the planning, design, and management of large-scale systems. Large-scale systems are inherently transdisciplinary/interdisciplinary. For example, an economic system is not just about business, but politics, technology, people, environment, the legal system, and so on. In addition, students learn about interconnections between different parts of the system, stakeholder’s behaviours, ecosystems, decision making and unintended consequences, cost analysis, and so on.

 

CHALLENGES AND ENABLERS

A large part of an engineer’s education is often technical/analytical in nature, and this makes teaching systems concepts challenging (Azad & Moore, 2022). Moreover, systems concepts cover organisations, behaviours, and dynamics, topics that engineers are often not familiar. In previous courses, the pedagogy includes lectures, cases, stories, role play, videos, class discussions, e-forum, assignments, group projects, examinations, readings, and self-reflection. With smaller classes, lectures took up about 50% of the time, with cases, stories, role play, and discussions taking the remaining time. However, it will not be possible to engage students well, given the same amount of time and almost triple the class size. Hence, questions to myself were:

  1. Which pedagogy needs to be modified/ changed to engage large classes?
  2. How to use student and lecturer’s time more effectively in class and assessments?

 

Teach Less Learn More

The concept of teaching less is doing things differently (Blankenship, 2019). Hence, the lecture materials were reduced, giving more time for discussions and questions. This was supplemented by more reading materials for students to learn by themselves. For master’s courses, the amount of tutorial time is either reduced or non-existent. A 30-minute tutorial was introduced for each session. This allowed time to work on difficult problems or concepts. It also allowed students to work on their projects. The project was structured such that students could carry out one part after each session. Students applied immediately what they have learned and clarify any doubts they have. This would also reduce their time to meet up for discussions later—important for part-time students where time is a premium.

 

Assessment as Pedagogy

The use of assessments in promoting deep learning in higher institutions have been advocated by many (Masuku et al, 2021). In the past, students did an individual assignment and comments/ feedback were given to the students. In the large class, students carried out a group assignment by watching a video (e.g., poverty) before answering questions. They got to discuss and learn from one another. It was also found that feedback to the group assignments were less than the individual assignments. This also reduced the amount of marking required.

 

Another new element introduced was a peer review of each other’s interim group project. Previously, groups presented their projects at the end of the semester. Students were able to get more formative feedback on their learning through their peers (although this introduced more work for the lecturer).

 

With large classes, there would not be enough time for all the groups to present during class time. Here, students made a video of their group presentation. In this way, they could improve their presentations and the lecturer had more time to evaluate them. The drawback was that there was no question-and-answer (Q&A) from the lecturer and class. This was mitigated by the earlier peer reviews and lecturer feedback via the report.

 

Student Feedback

The students like the concepts learned and the case studies. The common feedback given (even in previous courses) was that while they understood the need to cover diverse topics, the scope was wide, and some topics (especially non-engineering ones) were difficult to understand. More than half of the feedback respondents (57) for the large class nominated the lecturer for teaching awards (first time this has occured).

 

SIGNIFICANCE OF STUDY

The axiom ‘Teach Less, Learn More” is often true. Students can obtain facts from the Internet and even answers from CHATGPT. Hence, class time is best spent teaching metacognitive thinking. Assessment as a pedagogy is even more important now.

 

REFERENCES

Azad, A., and Moore, E. (2022). Lessons learned from teaching systems thinking to engineering students. Canadian Engineering Education Association (CEEA-ACEG22) Conference Proceedings.

Blankenship, S. (2019). Teach Less Learn More. Kreatif Beats. https://kreatifbeats.com/2019/03/16/teach-less-learn-more/

Masuku, M. M., Jili, N. N., & Sabela, P. T. (2021). Assessment as a pedagogy and measuring tool in promoting deep learning. International Journal of Higher Education, 10(2). https://doi.org/10.5430/ijhe.v10n2p274

 

Harnessing the Potential of Generative AI in Medical Undergraduate Education Across Different Disciplines—Comparative Study on Performance of ChatGPT in Physiology and Biochemistry Modified Essay Questions

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W. A. Nathasha Vihangi LUKE1*, LEE Seow Chong2, Kenneth BAN2, Amanda WONG1, CHEN Zhi Xiong1,3, LEE Shuh Shing3 , Reshma Taneja1,
Dujeepa SAMARASEKARA3, Celestial T. YAP1

1Department of Physiology, Yong Loo Lin School of Medicine (YLLSOM)
2Department of Biochemistry, YLLSOM
3Centre for Medical Education, YLLSOM

*nathasha@nus.edu.sg

 

Luke, W. A. N. V., Lee, S. C., Ban, K., Wong, A., Chen, Z. X., Lee, S. S., Taneja, R., Samarasekara, D., & Yap, C. T. (2023). Harnessing the potential of generative AI in medical undergraduate education across different disciplines—comparative study on performance of ChatGPT in physiology and biochemistry modified essay questions [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/harnessing-the-potential-of-generative-ai-in-medical-undergraduate-education-across-different-disciplines-comparative-study-on-performance-of-chatgpt-in-physiology-and-biochemistry-modified-es/ 
 

SUB-THEME

AI and Education

 

KEYWORDS

Generative AI, artificial intelligence, large language models, physiology, biochemistry

 

CATEGORY

Paper Presentations

 

INTRODUCTION & JUSTIFICATION

Revolutions in generative artificial intelligence (AI) have led to profound discussions on its potential implications across various disciplines in education. ChatGPT passing the United States medical school examinations (Kung et al., 2023) and excelling in other discipline-specific examinations (Subramani et al., 2023) displayed its potential to revolutionise medical education. Capabilities and limitations of this technology across disciplines should be identified to promote the optimum use of the models in medical education. This study evaluated the performance of ChatGPT, a large language model (LLM) by Open AI, powered by GPT 3.5, in modified essay questions (MEQs) in physiology and biochemistry for medical undergraduates.

