Lighting Talks

Does AI-generated Writing Differ from Human Writing in Style? A Literature Survey

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Feng CAO
Centre for English Language and Communication (CELC)

elccf@nus.edu.sg

 

Cao, F. (2023). Does AI-generated writing differ from human writing in style? A literature survey [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/does-ai-generated-writing-differ-from-human-writing-in-style-a-literature-survey/

 

SUB-THEME

AI and Education

 

KEYWORDS

AI-generated writing, human writing, ChatGPT, style, linguistic features

 

CATEGORY

Lightning Talks

 

ABSTRACT

Artificial intelligence (AI) has witnessed significant advancements recently, leading to the emergence of AI-generated writing. This new form of writing has sparked interest and debate, raising questions about how it differs from traditional human writing. One popular AI tool which has been attracting much attention since 2022 is ChatGPT, which has been used to create texts in many domains. In this preliminary survey of literature, I aim to review studies which compare the writing generated by ChatGPT with human writing to explore the rhetorical and linguistic differences in style.

 

This literature survey focuses on the most widely used databases: Google Scholar, Scopus, and Web of Science. An initial search in these databases using key terms such as “AI-generated writing”, “human writing”, and “ChatGPT” returned over 400 items relevant to the topic. I skimmed through the titles and abstracts, and sometimes the full texts to assess their relevance to the research question. Irrelevant items and duplicates were excluded, and only the most pertinent sources were further analysed.

 

The preliminary analysis showed that the AI-generated writing differed from human writing in a number of genres and disciplines, for example, medical abstracts and case reports, business correspondence, restaurant reviews, and academic essays. Regarding content creation, for example, the literature review shows that AI is capable of generating highly readable medical abstracts and case reports which are almost indistinguishable from human writing. However, a few key limitations, such as inaccuracies in content and fictitious citations, were also reported by expert reviewers.

 

In terms of tone and voice, the analysis reveals that human writing differs from AI-generated writing by evoking emotions and resonates with readers on a personal level. Human writers bring their life experiences, cultural background, and empathy into their work, enabling them to convey complex emotions, capture nuances, and engage readers’ emotions. AI-generated writing, however, typically lacks the emotional depth and intuition present in human writing.

 

In terms of linguistic features, the literature indicates that AI-generated writing tends to employ longer sentences than human writing, but the latter is likely to employ more diverse vocabulary and expressions. In addition, AI-generated writing contains a more formal register whereas human writing is more likely to use informal register such as the frequent use of personal pronouns.

 

In short, this survey of the literature provides an initial overview of some key differences between AI-generated writing and human writing. While AI models like ChatGPT have made remarkable advances in mimicking human writing, they still lack the distinct characteristics that make human writing unique and emotionally resonant. Understanding these differences is vital for harnessing the potential of AI-generated writing while mitigating potential risks and challenges. In the field of language education, a better understanding of the differences between AI- and human writing may help teachers and novice writers to better utilise AI tools for developing academic writing skills and publishing. At the same time, by addressing ethical concerns and nurturing human creativity alongside AI capabilities, teachers and learners can navigate the evolving landscape of AI-generated writing, and leverage it to enhance human expression and communication in a responsible and inclusive manner.

 

Fostering Interdisciplinarity in PF2203: Quality and Productivity Management

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Alexander LIN*, Anqi SHI, and TAY En Rong Stephen
Department of the Built Environment, College of Design and Engineering (CDE)

*bdgal@nus.edu.sg

 

Lin, A., Shi, A., & Tay, E. R. S. (2023). Fostering interdisciplinarity in PF2203: Quality and productivity management [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/fostering-interdisciplinarity-in-pf2203-quality-and-productivity-management/

 

SUB-THEME

Interdisciplinarity and Education

 

KEYWORDS

Quality and productivity management, industry relevance, knowledge integration, constructivism learning

 

CATEGORY

Lightning Talks

 

INTRODUCTION

This discussion elucidates a pedagogical transformation of the course PF2203 “Quality and Productivity Management (QPM)”, which amalgamates an interdisciplinary management philosophy. Interdisciplinary learning integrates knowledge from multiple domains while considering their interrelationships (Ivanitskaya et al., 2002). This enables an interprofessional education with a deeper understanding of thinking processes practiced by different professionals (Cooper et al. 2001) and hence, is essential for coordinating and integrating the operations of different teams within the construction industry.

 

The approach to enhancing the interdisciplinary elements within the PF2203 curriculum revolved around a shift from a traditional, teacher-centred pedagogy to a more inclusive, student-centred approach. This paradigm shift was motivated by the need to ensure that students are not merely passive recipients of knowledge but active constructors of their learning experience (Anthony, 1996). It is through this shift that we sought to foster an interdisciplinary constructivism learning experience.

 

METHODOLOGY

This transformative journey involved enriching the traditional lecture format through the incorporation of (i) current industry insights, (ii) research findings, and (iii) multidisciplinary concepts, of which examples are presented in Table 1. This is to enable students to link theoretical principles to real-world applications for authentic learning, thereby enhancing their understanding and critical thinking abilities (Lombardi & Oblinger, 2007).

 

Table 1
Content added for lectures

Topic for the Lecture Content Added Purpose
Nature of the construction industry Robotic fabrication in construction and automobile industries. To understand how different disciplines in construction and manufacturing industries affect the consideration of applying robotic fabrication.
The debate on quality A case introduction about design, construction, and operation of a university building. To provide a practical example from the industry where the effectiveness of collaborations between different professionals, such as engineers, architects, and managers, affects the project outcomes.
Construction Productivity, Quality and Technologies A case introduction about design and fabrication of a 3D-printed concrete arch structure. To utilise a real case to elaborate how considerations and knowledge in fields of architecture, structure, construction/fabrication, and quality management are integrated in a design-to-fabrication process.
Just-in-time productivity A case introduction about a real-time quality monitoring system of fresh concrete during delivery. To utilise a real case to elaborate how technology can help one achieve just-in-time productivity.

 

In parallel, the tutorials were utilised as explorative platforms where students could delve into the intricate interplay between the sub-domains of engineering, management, policy, and human aspects to synthesise them into a cohesive understanding of QPM, thus enforcing interdisciplinary learning. This also allows the passive acceptance of knowledge from lectures to be transferred to active learning (Anthony, 1996), with knowledge construction based on constructivism learning theory (Piaget, 1954). During the tutorial sessions, students presented their findings and the lecturer provided guidance and feedback focusing on the interrelationship of different disciplines.