 

METHODOLOGY

Modified essay questions (MEQs) extracted from physiology and biochemistry tutorials and case-based learning scenarios were encoded into ChatGPT. Answers were generated for 44 MEQs in physiology and 43 MEQs in biochemistry. Each response was graded by two examiners independently, guided by a marking scheme. In addition, the examiners rated the answers on concordance, accuracy, language, organisation, and information and provided qualitative comments. Descriptive statistics including mean, standard deviation, and variance were calculated in relation to the average scores and subgroups according to Bloom’s Taxonomy. Single factor ANOVA was calculated for the subgroups to assess for a statistically significant difference.

 

RESULTS

ChatGPT answers (n = 44) obtained a mean score of 74.7(SD 25.96) in physiology. 16/44(36.3%) of the ChatGPT answers scored 90/100 marks or above. 29.5%, numerically 13/44, obtained a score of 100%. There was a statistically significant difference in mean scores between the higher-order and lower-order questions on the Bloom’s taxonomy (p < 0.05). Qualitative comments commended ChatGPT’s strength in producing exemplary answers to most questions in physiology, mostly excelling in lower-order questions. Deficiencies were noted in applying physiological concepts in a clinical context.

 

The mean score for biochemistry was 59.3(SD 26.9). Only 2/43(4.6%) obtained 100% scores for the answers, while 7/43(16.27%) scored 90 or above marks. There was no statistically significant difference in the scores for higher and lower-order questions of the Bloom’s taxonomy. The examiner’s comments highlighted those answers lacked relevant information and had faulty explanations of concepts. Examiners commented that outputs demonstrated breadth, but not the depth expected.

nathasha luke et al, - Distribution of scores

Figure 1. Distribution of scores.

 

CONCLUSIONS AND RECOMMENDATIONS

Overall, our study demonstrates the differential performance of ChatGPT across the two subjects. ChatGPT performed with a high degree of accuracy in most physiology questions, particularly excelling in lower-order questions of the Bloom’s taxonomy. Generative AI answers in biochemistry scored relatively lower. Examiners commented that the answers demonstrated lower levels of precision and specificity, and lacked depth in explanations.

 

The performance of language models largely depends on the availability of training data; hence the efficacy may vary across subject areas. The differential performance highlights the need for future iterations of LLMs to receive subject and domain-specific training to enhance performance.

 

This study further demonstrates the potential of generative AI technology in medical education. Educators should be aware of the abilities and limitations of generative AI in different disciplines and revise learning tools accordingly to ensure integrity. Efforts should be made to integrate this technology into learning pedagogies when possible.

 

The performance of ChatGPT in MEQs highlights the ability of generative AI as educational tools for students. However, this study confirms that the current technology might not be in a state to be recommended as a sole resource, but rather be a supplementary tool along with other learning resources. In addition, the differential performance in subjects should be taken into consideration by students when determining the extent to which this technology should be incorporated into learning.

 

REFERENCES

Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., & Tseng, V. (2023). Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLOS Digital Health, 2(2), e0000198. https://doi.org/10.1371/journal.pdig.0000198

 Subramani, M., Jaleel, I., & Krishna Mohan, S. (2023). Evaluating the performance of ChatGPT in medical physiology university examination of phase I MBBS. Advances in Physiology Education, 47(2), 270–71. https://doi.org/10.1152/advan.00036.2023

 

Doing But Not Creating: A Theoretical Study of the Implications of ChatGPT on Paradigmatic Learning Processes

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Koki MANDAI1, Mark Jun Hao TAN1, Suman PADHI1, and Kuin Tian PANG1,2,3 

1*Yale-NUS College
2Bioprocessing Technology Institute, Agency for Science, Technology, and Research (A*STAR), Singapore
3School of Chemistry, Chemical Engineering, and Biotechnology, Nanyang Technology University (NTU), Singapore

*m.koki@u.yale-nus.edu.sg

 

Mandai, K, Tan, J. H. M., Padhi, S., & Pang, K. T. (2023). Doing but not creating: A theoretical study of the implications of ChatGPT on paradigmatic learning processes [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/doing-but-not-creating-a-theoretical-study-of-the-implications-of-chatgpt-on-paradigmatic-learning-processes/

SUB-THEME

AI and Education

 

KEYWORDS

AI, artificial intelligence, education, ChatGPT, learning, technology

 

CATEGORY

Paper Presentation 

 

CHATGPT AND LEARNING FRAMEWORKS

Introduction

Since the recent release of ChatGPT, developed by OpenAI, multiple sectors have been affected by it, and educational institutions are not only affected by this trend but are also more deeply impacted compared to other fields (Dwivedi et al., 2023; Eke, 2023; Rudolph et al., 2023). Following the sub-theme of “AI and Education”, we conduct a systematic investigation into the educational uses of ChatGPT and its quality as a tool for learning, teaching, and assessing, mainly in higher education. Research is carried out using comprehensive literature reviews of the current and future educational landscape and ChatGPT’s methodology and function, while applying major educational theories as the main component for the construction of the evaluative criteria. Findings will be presented via a paper presentation.

 

Theoretical Foundations and Knowledge Gaps

Current literature on the intersections of education and artificial intelligence (AI) consists of variegated and isolated critiques of how AI impacts segments of the educational process. For instance, there is a large focus on the general benefits or harms in education (Baidoo-Anu & Ansah, 2023; Dwivedi et al., 2023; Mhlanga, 2023), rather than discussion of specific levels of learning that students and teachers encounter. Furthermore, there seems to be a lack of analysis on the fundamental change and reconsideration of the meaning of education that may occur due to the introduction of AI. The situation can be described as a Manichean dichotomy, as one side argues for the expected enhancements and improved efficiency in education (Ray 2023; Rudolph et al., 2023), while the other side argues for the risks of losing knowledge/creativity and the basis of future development (Chomsky, 2023; Dwivedi et al., 2023; Krügel et al., 2022/2023).

 

By referring to John Dewey’s reflective thought and action model for the micro-scale analysis (Dewey, 1986; Gutek, 2005; Miettinen, 2000) and a revision of Bloom’s taxonomy for the macro-scale analysis (Elsayed, 2023; Forehand, 2005; Kegan, 1977; Seddon, 1978), we consider the potential impact of ChatGPT over progressive levels of learning and the associated activities therein. These models were mainly chosen due to their hierarchical framework that allows for easy application in evaluation compared to other models, although this does not indicate that these models are superior to others; the evaluative criteria we aim to construct will be comprehensive, thus what our research provides is a possible base for future improvements. Moreover, we also incorporate insights from multiple perspectives that are not limited to educational theory, such as from the fields of policy and philosophy with the diverse backgrounds in our research team.

 

Purpose and Significance of the Present Study

This study sought to answer questions regarding the viability of ChatGPT as an educational tool, its proposed benefits and harms, and potential obstacles educators may face in its uptake, as well as relevant safeguards against those obstacles.

 

Furthermore, we suggest a possible base for a new theoretical framework in which ChatGPT is explicitly integrated with standard educational hierarchies, in order to provide better instruction to educators and students. This study aims to safely pioneer a baseline for policy considerations on it as an education tool made to either ameliorate or deteriorate. As a result, ChatGPT can be ratified in educational institutions with accompanying developmental policies to be considered and amended in governmental legislatures for wider educational use.

 

Potential Findings/Implications

The expectations from the existing literature suggest that in keeping with intuitions regarding higher-level learning, ChatGPT itself seems to be limited to do—that is, it is only able to process lower to mid-level learning comprising repetitive actions like remembering, understanding, applying, and analysing (Dwivedi, 2023; Elsayed 2023). Some literature also positions ChatGPT as less useful directly in higher-level processes of creation like evaluation and creation of new knowledge, and can even be said to hinder them (Crawford, 2023; Rudolph, 2023). Even within the lower-level process, there is a high concern for overreliance that will potentially lead to dullness of the learners (Halaweh, 2023; Ray, 2023). Yet under the lens of educational theories that this paper so far applied, there seems to be a possibility that ChatGPT may be able to assist higher-order skills such as creativity and related knowledge acquisition. As the net benefit of ChatGPT on education may more or less depend on external factors such as educational fields, the personality of the user, and the environment that we have yet to take into account of, it requires further research to determine its optimal usage in education. Still, this attempt may be one of the first steps to construct an evaluative criteria for the new era of education with AIs.

 

REFERENCES

Baidoo-Anu, D. & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. SSRN. https://ssrn.com/abstract=4337484

Crawford, J., Cowling, M., & Allen, K. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI). Journal of University Teaching & Learning Practice, 20(3). https://doi.org/10.53761/1.20.3.02

Chomsky, N, et al. (2023). Noam Chomsky: The False Promise of ChatGPT. The New York Times. www.nytimes.com/2023/03/08/opinion/noam-chomsky-chatgpt-ai.html

Dewey, J. (1986). Experience and education. The Educational Forum, 50(3), 241-52. https://doi.org/10.1080/00131728609335764

Dwivedi, Y. K. et al. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 1-63. https://doi.org/10.1016/j.ijinfomgt.2023.102642

Eke, D. O. (2023). ChatGPT and the rise of generative AI: Threat to academic integrity? Journal of Responsible Technology, 13, 1-4, https://doi.org/10.1016/j.jrt.2023.100060

Elsayed, S. (2023). Towards mitigating ChatGPT’s negative impact on education: Optimizing question design through Bloom’s taxonomy. https://doi.org/10.48550/arXiv.2304.08176

Forehand, M. (2005). Bloom’s taxonomy: Original and revised. In M. Orey (Ed.), Emerging perspectives on learning, teaching, and technology. http://projects.coe.uga.edu/epltt/

Gutek, G. L. (2005). Jacques Maritain and John Dewey on education: A reconsideration. Educational Horizons, 83(4), 247–63. http://www.jstor.org/stable/42925953

Halaweh, M. (2023). ChatGPT in education: Strategies for responsible implementation. Contemporary Educational Technology, 15(2), ep421. https://doi.org/10.30935/cedtech/13036

Kegan, D. L. (1977). Using Bloom’s cognitive taxonomy for curriculum planning and evaluation in nontraditional educational settings. The Journal of Higher Education, 48(1), 63–77. https://doi.org/10.2307/1979174

Krügel, S., Ostermaier, A. & Uhl, M (2023). ChatGPT’s inconsistent moral advice influences users’ judgment. Sci Rep 13, 4569. https://doi.org/10.1038/s41598-023-31341-0