 

The framework illustrated in Figure 1 was deployed herein and fosters a constructivist learning process for interdisciplinary learning, which builds upon previous works on constructivism for interdisciplinary teaching and learning (Ledoux & McHenry, 2004; Scheer et al., 2012). Merging knowledge from both technical and non-technical subdomains, it builds upon students’ prior knowledge acquired from earlier lectures and courses, integrating it into tutorial activities. Within this approach, students explore the nuances of subdomain knowledge through an iterative balance between two main pillars: active learning and social interaction (Ledoux & McHenry, 2004). The former involves students actively constructing knowledge for their presentation, while the latter centres on obtaining feedback from peers and the lecturer. This cyclical engagement between the two processes across interdisciplinary sub-domains deepens comprehension and encourages a collaborative learning environment (Scheer et al., 2012).

framework employed to foster a constructivist learning process for interdisciplinary learning in the QPM course
Figure 1. The framework employed to foster a constructivist learning process for interdisciplinary learning in the QPM course.

 

RESULTS

The transformation of the pedagogical approach was met with positive student feedback in an end-of-course survey. Table 2 shows some representative student feedback, indicating that the revamped course allowed students to learn how QPM theory was applied to the construction industry [refer to feedback (a) and (b)], and the peer learning in tutorials allowed students to have a deeper understanding on comprehensive sub-domains relevant to QPM [refer to feedback (c) and (d)].

 

Table 2
Qualitative student feedback reproduced as they are

Feedback
(a) Further discusses applications and real world applications of the topics taught in the module. Content from slides and readings are closely related.
(b) Took a closer look into real-life examples of QPM and how it is implemented within a company
(c) The group projects are definitely useful as the various presentations done by the different groups covers a lot of different areas in QPM. This wide coverage of content is good in allowing us to learn as much from everyone.
(d) Understanding the different factors relating to quality and productivity, Listening and learning from other groups.

 

Table 3 shows the responses for the end-of-course survey utilising a five-point Likert scale. Survey responses for Questions (1) to (3) indicate a general agreement that the innovative learning activities contributed to a deeper understanding of the interdisciplinary relationships among the course’s subtopics and the integration of them. Most students appreciated the value derived from seeing the practical application of theoretical concepts (Question 4) and the lecturer’s approachability (Question 6). Additionally, students acknowledged that these activities fostered their ability to critically analyse and apply QPM concepts in the construction industry [Questions (5) and (6)]. Examples and images of students’ work will be shown in the presentation during the conference.

 

Table 3
Survey results indicating the average response based on a five-point Likert scale with 1 (Strongly Disagree) and 5 (Strongly Agree) (n = 27)

Questions Average Score 
(1) Quality and Productivity Management consists of many sub-topics. Through the learning activities for tutorials and group projects, I gained an understanding of the relationship between these sub-topics. 3.8
(2) Quality and Productivity Management consists of many sub-topics. Through the activities for tutorials and group projects, I learnt how to integrate these sub-topics. 3.6
(3) Quality and Productivity Management consists of many sub-topics. Through the activities for tutorials and group projects, I appreciate how these sub-topics connections to my prior knowledge/experiences about the built environment industry. 4.2
(4) Through the activities for tutorials and group projects, I learnt how quality and productivity management concepts/principles have been implemented in the construction industry and other industries/sectors. 4.1
(5) The activities for tutorials and group projects facilitate my critical thinking for deployment of Quality and Productivity Management. 4.0
(6) In the activities for tutorials and group projects, the guidance (if any) presented by the tutor(s) were instructive and inspired me and my group members to think critically and delivery our own ideas. 4.0

 

CONCLUSION AND SIGNIFICANCE

In conclusion, this study highlights how interdisciplinarity could be achieved through a course revamp incorporating i) current industry insights, ii) research findings, and iii) multidisciplinary concepts. Through this transformation, we have observed students actively participating in their learning journey while at the same time applying interdisciplinary knowledge from other domains of knowledge. This model potentially serves as a blueprint for other courses looking to foster an interdisciplinary and industry-relevant learning environment.

 

REFERENCES

Anthony, G. (1996). Active learning in a constructivist framework. Educational Studies in Mathematics, 31(4), 349-69. https://doi.org/10.1007/BF00369153

Cooper, H, Carlisle, C., Gibbs, T., & Watkins, C. (2001). Developing an evidence base for interdisciplinary learning: a systematic review, Journal of Advanced Nursing, 35(2), 228-37. https://doi.org/10.1046/j.1365-2648.2001.01840.x

Ivanitskaya, L., Clark, D, Montgomery, G., & Primeau, R. (2002). Interdisciplinary learning: Process and outcomes. Innovative Higher Education, 27(2), 95-111. https://doi.org/10.1023/A:1021105309984

Ledoux, M. & McHenry, N. (2004). A constructivist approach in the interdisciplinary instruction of science and language arts methods. Teaching Education, 15(4), 385-99. https://doi.org/10.1080/1047621042000304510

Lombardi, M. M., & Oblinger, D. G. (2007). Authentic learning for the 21st century: An overview. Educause Learning Initiative, 1(2007), 1-12. https://library.educause.edu/resources/2007/1/authentic-learning-for-the-21st-century-an-overview

Piaget, J. (1954). The construction of reality in the child. (M. Cook, Trans.). Basic Books.

Scheer, A., Noweski, C., & Meinel, C. (2012). Transforming constructivist learning into action: Design thinking in education. Design and Technology Education, 17(3), 8-19. https://openjournals.ljmu.ac.uk/DATE/article/view/1679

 

Collecting, Documenting and Researching About the Effects of Litter on Biodiversity with Team Mates

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Amy CHOONG Mei Fun
Department of Biological Sciences, Faculty of Science (FOS)

dbscmfa@nus.edu.sg

 

Choong, A. M. F. (2023). Collecting, documenting and researching about the effects of litter on biodiversity with team mates [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/collecting-documenting-and-researching-about-the-effects-of-litter-on-biodiversity-with-team-mates/

 

SUB-THEME

Interdisciplinarity and Education

 

KEYWORDS

Waste and our environment, group project, Natural Heritage of Singapore, biodiversity, protecting the environment

 

CATEGORY

Lightning Talks

 

ABSTRACT

GES1021/GESS1016 “Natural Heritage of Singapore” is a course that showcases biodiversity in Singapore and how development threatens local biodiversity. Undergraduates can take the course from any level. Owing to a lack of manpower, the LSM1307 “Waste and Our Environment” had to be put on hold and since I took over GES1021/GESS1016, I decided to incorporate LSM1307’s key topics, such as litter and pollution, into GES1021/GESS1016. The course LSM1307 focusses on environmental sustainability, particularly on waste and health concerns while GES1021/GESS1016 focusses on biodiversity, specifically on the natural heritage of Singapore. Students who enrolled into this course came from all faculties thus rendering this continual assessment (CA), titled as in this abstract, highly interdisciplinary.