Krügel, S., Ostermaier, A. & Uhl, M. Zombies in the loop? Humans trust untrustworthy AI-advisors for ethical decisions. (2022) Philos. Technol. 35, 17. https://doi.org/10.1007/s13347-022-00511-9

Mhlanga, D. (2023). Open AI in Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning SSRN, https://ssrn.com/abstract=4354422

Miettinen, R. (2000). The concept of experiential learning and John Dewey’s theory of reflective thought and action, International Journal of Lifelong Education, 19(1), 54-72. https://doi.org/10.1080/026013700293458

Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121-154, https://doi.org/10.1016/j.iotcps.2023.04.003

Rudolph, J., Tan, S., Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning & Teaching, 6(1), 1-22. https://journals.sfu.ca/jalt/index.php/jalt/article/view/689

Seddon, G. M. (1978). The properties of Bloom’s Taxonomy of educational objectives for the cognitive domain. Review of Educational Research, 48(2), 303–23. https://doi.org/10.2307/1170087

 

Does Promoting Diversity of Opinion in Collaborative Learning in Conservation Enhance Student Learning?

cdtlsd Paper Presentations , , , , ,

Ian Zhi Wen CHAN
Department of Biological Sciences, Faculty of Science (FOS)

ianchan@nus.edu.sg

 

Chan, I. Z. W. (2023). Does promoting diversity of opinion in collaborative learning in conservation enhance student learning? [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/does-promoting-diversity-of-opinion-in-collaborative-learning-in-conservation-enhance-student-learning/

SUB-THEME

Communities and Education 

 

KEYWORDS

Diversity, collaborative learning, learning outcomes, learning objectives, conservation

 

CATEGORY

Paper Presentation 

 

ABSTRACT

The use of pedagogical techniques to promote collaborative learning has wide-ranging social, psychological, and academic benefits for students (Panitz, 1996; Laal & Ghodsi, 2012). Academically, the successful implementation of collaborative learning results in increased student motivation, improved learning, and generally enhanced classroom results. However, there exist many potential pitfalls along the process of forming and working in groups which can detrimentally affect learning (Bitzer, 1999), such as differing motivation levels amongst group members and potentially disruptive interpersonal conflict. It is important for educators to be aware of these hazards to manage them well.

 

One area that would benefit from further study is how diversity in groups affects learning outcomes. In the literature, diversity is often seen as a challenge to be overcome (Ashman & Gillies, 2013) or a problem to be solved through collaborative learning as a form of social intervention, e.g. see the Jigsaw method (Aronson, n.d.) and Loes et al. (2018). Anecdotally, educators typically try to achieve a balance—too little diversity may lead to less robust discussions and groupthink, whereas too much could cause excessive conflict (Barkley et al., 2014). Yet, how the presence (or absence) of diversity in groups affects eventual academic outcomes such as the achievement of learning outcomes is generally not well researched—as an exception, see Curşeu et al.’s (2018) study on the benefits of gender diversity. In this study, I ask whether assigning students to work in groups with diverse views on a divisive topic in Conservation Biology enhances their learning.

 

Today over 42,000 plant and animal species are threatened with extinction. Conservation action is crucial to protect them but many academics and practitioners disagree fundamentally on what kind of action should be taken. Together with the emotional and evocative nature of the problem, this has led to heated arguments, even in the literature. In an attempt to update Soulé’s (1985) original “Traditional Conservation”, Kareiva and Marvier (2012) put forth new ideas which became known as “New Conservation”. These ideas did not sit well with Soulé (2014) who said, “[…] it does not deserve to be labelled conservation” (p. 895), prompting replies from Marvier (2014) “New Conservation is True Conservation” and others. Over the past two years, I have observed a similar (if less vocal) divide amongst my students in the course LSM4262 “Tropical Conservation Biology”, and I ask whether assigning students with differing views on this divisive topic to the same group will enhance their learning over the course of a semester.

Students’ opinions on three issues in conservation—people-centredness, the role of science, and the role of capitalism—can be broadly used to identify whether they prefer “Traditional Conservation”, “New Conservation”, “Market ecocentrism” or “Critical social science”.
Figure 1. Students’ opinions on three issues in conservation—people-centredness, the role of science, and the role of capitalism—can be broadly used to identify whether they prefer “Traditional Conservation”, “New Conservation”, “Market ecocentrism” or “Critical social science”. Adapted from The Future of Conservation (n.d.).

 

At the beginning of this semester (Semester 1, AY2023/24), I will use my students’ opinions on three issues to identify their preferred approach to conservation (Sandbrook et al., 2019; Figure 1). As far as possible, students will be distributed into groups of four students—each with a different preference—and these groups will go through the same learning activities (e.g. class discussions) and assessments (e.g. preparing and presenting a case study) as the cohort from the previous year which was randomly sorted into groups. I will compare these two cohorts based on: (i) their academic performance as assessed by me using rubrics designed to evaluate their improvement in the course’s learning outcomes, and (ii) student self-reported learning using pre- and post-surveys and reflection assignments. These results are intended to inform educators designing collaborative learning activities on whether intentionally introducing diversity to groups can enhance student learning.

 

REFERENCES

Aronson, E. (n.d.). History of the Jigsaw. Retrieved from https://www.jigsaw.org/history/.

Ashman, A. F., & Gillies, R. M. (2013). Collaborative learning for diverse learners. In C. E. Hmelo-Silver, C. A. Chinn, C. K. K. Chan, & A. M. O’Donnell (Eds), The international handbook of collaborative learning (pp. 297-313). Routledge. https://doi.org/10.4324/9780203837290.ch17

Barkley, E. F., Cross, K. P., & Major, C. H. (2014). Collaborative learning techniques: A handbook for college faculty. John Wiley & Sons.