 

This CA was a group project. In the CA instruction given, students were taught how to collect the trash, what to avoid, how to practice safety, how to document the waste and categorise it. The instruction also named the students as heroes to motivate them to do good as their litter removal helps local biodiversity. They were graded on aesthetics of the poster (2%), accuracy of information about the organisms (12%), detailed research on waste (5%), good referencing (1%), as well as the pictures and categories of waste collected (3%).

 

Out of the class of 125, the students formed their own groups of 3 to 5 members. Each group focussed on one natural habitat (may be at different locations in Singapore), documented three native plants and three native animals that lived there, and picked at least 50 pieces of litter from the habitat and documented them in their group poster. Based on what they had picked, students researched on the category of litter, their effects on the flora and fauna in general (need not be specific to their organism, as few such studies had been carried out locally). For instance, there were different types of plastics, and information on how they affected plants or animals could be obtained from studies done (need not be limited to Singapore). Finally, students submitted their work in the form of a three-page A3 poster in PDF. The first page described the team’s chosen habitat and organisms. The second page listed the types of litter collected and how these affected plants and animals, and the final page listed the references.

 

This CA was a form of experiential learning (Kolb, 1984). Students were taught in the course what a habitat is and what are considered native organisms. These background information form the intellectual origin (Kolb, 1984). As they carried out this assignment, students must be able to apply the concepts and correctly identify as well as photograph three native animals and plants. From the litter picking component, students could see for themselves how their six organisms were living amongst litter. From their desktop research, they would discover the harmful effects and might feel for their organisms’ plight. The research involved many disciplines, from biology and ecology of organisms, pollution chemistry affecting organisms’ growth and physiology (D’Costa, 2022; van Bijsterveldt et al., 2021; Zdunek & Kolenda, 2022), heavy metals (Buhari & Ismail, 2016), soil structure or aquatic quality, ultimately affecting human health (although students are to omit this in their poster). These experiences thus influence their overall learning.

 

When the students first started GES1021/GESS1016, most were clueless about local biodiversity and Singapore’s natural habitats. Subsequently as they attended lectures, worked on this assignment, encountered interesting plants and animals and recognised that these organisms were at risk from litter, students gained cognitive growth and their understanding changed. Their ideas about the environment and biodiversity were formed and reformed with each experience (Kolb, 1984).

 

The assignment was effective in bringing across the seriousness of litter’s harm to wildlife. The hard work required to pick up litter, the encounters with wildlife would be memorable. Students enjoyed the experience as they mentioned this in the module feedback (see comments in the next two paragraphs) and from conversations I had with them. During the “get to know you” online poll conducted on Mentimeter, my current student (2023-24) said they selected this course because of the litter-picking assignment.

 

Comments from two students:

  • “Very fun module with a very passionate Dr Choong! She instils values in us such as the importance of not wasting food, or not littering. Our project is very unique where we get to explore our natural habitat in Singapore and pick rubbish that pollutes these habitats.”
  • “It allows me to understand nature more and inspires me to make some changes in the future to protect our natural environment.”

 

REFERENCES

Buhari, T. R., & Ismail, A. (2016). Correlations between geo-chemical speciation of heavy metals (Cu, Zn, Pb, Cd and Ni) in surface sediments and their concentrations in giant mudskipper (Periophthalmodon schlosseri) collected from the west coast of Peninsular Malaysia. Journal of Geoscience and Environment Protection, 4(1), 28-36. https://doi.org/10.4236/gep.2016.41003

D’Costa, A. H. (2022). Microplastics in decapod crustaceans: Accumulation, toxicity and impacts, a review. Science of The Total Environment, 832, 154963. https://doi.org/10.1016/j.scitotenv.2022.154963

Kolb, D. A. (1984). Experiential learning: experience as the source of learning and development. Prentice-Hall.

van Bijsterveldt, C. E. J., van Wesenbeeck, B. K., Ramadhani, S., Raven, O. V., van Gool, F. E., Pribadi, R., & Bouma, T. J. (2021). Does plastic waste kill mangroves? A field experiment to assess the impact of macro plastics on mangrove growth, stress response and survival. Science of The Total Environment, 756, 143826. https://doi.org/10.1016/j.scitotenv.2020.143826

Zdunek, P. & Kolenda, K. (2022). The threat of discarded food and drinks containers to monitor lizards. Herpetological Bulletin, 161, 28-30. https://doi.org/10.33256/hb161.2830

 

 

Harnessing the Power of ChatGPT for Assessment Question Generation: Five Tips for Medical Educators

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Inthrani Raja INDRAN*, Priya PARANTHAMAN, and Nurulhuda MUSTAFA

Department of Pharmacology,
Yong Loo Lin School of Medicine (YLLSoM)

*phciri@nus.edu.sg

 

Indran, I. R., Paranthaman, P., & Mustafa, N. (2023). Harnessing the power of ChatGPT for assessment question generation: Five tips for medical educators [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/harnessing-the-power-of-chatgpt-for-assessment-question-generation-five-tips-for-medical-educators/ 

SUB-THEME

AI and Education 

 

KEYWORDS

AI, ChatGPT, questions, medical assessment

 

CATEGORY

Lightning Talks 

 

INTRODUCTION

Developing diverse and high-quality assessment questions for the medical curriculum is a complex and time-intensive task, as they often require the incorporation of clinically relevant scenarios which are aligned to the learning outcomes (Al-Rukban, 2006; Palmer & Devitt, 2007). The emergence of artificial intelligence (AI)-driven large language models (LLMs) has presented an unprecedented opportunity to explore how AI can be harnessed to optimise and automate these complex tasks for educators (AI, 2023). It also provides an opportunity for students to use the LLMs to help create practice questions and further their understanding of the concepts they wish to test.

 

AIMS & METHODS

This study aims to establish a definitive and dependable series of practical pointers, that would enable educators to tap on the ability of LLMs, like ChatGPT, to firstly enhance question generation in healthcare profession education, using multiple choice question (MCQs) as an illustrative example. Secondly, it can assist to generate diverse clinical scenarios for teaching and learning purposes and lastly, we hope that our experiences will encourage more educators to explore and access AI tools such as ChatGPT with greater ease, especially if they had limited prior experiences.

 

To generate diverse, high-quality clinical scenario MCQs, we outlined core medical concepts and identified essential keywords for integrating into the instruction stem. The text inputs were iteratively refined and fine-tuned until we developed instruction prompts that could help us generate questions of a desirable quality. Following question generation, respective domain experts reviewed them for content accuracy and overall relevance, identifying any potential flags in the question stem. This process of soliciting feedback and implementing refinements, enabled us to continuously enhance the prompts and the quality of questions generated. By prioritising expert review, we established a necessary validation process for the MCQs prior to their formal implementation.

 

THE FIVE TIPS

We consolidated the following tips to effectively harness the power of ChatGPT for assessment question generation.

 

Tip 1: Define the Objective and Select the Appropriate Model

Determine the purpose of question generation and choose the appropriate AI model based on needs and access. Model selection depends on the needs and accessibility. Choose ChatGPT 4.0 over 3.5 for greater accuracy and concept integration. ChatGPT 4.0 requires a subscription. Activate the beta features in “Settings” and utilise the “Browse with Bing” mode to retrieve information surpassing its training cut-off period, as well as install plugins for improved AI performance.

 

Tip 2: Optimise Prompt Design

When refining the stem design for question generation, there are several important considerations. Firstly, be specific in your instructions by emphasising key concepts, question types, quantity, and the answer format. Clearly state any guidelines or rules you want the model to follow. Focus on core concepts and keywords relevant to the discipline to build the instruction stem. Experiment with vocabulary to optimise question quality.

 

Tip 3: Build Diverse Authentic Scenarios

Develop a range of relevant clinical vignettes to broaden the scope of scenarios that can be used to assess students.

 

Tip 4: Calibrate Assessment Difficulty

Incorporate the principles of Bloom’s Taxonomy when developing assessment questions to test different cognitive skills, ranging from basic knowledge recall to complex analysis, enhancing question diversity.

 

Tip 5: Work Around Limitations

Be mindful that ChatGPT is trained on limited data and can generate factually inaccurate information. Despite diverse training, ChatGPT does not possess the nuanced understanding of a medical expert, which can impact the quality of the questions it generates. Human validation is necessary to address any factual inaccuracies that may arise. AI data collection risks misuse, privacy breaches, and bias amplification, leading to misguided outcomes.

 

CONCLUSION

AI-assisted question generation is an iterative process, and these tips can provide any healthcare professions educator valuable guidance in automating the generation of good quality assessment questions. Furthermore, students can leverage this technology for self-directed learning, creating and verifying their practice questions and strengthening their understanding of medical concepts (Touissi et al., 2022). While this paper primarily demonstrates the use of ChatGPT in generating MCQs, we believe that the approach can be extended to various other question types. It is also important to remember that though AI augments, it does not replace human expertise. (Ali et al., 2023; Rahsepar et al., 2023). Domain experts are needed to ensure quality, accuracy, and relevance.

 

REFERENCES 

AI, O. (2023).

Al-Rukban, M. O. (2006). Guidelines for the construction of multiple choice questions tests. J Family Community Med, 13(3), 125-33. https://www.ncbi.nlm.nih.gov/pubmed/23012132

Ali, R., Tang, O. Y., Connolly, I. D., Fridley, J. S., Shin, J. H., Zadnik Sullivan, P. L., Cielo, D., Oyelese, A. A., Doberstein, C. E., Telfeian, A. E., Gokaslan, Z. L., & Asaad, W. F. (2023). Performance of ChatGPT, GPT-4, and Google Bard on a Neurosurgery Oral Boards Preparation Question Bank. Neurosurgery. https://doi.org/10.1227/neu.0000000000002551

Palmer, E. J., & Devitt, P. G. (2007). Assessment of higher order cognitive skills in undergraduate education: modified essay or multiple choice questions? Research paper. BMC Med Educ, 7, 49. https://doi.org/10.1186/1472-6920-7-49

Rahsepar, A. A., Tavakoli, N., Kim, G. H. J., Hassani, C., Abtin, F., & Bedayat, A. (2023). How AI responds to common lung cancer questions: ChatGPT vs Google Bard. Radiology, 307(5), e230922. https://doi.org/10.1148/radiol.230922

Touissi, Y., Hjiej, G., Hajjioui, A., Ibrahimi, A., & Fourtassi, M. (2022). Does developing multiple-choice questions improve medical students’ learning? A systematic review. Med Educ Online, 27(1), 2005505. https://doi.org/10.1080/10872981.2021.2005505

 

Fostering AI Literacy: Human-agency-oriented Approach to AI Usage in Higher Education

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Jodie LUU and Jungyoung KIM
Centre for English Language Communication (CELC)
jodieluu@nus.edu.sg

 

Luu, T. H. L., & Kim, J. Y. (2023). Fostering AI literacy: Human-agency-oriented approach to AI usage in higher education [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/fostering-ai-literacy-human-agency-oriented-approach-to-ai-usage-in-higher-education/

 

SUB-THEME

AI and Education

 

KEYWORDS

ChatGPT, AI literacy, critical thinking, human agency, human-AI interaction

 

CATEGORY

Lightning Talks

 

ABSTRACT

From providing learning analytics essential to personalized personalised education to conducting automated assessments and grading, technology powered by artificial intelligence (AI) has been gradually transforming the education sector. However, it is the pivotal open access to ChatGPT, a powerful AI chatbot built with OpenAI’s large language models (LLMs) such as GPT-4 and its predecessors (Marr, 2023), that has given rise to the question of how to harness the potential of AI while maintaining the integrity and ethos of education.