Bitzer, E. M. (1999). Pitfalls and bridges: Co-operative and collaborative learning in higher education. South African Journal of Higher Education, 13(1), 11-17. https://hdl.handle.net/10520/AJA10113487_892

Curşeu, P. L., Chappin, M. M., & Jansen, R. J. (2018). Gender diversity and motivation in collaborative learning groups: the mediating role of group discussion quality. Social Psychology of Education, 21(2), 289-302. https://doi.org/10.1007/s11218-017-9419-5

Kareiva, P., & Marvier, M. (2012). What is conservation science? BioScience, 62(11), 962-69. https://doi.org/10.1525/bio.2012.62.11.5

Laal, M., & Ghodsi, S. M. (2012). Benefits of collaborative learning. Procedia-Social and Behavioral Sciences, 31, 486-90. https://doi.org/10.1016/j.sbspro.2011.12.091

Loes, C. N., Culver, K. C., & Trolian, T. L. (2018). How collaborative learning enhances students’ openness to diversity. The Journal of Higher Education, 89(6), 935-60. https://doi.org/10.1080/00221546.2018.1442638

Marvier, M. (2014). New conservation is true conservation. Conservation Biology, 28(1), 1-3. https://doi.org/10.1111/cobi.12206

Panitz, T. (1999). Benefits of cooperative learning in relation to student motivation. In Theall, M. (Ed.) Motivation from within: Approaches for encouraging faculty and students to excel, New directions for teaching and learning. Josey-Bass Publishing.

Sandbrook, C., Fisher, J. A., Holmes, G., Luque-Lora, R., & Keane, A. (2019). The global conservation movement is diverse but not divided. Nature Sustainability, 2(4), 316-23. https://doi.org/10.1038/s41893-019-0267-5

Soulé, M. E. (1985). What is conservation biology? BioScience, 35(11), 727-34. https://doi.org/10.2307/1310054

Soulé, M. E. (2013). The “new conservation”. Conservation Biology, 27(5), 895-97. https://doi.org/10.1111/cobi.12147

The Future of Conservation (n. d.). About the debate. Retrieved from https://futureconservation.org/about-the-debate.

 

Teaching Service – NUS Communities and Engagement Pillar: Reflections on a Journey in Progress

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ZHENG Liren1, ONG Mui Hong2, Alex E. Y. LEE1, Esther GOH Chor Leng1, KANG Chul Hee3, SIM Qin Ying4, Anne CHONG Suet Lin5, Kenneth CHONG6, KOH Hui Li7, Pamela YEH8, Raiza RIFAAIE9, and CHENG Yuan Wen1

1*Department of Social Work, Faculty of Arts and Social Sciences (FASS)
2NUS Provost’s Office
3Yonsei University
4Communities and Engagement Pillar, NUS Provost’s Office
5Course Lead, GEN2061
6Course Lead, GEN2060
7Course Lead, GEN2062
8Course Lead, GEN2070
9Course Lead, GEN2050

*z.liren@nus.edu.sg

 

We acknowledge the support, guidance, and oversight from Professor Peter Ho,
Vice-Provost (Undergraduate Education & Technology-Enhanced Learning), NUS

 

Zheng, L., Ong, M. H., Lee, A. E. Y., Goh, E. C. L., Kang, C. H., Sim, Q. Y., Chong, A. S. L., Chong, K., Koh, H. L., Yeh, P., Rifaaie, R., & Cheng, Y. W. (2023). Teaching service – NUS Communities and Engagement pillar: Reflections on a journey in progress [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. Zheng, L., Ong, M. H., Lee, A. E. Y., Goh, E. C. L., Kang, C. H., Sim, Q. Y., Chong, A. S. L., Chong, K., Koh, H. L., Yeh, P., Rifaaie, R., & Cheng, Y. W. (2023). Teaching service – NUS Communities and Engagement pillar: Reflections on a journey in progress [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/teaching-service-nus-communities-and-engagement-pillar-reflections-on-a-journey-in-progress/

SUB-THEME

Communities and Education 

 

KEYWORDS

Service-learning, general education, communities, volunteering, social services

 

CATEGORY

Paper Presentation 

 

ABSTRACT

In 2021, the National University of Singapore (NUS) embarked on a journey to re-think General Education (GE) for all undergraduates and prepare them for a fast-changing world. One of the new initiatives was to include a Communities and Engagement (C&E) Pillar. C&E aims to deepen a sense of social responsibility and social action among students through service learning.

 

To achieve these outcomes, NUS utilises service-learning as a form of teaching and learning in C&E. Service-learning has been found to be associated with positive outcomes in development of empathy, civic consciousness, social skills, and academic achievement. Well-designed service-learning increases the likelihood that students will engage with the communities they encounter, engage in dialogue and problem-solving, and become part of the solution to a variety of social issues.

 

Research suggests that university leadership is key to a successful service-learning programme, and this support contributes to better outcomes for both the students and the community. To that end, NUS has invested considerable leadership, manpower, and financial resources into a structured service-learning programme that ensures positive learning outcomes for students while also meeting real community needs identified by relevant agency partners.