 

In response to ChatGPT and its equivalents’ capability of producing comprehensive content based on well-crafted prompts, higher education institutions worldwide have started to devise policies for AI-generated content. In NUS, a timely interim policy for the use of AI in teaching and learning was first circulated in February 2023. The policy’s focus on mandating self-declaration seems to suggest that the moral compass of an AI user plays a key role. Considering the fast-paced advancement and integration of AI in various sectors, it could be argued that learners need both a moral compass and AI literacy to navigate and harness the potential of AI tools.

 

The emerging literature on AI in education has highlighted the need to develop AI literacy across all age groups and professions (Taguma et al., 2021; Ng et al., 2022; Cardon et al., 2023; Long et al.; 2023; Su & Yang, 2023). As proposed by Kong et al. (2021), “AI literacy includes three components: AI concepts, using AI concepts for evaluation, and using AI concepts for understanding the real world through problem solving” (p. 2). In the context of human-AI interaction, AI is said to manifest machine agency, which could be understood as the algorithms’ ability to process a large amount of data, learn from the analysis, adapt, and evolve to support decision-making and problem solving (Kaplan & Haenlein, 2019; Kang & Lou, 2022). Informed by Williams et al.’s (2021) conception of agency that acknowledges the consideration of context, consequences, or implications of human actions (in addition to rationality and autonomy), human agency, on the other hand, could be seen as the ability to make intentional, reasoned, contextualised and ethical decisions when it comes to AI-powered activities, be it for school, work, or leisure.

 

Following these discussions, our Lightning Talk will discuss how we can reframe AI usage in higher education while fostering AI literacy based on the notion of human agency within the context of human-AI interaction. In doing so, we will draw on results from an anonymous poll on the use of ChatGPT conducted in Semester 2 AY2022/23 (with students enrolled in the course ES2660 “Communicating in the Information Age”) and two case studies of how the teaching team handled written works flagged positive by GPTZero, an AI detection tool. Ultimately, we would like to suggest that a proper cultivation of AI literacy and awareness of the role of human agency in the technology-driven world among students are imperative. At the practical level, AI literacy development needs to move beyond mandating self-declaration to include engaging with learners through dialogues and integrating AI tools such as ChatGPT in learning activities where human- AI interaction could be experienced and human agency negotiated.

 

REFERENCES

Cardon, P. W., Fleischmann, C., Aritz, J., Logemann, M., & Heidewald, J. (2023). The challenges and opportunities of AI-assisted writing: Developing AI literacy for the AI age. Business and Professional Communication Quarterly, 232949062311765. https://doi.org/10.1177/23294906231176517

Kang, H., & Lou, C. (2022). AI agency vs. human agency: understanding human–AI interactions on TikTok and their implications for user engagement. Journal of Computer-Mediated Communication, 27(5). https://doi.org/10.1093/jcmc/zmac014

Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004

Kong, S. C., Cheung, W. W. L., & Zhang, G. (2021). Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds. Computers & Education: Artificial Intelligence, 2, 100026. https://doi.org/10.1016/j.caeai.2021.100026

Long, D., Roberts, J., Magerko, B., Holstein, K., DiPaola, D., & Martin, F. (2023). AI Literacy: Finding Common Threads between Education, Design, Policy, and Explainability. https://doi.org/10.1145/3544549.3573808

Marr, B. (2023, May 19). A short history of ChatGPT: How we got to where we are today. Forbes. https://www.forbes.com/sites/bernardmarr/2023/05/19/a-short-history-of-chatgpt- how-we-got-to-where-we-are-today/?sh=5f1e3e13674f

Ng, D. T. K., Lee, M. G., Tan, R. J. Y., Hu, X., Downie, J. S., & Chu, S. K. W. (2022). A review of AI teaching and learning from 2000 to 2020. Education and Information Technologies. https://doi.org/10.1007/s10639-022-11491-w

Taguma, M., Feron, E., & Lim, M. H. (2021, July 5). Education and AI: Preparing for the future & AI, attitudes and values. In Future of Education and Skills 2030: Conceptual Learning Framework. Organisation for Economic Co-operation and Development. https://www.oecd.org/education/2030/E2030%20Position%20Paper%20(05.04.2018).pdf

Su, J., & Yang, W. (2023). Artificial Intelligence (AI) literacy in early childhood education: an intervention study in Hong Kong. Interactive Learning Environments, 1–15. https://doi.org/10.1080/10494820.2023.2217864

Williams, R. A., Gantt, E. E., & Fischer, L. (2021). Agency: What does it mean to be a human being? Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.693077

 

Conditions for Interdisciplinary Learning–Some Preliminary Reflections on Designing and Facilitating “Global Experience Tokyo: City, Culture and Technology”

cdtlsd Lighting Talks , , , ,

LEE Chee Keng
NUS College

ckenglee@nus.edu.sg

 

Lee, C. K. (2023). Conditions for interdisciplinary learning–Some preliminary reflections on designing and facilitating “Global Experience Tokyo: City, Culture and Technology” [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/conditions-for-interdisciplinary-learning-some-preliminary-reflections-on-designing-and-facilitating-global-experience-tokyo-city-culture-and-technology/

 

SUB-THEME

Interdisciplinarity and Education

 

KEYWORDS

Interdisciplinary, learning, experiential learning, independent study

 

CATEGORY

Lightning Talks

 

ABSTRACT

This Lighting Talk explores the sub-theme of Interdisciplinarity and Education by reflecting on the design and facilitation experience of Global Experience Tokyo (GEx Tokyo) 2023, guided by the questions:1) What are the conditions necessary for effective interdisciplinary learning? 2) What are the possible preparations that could bring about these conditions?

 

Global Experience (GEx) is a specially curated course in which students spend a month living in and studying an international city. Each GEx is guided by a theme. The theme for GEx Tokyo is “City, Culture and Technology.” The objective of the course is to allow students to examine and reflect on the dynamic and transformative relationship between city, culture, and technology through a set of interweaving and interdisciplinary encounters and site visits. In GEx Tokyo 2023, students attended seminars with guest professors, workshops with practitioners, masterclasses with experts, and field visits to start-ups, research centres, and government offices. Prior to arriving in Tokyo, students attended preparatory seminars that familiarise them with some of the anticipated topics and social situations in GEx Tokyo. Students were also required to propose an independent study research project related to the theme of GEx Tokyo prior to arriving in Tokyo.

 

Based on discussions with students during independent research project consultations, it became apparent that despite the explicitly stated course objective and the purposeful layering of the programme itineraries, students were not drawing upon the interdisciplinary itineraries to deepen and enrich their independent study projects. Preliminary student feedback suggests that students formulated their Independent Study proposals with disciplinary-based frames and experienced the diverse GEx Tokyo itineraries largely through the lens of their Independent Study project. Tellingly, they found all the experts they met on the trip knowledgeable but indicated that few helped them achieve their learning objectives.

 

This experience prompted the questions I would like to contemplate in this Lighting Talk:

  1. What are the conditions necessary for effective interdisciplinary learning in general and for GEx Tokyo in particular?
  2. What are the possible preparations that could bring about these conditions?

 

Discussions on interdisciplinarity and education often focus on how specific disciplines can connect to and benefit from interdisciplinary links, as well as how interdisciplinary links can be built across different disciplines in a course. Such discussions extend into how to operationalise interdisciplinary learning objectives by describing and assessing interdisciplinary learning.

 

This Lighting Talk attempts to reflect on GEx Tokyo 2023 student feedback through the integrated lens of literature examining the entanglement of personal epistemologies and emotions in students’ thinking, and those discussing learning environments, to contemplate the conditions that could motivate and facilitate effective interdisciplinary learning.

 

A Journey Through A Quantitative Reasoning Course with Quirkiness and Laughter

cdtlsd Lighting Talks , , ,

Da Yang TAN
NUS College

dytan@nus.edu.sg

 

Tan, D. Y. (2023). A journey through a quantitative reasoning course with quirkiness and laughter [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/a-journey-through-a-quantitative-reasoning-course-with-quirkiness-and-laughter/

SUB-THEME

Others 

 

KEYWORDS

Humour, motivation, quantitative reasoning

 

CATEGORY

Lightning Talks 

 

ABSTRACT

As the timeless saying goes, “laughter is the best medicine”. In my latest run of GEA1000N “Quantitative Reasoning with Data” (Ng et al. 2022), I explored the use of humour within my classes as a mediator to engage students from diverse academic backgrounds. As it is known, humour, when used appropriately, creates an engaging and enjoyable learning environment that captures students’ attention and encourages active participation. It helps to alleviate the often-dreaded monotony of lectures, making the content more relatable and memorable (Neumann et al., 2009). Moreover, humour can serve as an effective communication bridge between instructors and students, breaking down barriers and building rapport, thereby fostering a positive and light-hearted classroom atmosphere conducive to learning (Lomax & Moosavi, 2002). Furthermore, discovering humour within the subject requires a profound understanding of the subject matter, and this stimulates students’ higher order thinking towards the subject at hand (Garner, 2006; Ziv, 1988; Daumiller et al., 2020). In this Lightning Talk, I will elaborate on my strategies and approaches to incorporate humour within a technical and quantitative classroom. In the following, I propose three possible levels in which the humour could be implemented:

 

LEVEL 1000: SLAPSTICK COMEDY TO ATTRACT STUDENTS’ ATTENTION

Figure 1 illustrates an example of attracting students’ attention through the wordplay of established bubble tea chains (another subject that students will be interested in) to encourage the students to look and think about the questions posed to them. The humour at this Level 1000 lowest tier serves as a psychological break from the monotony of the lesson, especially when I attempt to pronounce the names of the chain and when students break into laughter (or at least a sheepish smile). However, it is important to capture the opportunity to broach about a serious subject or the content matter once the attention has been captured.

Lightning Talk Tan Da Yang Fig 1
Figure 1. An example on how wordplay is used to capture students’ attention. (The story, all names, characters, and incidents portrayed in this production are fictitious. No identification with actual persons (living or deceased), places, buildings, and products are intended or should be inferred.)

 

Figure 2 shows a whimsical made-up scenario to get students to start thinking about the validity of using average in a Likert scale. Like the first example, the idea is to capture students’ attention by introducing something that is considered fun for them.

 

Lightning Talk Tan Da Yang Fig 2
Figure 2. A whimsical hypothetical scenario on bubble tea production for students to think about the correct use of the Likert scale (or to brainstorm new bubble tea flavours).

 

LEVEL 2000: CONTEXTUALISED HUMOUR TO GET STUDENTS THINKING

Within the course, one of the hardest concepts to grasp in probability is the concept of mutual exclusivity, which refers to the fact that events do not occur at the same time; and independence, in which the occurrence of one event does not affect the chance of occurrence of the other event. To demonstrate the differences, I showed a slide that says:

Mutual exclusivity: Both of you have zero chance of being together.
Independence: The chance of being together has nothing to do with whether you like the person.

 

The main objective is to contextualise potentially conceptually confusing pain points into ideas that students may appreciate, and then infuse some form of humour to get them to think why the formal definitions could be applied in their personal context, in this case, relationships.

 

LEVEL 3000: HUMOUR FOR MEMORY RETENTION

To demonstrate what null hypothesis is about, I wore red shirts for six of my lessons, and in the eighth lesson where the concept of hypothesis testing is covered, I asked the class the question as shown in Figure 3. While not all the students selected the correct answer on the first attempt, the act itself was achieved both Level 1000 and Level 2000, and there was ample attention given to myself when I explained the solution. Furthermore, in the last lesson of the course, an informal survey was administered, and students were able to recall and mention the incident, therefore demonstrating some degree of retention.

Lightning Talk Tan Da Yang Fig 3
Figure 3. Building up of a playful narrative over multiple weeks with the aim that students will remember the important concept of null hypothesis in hypothesis testing. (The red shirt was washed every week well before the lesson.)

 

CONCLUDING REMARKS

Although the use of humour is not new and have been incorporated to varying degrees by instructors, having a framework and discourse that highlights its value as a useful pedagogical strategy would assist in purposefully reflecting on our teaching practices (Bieg & Dresel, 2018). This Lightning Talk aims to precisely provide that by encouraging intentional and deliberate consideration of how humour can be effectively employed in the classroom.