 

NUS C&E Type A courses offer a structured programme with equal focus on both classroom learning and service work. The classroom learning is anchored by the Faculty of Arts and Social Sciences’ (FASS) Department of Social Work (SW), while the service work component is helmed by the NUS Provost’s Office (PVO). These courses require students to undergo e-learning lectures and tutorials in preparation for service-learning prior to being deployed to their respective agencies for service-work. When nearing the completion of service-work, students return for a final tutorial to consolidate their learning and reflections, in addition to academic assignments. Operational matters such as liaison with social service agencies, placement of students, managing issues and challenges on the ground are led by staff from PVO.

 

This model differs from volunteering through students’ own initiatives. It requires strong leadership from the university, tight collaboration between SW and PVO, with SW contributing its professional knowledge of community engagement and PVO its operational expertise.

 

This paper presents the development and initial evaluation results of the two pilot trials (Pilot 1a, N = 208, Pilot 1b, N = 561) of the C&E Pillar Type A service-work courses.

 

The stages of development of the C&E pillar will be discussed, including preparation for pilots 1a and 1b. The presentation will outline the strategies that NUS has taken to create and manage the service partnerships with ministries, agencies, and their community partners to create five courses spanning the three key sectors of support for disadvantaged school children, families in rental neighbourhoods, and senior citizens. Efforts to develop engaging lessons for students to prepare them with the necessary knowledge and skills for service-learning will also be discussed.

 

Student surveys were conducted before, during, and after their service-work was completed to understand their experiences of service-learning. These surveys focused on evaluating students’ motivations for volunteering as well as their satisfaction levels for their service-learning experience. In addition, students were also invited to focus group discussions for further in-depth discussion on their learning and experience. In addition, a survey with agency supervisors is being conducted to understand their experience of the various aspects of working with NUS. Supervisors will also be invited to a focus group discussion for the research team to collect further data to evaluate our collaborations.

 

While data collection is still ongoing, preliminary findings revealed students’ gains in their exposure to real world issues through service learning and especially the opportunities to observe the challenges faced by service beneficiaries, allowed students to be grounded in their thinking about social issues and how they could contribute to alleviating them.

 

Going forward, NUS will be deploying a large volunteer force into the social service sector in unprecedented numbers. This requires tight coordination to synergise processes between NUS and the various external stakeholders. Supporting the large number of students deployed and managing their expectations while out in the field would also require considerable effort from faculty and teaching staff from NUS. These challenges require constant deliberation and calibration to achieve the desired outcomes for NUS students and for Singapore.

 

REFERENCES

Communities and Engagement Pillar. (n.d.). Retrieved June 12, 2023, from https://www.nus.edu.sg/registrar/academic-information-policies/undergraduate-students/general-education/communities-and-engagement-pillar

Celio, C. I., Durlak, J., & Dymnicki, A. (2011). A Meta-analysis of the Impact of Service-Learning on Students. Journal of Experiential Education, 34(2), 164–81. https://doi.org/10.5193/JEE34.2.164

Gordon, C. S., Pink, M. A., Rosing, H., & Mizzi, S. (2022). A systematic meta-analysis and meta-synthesis of the impact of service-learning programs on university students’ empathy. Educational Research Review, 37, 100490. https://doi.org/10.1016/j.edurev.2022.100490

Holmes, K., Paull, M., Haski-Leventhal, D., MacCallum, J., Omari, M., Walker, G., Scott, R., Young, S., & Maher, A. (2021). A continuum of University student volunteer programme models. Journal of Higher Education Policy and Management, 43(3), 281–97. https://doi.org/10.1080/1360080X.2020.1804658

Jacoby, B. (2015). Service-learning essentials: Questions, answers, and lessons learned (1st ed.). Jossey-Bass.

Service learning and greater flexibility for incoming undergraduates at NUS. (n.d.). Service Learning and Greater Flexibility for Incoming Undergraduates at NUS. Retrieved June 12, 2023, from https://news.nus.edu.sg/service-learning-and-greater-flexibility-for-incoming-undergraduates-at-nus/

 

The Role of Mentoring, Supervision, Coaching, Teaching and Instruction on Professional Identity Formation: A Systematic Scoping Review

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Jun Kiat LUA1,2*, Rachelle Qi En TOH1,2, Kai Kee KOH1,2, Ruth Si Man WONG1,2, Elaine Li Ying QUAH1,2, Aiswarya PANDA1,2, Chong Yao HO1,2, Nicole‐Ann LIM1,2, Yun Ting ONG1,2, Keith Zi Yuan CHUA1,2, Victoria Wen Wei NG1,2, Sabine Lauren Chyi Hui WONG1,2, Luke Yu Xuan YEO1,2, Sin Yee SEE1,2, Jolene Jing Yin TEO1,2, Yaazhini RENGANATHAN1,2, Annelissa Mien Chew CHIN3 and Lalit Kumar Radha KRISHNA1,2,4,5,6,7,8

1Yong Loo Lin School of Medicine (YLLSOM), National University Singapore (NUS)
2Division of Palliative and Supportive Care, National Cancer Centre Singapore
3Medical Library, NUS Libraries
4Division of Cancer Education, National Cancer Centre Singapore
5Duke‐NUS Medical School
6Palliative Care Institute Liverpool, Academic Palliative & End of Life Care Centre, University of Liverpool
7Centre for Biomedical Ethics, NUS
8PalC, The Palliative Care Centre for Excellence in Research and Education, PalC c/o Dover Park Hospice


*e0638946@u.nus.edu

 