 

REFERENCES

Bieg, S., & Dresel, M. (2018). Relevance of perceived teacher humor types for instruction and student learning. Social Psychology of Education, 21, 805-25. https://doi.org/10.1007/s11218-018-9428-z

Daumiller, M., Bieg, S., Dickhäuser, O., & Dresel, M. (2020). Humor in university teaching: role of teachers’ achievement goals and self-efficacy for their use of content-related humor. Studies in Higher Education, 45(12), 2619-33. https://doi.org/10.1080/03075079.2019.1623772

Garner, R. L. (2006). Humor in pedagogy: How ha-ha can lead to aha! College Teaching, 54(1), 177-80. https://doi.org/10.3200/CTCH.54.1.177-180

Lomax, R. G., & Moosavi, S. A. (2002). Using humor to teach statistics: Must they be orthogonal? Understanding Statistics: Statistical Issues in Psychology, Education, and the Social Sciences, 1(2), 113-30. https://doi.org/10.1207/S15328031US0102_04

Neumann, D. L., Hood, M., & Neumann, M. M. (2009). Statistics? You must be joking: The application and evaluation of humor when teaching statistics. Journal of Statistics Education, 17(2). https://doi.org/10.1080/10691898.2009.11889525

Ng, K. L., Hartman, K., Gan, M. J., Lu, M., & Tan, S. W. (2022). Data literacy for all: Designing GEA1000 “Quantitative Reasoning with Data” with an eye towards inclusivity [Paper presentation]. Higher Education Campus Conference (HECC) 2022, 7-8 December. National University of Singapore. Retrieved from https://nus.edu.sg/cdtl/engagement/conferences/higher-education-campus-conference-2022/hecc-2022-home/ebooklet.pdf

Ziv, A. (1988). Teaching and learning with humor: Experiment and replication. The Journal of Experimental Education, 57(1), 4-15. https://doi.org/10.1080/00220973.1988.10806492

 

Peer Partnership in Interdisciplinary Settings: A Learning Community’s Experience

cdtlsd Lighting Talks , , ,

Linda SELLOU1*, Mark CHONG2, Sarada BULCHAND3, Mei Hui LIU4, Hui Ting CHNG5, Stephen TAY En Rong6, Matthew TAN Chiang Wang5, ZHANG Ye7, Nicholas CAI Xianhui8, Francis CHONG Yuan Yi9, Janelle Claire TEOH Gi Yan10

1Special Programme in Science
2Department of Biomedical Engineering
3Duke-NUS Medical School
4Department of Food Science & Technology
5Department of Pharmacy
6Department of the Built Environment
7Department of Architecture
8Department of Philosophy
9Department of Chemistry
10Faculty of Arts and Social Science

*chmsll@nus.edu.sg

 

Sellou, L., Chong, M., Bulchand, S., Liu, M. H., Chng, H. T., Tay, S. E. R., Tan, M. C. W., Zhang, Y., Cai, N. X., Chong, F. Y. Y., Teoh, J. C. G. Y. (2023). Peer partnership in interdisciplinary settings: A learning community’s experience [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/peer-partnership-in-interdisciplinary-settings-a-learning-communitys-experience/ 
 

SUB-THEME

Communities and Education 

 

KEYWORDS

Learning communities, interdisciplinary education, best practices

 

CATEGORY

Lightning Talks

 

BACKGROUND

In this lightning talk, we will share our experiences and lessons learnt from our Learning Community (LC) which started in April 2022. Our LC sought to explore “Peer partnership in interdisciplinary settings” and started off with asking two key questions:

 

1. How can students from different disciplines and backgrounds learn from one another effectively?

There is a demand for interdisciplinary education and/or training in interdisciplinary settings. Particularly in higher learning settings, however, existing monodisciplinary structures often limit the effectiveness of interdisciplinary efforts. It follows that the “undifferentiated” students themselves—as active partners in learning, in both self-directed and peer settings—may be key to providing effective interdisciplinary education. The frameworks to do so, however, are not well-established.

 

2. How can students provide effective feedback to one another?

Peer learning is commonly employed in academic settings, with documented benefits of greater ownership over learning and deeper learning (Boud et al., 1999). More recently, the ability to provide feedback to peers has emerged as an important tool in the modern workplace (Di Fiore & Souza, 2021). Despite these various merits, effective deployment of peer learning and feedback remains challenging.

In light of the above, this LC aims to better understand the perceptions of both students and faculty in this shared learning process, focusing on three key areas:

  • Challenges in peer learning, appraisal, and review in the interdisciplinary space (SETTINGS)
  • Specialised tools in blended learning spaces (PLATFORMS)
  • Faculty as supporters / mediators (PEOPLE)

 

LC STRUCTURE

Our LC has been engaging diverse stakeholders from students to faculty across disciplines. Specifically, the community started with nine (and have now grown to 11) members comprising students and faculty from eight (now ten) different departments in Design and Engineering, Science, and Medicine. This was a reflection of our deliberate efforts to increase breadth and representation, in order to better approach interdisciplinary learning. In our meetings, we explored best practices to implement peer appraisal, review and reflection, by consolidating challenges in design and implementation, brainstorming solutions, and identifying areas for adoption and utility. A unique aspect of the LC is the formation of two sub-working groups, focusing on the following “mini-projects”:

 

  • Knowledge, Skills, and Attitudes in Interdisciplinary Teams
    Through review of literature and reflections from faculty, the sub-group seeks to explore:
    (1) What knowledge, skills, and attitudes (K/S/A) are required to work effectively in an interdisciplinary team? (2) Do the K/S/A differ depending on the types of disciplines that work together?
  • Peer Feedback: Student-generated Questions and Peer-to-peer Critique
    Through sharing of personal practices and conduct of comparative studies, the sub-group explores the strengths and areas for improvement of peer teaching tools being used in our classes. This can lead subsequently to the abstraction of key factors and considerations in the design of tools in peer instruction.

 

Currently, both groups have completed preliminary literature reviews and have sought ethics board approval for the “mini-studies”, sharing their reports and updates at the bi-monthly meetings.

 

CENTRAL MESSAGE/WHY YOU SHOULD ATTEND THIS PRESENTATION

This presentation provides a summary and anecdotal sharing of our experiences in the LC: besides factors contributing to favourable outcomes, we will also discuss pitfalls encountered that other LCs can avoid. Specific to our LC, this may serve as a platform to attract like-minded members, who may be able to benefit from and contribute towards the diversity and dynamism of the LC.