Lua, J. K., Toh, R. Q. E., Koh, K. K., Wong, R. S. M., Quah, E. L. Y., Panda, A., Ho, C. Y., Lim, N.-A., Ong, Y. T., Chua, K. Z. Y., Ng, V. W. W., Wong, S-L. C. H., Yeo, L. Y. X., See, S. Y., Teo, J. J. Y., Renganathan, Y., Chin, A. M. C., & Krishna, L. (2023). The role of mentoring, supervision, coaching, teaching and instruction on professional identity formation: A systematic scoping review [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/the-role-of-mentoring-supervision-coaching-teaching-and-instruction-on-professional-identity-formation-a-systematic-scoping-review/

SUB-THEME

Communities and Education 

 

KEYWORDS

Communities of practice, mentoring, supervision, coaching, professional identity formation

 

CATEGORY

Paper Presentation 

 

BACKGROUND

The crucial role of mentoring in fostering professional identity formation (PIF) is greatly influenced by its integration with supervision, coaching, tutoring, instruction, and teaching. Yet, the impact of this comprehensive approach, the ‘mentoring umbrella’ (MU), lacks clear understanding. This is especially so in the healthcare setting which has constant interplay between various healthcare professionals, families, and patients. This systemic scoping review (SSR) thus provides an overview of the present state of knowledge and proffers new insights into better application of MU for educational purposes.

 

INTRODUCTION

Mentoring is vital for facilitating the development of PIF in medical students and physicians in training (henceforth mentees), helping them “think, act and feel like physicians” (Merton, 2013). The personalised, long-term, and comprehensive support provided by mentors assists the assimilation of professional values, beliefs, standards, codes of conduct, and culture of the medical profession into their own identities (Cruess & Cruess, 2018). However, understanding of the specific roles of mentoring in PIF has been limited due to the presence of various mentoring forms (Krishna et al., 2020; Krishna et al., 2019; Radha Krishna et al., 2019) and its association with other practices such as role modelling, supervision, coaching, tutoring, teaching, and instruction (Wahab et al., 2016). Two recent developments offer potential solutions to this challenge and can provide fresh perspectives into the impact of mentoring on PIF.

 

First, recent evidence suggests that when applied longitudinally, practices such as role modelling, supervision, coaching, tutoring, teaching, and instruction create the effects currently attributed to mentoring (Buddeberg-Fischer & Herta, 2006). Krishna et al. (2019) suggests that role modelling, supervision, coaching, tutoring, teaching, and instruction are part of a broader concept that can be referred to as the MU.

 

Second, on their own or in tandem within MU, these educational approaches shape professional identity by changing the mentee’s values, beliefs and principles (henceforth belief systems). Krishna’s Ring Theory of Personhood (RToP) suggest that the four domains of the belief system are contained within the Innate, Individual, Relational, and Societal Rings of the RToP (Figure 1) (Chan et al., 2021; Ho et al., 2020; Vig et al., 2021). Exposure, reflection, and inculcation of new experiences and beliefs systems over the course of a training programme changes parts of mentees’ belief systems within the four rings of the RToP. These changes inform self-concepts of personhood or “what makes you, you” (Krishna & Alsuwaigh, 2015), which in turn reshapes personal and professional identities. It is this link that allows the RToP to be utilised to sketch changes in PIF. Critically, the RToP also captures the impact of changing roles, and obligations, within the team, family unit, professional community, and society, and offers a deeper understanding of their thought patterns, actions, and capacity to adapt to diverse influences (Alsuwaigh, 2015; Arai et al., 2017; Ho et al., 2020; Khandelwal et al., 2015; Kim & Choi, 2015; Krishna, Alsuwaigh, et al., 2014; Krishna, Yong, et al., 2014; Kuek et al., 2020).

The Ring Theory of Personhood

 

METHODOLOGY

Systematic Evidence‐based Approach (SEBA) (Figure 2) guided SSR seeks to map current understanding of the MU and its effects on PIF on mentees (Bok et al., 2020; Kow et al., 2020; Krishna et al.; Ngiam et al.). The primary research question was identified:

“What is known about the effect of mentoring, supervision, coaching, tutoring, teaching, and instruction on professional identity formation amongst medical students, residents, and junior doctors?”

 

It is hoped that insights provided will guide structuring, support, and oversight of the MU in nurturing PIF. Articles published between 1st Jan 2000 and 31st Dec 2021 in PubMed, Scopus, ERIC and the Cochrane databases were scrutinised. The included articles were concurrently summarised and tabulated, and concurrently analysed using content and thematic analysis and tabulated. The themes and categories identified were compared with the summaries of the included articles to create accountable and reproducible domains that guide the discussion.

Systematic Evidence‐based Approach (SEBA)

 

RESULTS

A total of 12201 abstracts were reviewed, 657 full text articles evaluated, and 207 articles included (Figure 3).

The three domains identified were definitions; impact on PIF; and enablers and barriers.

 

The MU shapes PIF in three stages. To begin it builds a cognitive base of essential knowledge, skills, and professional attitudes. The cognitive base informs thinking, conduct, and opinions in early supervised clinical exposure in Communities of Practice (COP). The COPs’ individualised approach to the inculcation of desired professional characteristics, goals, values, principles, and beliefs reshapes the individual’s identity, whilst the socialisation process sees to their integration into current identities.

PRISMA flowchart

 

DISCUSSION

In this SSR, we highlight the impact of the MU on PIF, shedding light on its effects on different stages of PIF development and the role of the host organisation. When implemented over time in personalised learning relationships, involving individual or small groups of learners with shared goals, abilities, and experiences, the MU offers customised, prompt, and comprehensive support to the developing professional.

 

The overlapping elements within the MU provide synergistic support in tackling the influences of societal, professional, clinical, academic, research, and personal factors, as well as the prevailing sociocultural considerations and the impact of the healthcare and educational systems, including the local hidden, informal, and formal curriculum, on PIF. This highlights the wide applicability and stage-based nature of the MU in fostering PIF.

 

CONCLUSION

This SSR underscores the crucial role of MU in the development of PIF. Additionally, it emphasises the importance of conducting long-term and comprehensive evaluations to assess the impact of MU on PIF, as PIF significantly influences the personal growth and education of mentees during their interactions with diverse healthcare communities.

 

REFERENCES

Alsuwaigh, R. (2015). How do English-speaking cancer patients conceptualise personhood? Ann Acad Med Singapore, 44. https://doi.org/10.47102/annals-acadmedsg.V44N6p207

Arai, K., Saiki, T., & Imafuku, R. (2017). What do Japanese residents learn from treating dying patients? The implications for training in end-of-life care. BMC Med Educ, 17. https://doi.org/10.1186/s12909-017-1029-6

Bok, C., Ng, C. H., & Koh, J. W. H. (2020). Interprofessional communication (IPC) for medical students: a scoping review. BMC Med Educ, 20. https://doi.org/10.1186/s12909-020- 02296-x

Buddeberg-Fischer, B., & Herta, K. D. (2006). Formal mentoring programmes for medical students and doctors–a review of the Medline literature. Med Teach, 28. https://doi.org/10.1080/01421590500313043

Chan, N., Chia, J., & Ho, C. (2021). Extending the ring theory of personhood to the care of dying patients in intensive care units. Asian Bioethics Rev, 14. https://doi.org/10.1007/s41649-021-00192-0

Cruess, S. R., & Cruess, R. L. (2018). The development of professional identity. Vol. 17. In T. Swanwick, K. Forrest, & B. C. O’Brien (Eds.), Understanding Medical Education: Evidence, Theory, and Practice, Third Edition.

Ho, C. Y., Kow, C. S., & Chia, C. H. J. (2020). The impact of death and dying on the personhood of medical students: a systematic scoping review. BMC Med Educ, 20. https://doi.org/10.1186/s12909-020-02411-y

Khandelwal, A., Nugus, P., & Elkoushy, M. A. (2015). How we made professionalism relevant to twenty-first century residents. Med Teach, 37. https://doi.org/10.3109/0142159X.2014.990878

Kim, S., & Choi, S. (2015). The medical professionalism of Korean physicians: Present and future.

BMC Med Ethics, 26. https://doi.org/10.1186/s12910-015-0051-7

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Public Reason and Civic Education: A Rawlsian Framework

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Jimmy LIM
Lee Kuan Yew School of Public Policy (LKYSPP)

*jimmylim@nus.edu.sg

 

Lim, J. (2023). Public reason and civic education: A Rawlsian framework [Paper presentation]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/public-reason-and-civic-education-a-rawlsian-framework/

SUB-THEME

Communities and Education 

 

KEYWORDS

Public reason, civic education, moral reasoning, Rawls, active citizenship

 

CATEGORY

Paper Presentation 

 

ABSTRACT

John Rawls’s concept of public justification is part of a broader concept that goes under the label “public reason.” The secondary literature suggests that his account of public reason is vulnerable to two objections. The first objection turns on the assumption that Rawlsian public justification is something that involves the participation of many citizens. On this assumption, Rawls’s account of public reason is unrealistic because it ignores the fact that many citizens in a real society may lack the resources (e.g. time, money, knowledge) to participate in the public justification of law. The second objection turns on the assumption that the “duty of civility” (the duty to offer public reasons in the justification of law) is something that falls on both government officials and ordinary citizens. On this assumption, Rawls’s account of public reason is unrealistic because it ignores the consideration that officials and citizens alike may not observe the duty of civility. In my paper, I resist the first objection by arguing that Rawlsian public justification involves the empathetic power to place oneself in the shoes of those to whom one disagrees with, in the course of evaluating the normativity of law. Taking my cue from Stephen Darwall (2006), I call this power the power to take up the second-person standpoint in moral reasoning. For Rawls, what makes justification as a mode of reasoning “public” is not a situation where every member of society gathers in some outdoor space to debate with one another (which would make justification an actual, historical, event), but the presence of an implied addressee (which makes justification a normative, second-personal, concept). In Rawlsian thought, citizens may pursue public justification collectively (inter-personally), in a raucous townhall, or intra-personally, without ever participating in face-to-face debates. I also resist the second objection by arguing that, in the context of a real society, the duty of civility falls more heavily on the shoulders of civic leaders than on ordinary citizens. Inspired by Martin Luther King, Jr., Rawls himself sees civic leaders as playing an important role in honoring the duty of civility and mobilizing ordinary citizens to take up the second-person standpoint in public justification. My paper sheds light on the place of second-personal reasoning and second-personal reactive attitudes such as guilt and empathy in Rawlsian thought. It provides resources for civic educators to reflect upon the importance of cultivating citizens’ capacity for second-personal reasoning, not just in the public sphere but also in more localized settings such as the classroom. It tries to answer the question of how to bring the idea of public justification (as second-personal justification) and its related reactive attitudes into the classroom—and to do so in a morally justifiable way—to help students learn and appreciate the political values of toleration, respect, diversity, and trust.

 

I would like to present my work as a paper presentation, under the sub-theme of “Communities and Education.”

 

REFERENCES

Darwall, S. (2006). The Second-Person Standpoint: Morality, Respect, and Accountability. Harvard University Press.

Rawls, J. (2005). Political Liberalism, expanded edition. Columbia University Press.

 

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