 

REFERENCES

Boud, D., Cohen, R., & Sampson, J. (1999). Peer learning and assessment. Assessment & Evaluation in Higher Education, 24(4), 413-26. https://doi.org/10.1080/0260293990240405

Di Fiore, A., & Souza, M. (2021, January 12). Are peer reviews the future of performance evaluations? Harvard Business Review Online. https://hbr.org/2021/01/are-peer-reviews-the-future-of-performance-evaluations

 

 

ChatGPT and Teacher Education/Development

cdtlsd Lighting Talks , , , ,

Aileen LAM Wanli
Centre for English Language Communication (CELC)
aileenlam@nus.edu.sg

 

Lam, A. W. (2023). ChatGPT and teacher education/development [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/chatgpt-and-teacher-education-development/

 

SUB-THEME

AI and Education 

 

KEYWORDS

AI generative software, ChatGPT, teacher education, teacher development

 

CATEGORY

Lightning Talks 

 

ABSTRACT

ChatGPT by OpenAI and other variations of generative artificial intelligence (AI) software such as Bard by Google, Bing AI chat by Microsoft, Ernie by Baidu, Tong Yi Qian Wen by Alibaba have been viewed with optimism and suspicion. Its capabilities in understanding user requests, access to a comprehensive data bank and ability to generate natural and appropriate responses using human-like language is significant (Lund & Wang, 2023). This ability to perform complex tasks have led to educators arguing over its benefits and disadvantages such as the ability to provide ‘personalised and interactive learning’ and ‘ongoing feedback’ as opposed to its limitations in the accuracy of answers provided, promotion of biases, and privacy issues (Baidoo-Anu & Owusu Ansah, 2023). There is also a common worry that AI generative software would lead to more instances of cheating and plagiarism (King & ChatGPT, 2023) and by extension, affect students’ learning when they take shortcuts. Yet, from all angles, this technology is here to stay. Universities such as the University of Hong Kong and those in Japan have reacted by banning or restricting students’ use of ChatGPT (Universities in Japan, 2023; Yau & Chan, 2023) while others such as Yale University and Princeton have issued AI guidelines for students and faculty in response to its rising popularity (Gorelick & Mcdonald, 2023; Hartman-Sigall, 2023). The industry and even the civil service have also taken an interest in this technology, with a team from Open Government Product (OGP) integrating ChatGPT into Microsoft Word for public officers in Singapore to use for research and writing (Chia, 2023). With constant advancements and improvements, the possibilities are endless for education and the industry alike. Though some tech companies like Apple, Samsung and Amazon as well as financial institutions like JPMorgan Chase, Citigroup, Goldman Sachs have put a ban on the use of AI generative software citing data concerns, cyber security risks, accountability, and legal consequences (Ray, 2023; Uche, 2023; Nelson, 2023; Cawley, 2023), others like Lazada and Bain & Company have embraced the technology and looked into ways to integrate AI generative software into their systems (Yordan, 2023; Bain & Company, 2023) in a more secure manner with the end goal of efficiency. Certain sectors have also begun to explore the role of AI generative software such as ChatGPT in areas such as in global warming (Biswas, 2023a), public health (Biswas, 2023b), and healthcare research (Sallam, 2023). With the advantages that the industry already recognises, this lightning talk focuses on AI generative software in education but shifts the focus from students to the tutors and explores the possibilities of AI generative software in teacher education (Trust et al., 2023; Rahman & Watanobe, 2023) as well as for teacher development, especially for new tutors who may need help in the formative stages of their teaching careers or those going into new domains. Beyond exploring ChatGPT’s support for pedagogical knowledge such as teaching skills and classroom management, student assessment/evaluation, and personalised learning support, this talk will look into the possible support for tutor-student communication, creative thinking/multimodal approaches as well as subject-specific tutor development. 

 

REFERENCES

Baidoo-Anu, D., & Owusu Ansah, L. (2023b). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Available at SSRN 4337484. https://dx.doi.org/10.2139/ssrn.4337484

Bain & Company. (2023, 21 February). Bain & Company announces services alliance with OpenAI to help enterprise clients identify and realize the full potential and maximum value of AI [Press release]. https://www.bain.com/about/media-center/press-releases/2023/bain–company-announces-services-alliance-with-openai-to-help-enterprise-clients-identify-and-realize-the-full-potential-and-maximum-value-of-ai/

Biswas, S. S. (2023a). Potential use of chat GPT in global warming. Annals of Biomedical Engineering, 51(6), 1126-27. https://doi.org/10.1007/s10439-023-03171-8

Biswas, S. S. (2023b). Role of chat GPT in public health. Annals of Biomedical Engineering, 51(5), 868-69. https://doi.org/10.1007/s10439-023-03172-7

Cawley, C. (2023, 13 June). From Apple to Samsung, these companies (and a few countries) are prohibiting the use of generative AI platforms like ChatGPT. Tech.co. https://tech.co/news/tech-companies-banning-generative-ai

Chia, O. (2023, 14 February). Civil servants to soon use ChatGPT to help with research, speech writing. The Straits Times. https://www.straitstimes.com/tech/civil-servants-to-soon-use-chatgpt-to-help-with-research-speech-writing

Gorelick, E. & Mcdonald, A. (2023, 12 February). University leaders issue AI guidance in response to growing popularity of ChatGPT. Yale Daily News. https://yaledailynews.com/blog/2023/02/12/university-leaders-issue-ai-guidance-in-response-to-growing-popularity-of-chatgpt/

Hartman-Sigall, J. (2023, 25 January). University declines to ban ChatGPT, releases faculty guidance for its usage. The Daily Princetonian. https://www.dailyprincetonian.com/article/2023/01/university-declines-ban-chatgpt-releases-faculty-guidance-for-usage

King, M. R., & ChatGPT (2023). A conversation on artificial intelligence, chatbots, and plagiarism in higher education. Cellular and Molecular Bioengineering, 16(1), 1-2. https://doi.org/10.1007/s12195-022-00754-8

Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: how may AI and GPT impact academia and libraries? Library Hi Tech News, 40(3), 26-29. https://dx.doi.org/10.2139/ssrn.4333415

Nelson, F. (2023, 16 June). Many Companies Are Banning ChatGPT. This Is why. Science Alert. https://www.sciencealert.com/many-companies-are-banning-chatgpt-this-is-why

Rahman, M. M., & Watanobe, Y. (2023). ChatGPT for education and research: Opportunities, threats, and strategies. Applied Sciences, 13(9), 5783. https://doi.org/10.3390/app13095783

Ray, S. (2023, 19 March). Apple Joins a Growing List of Companies Cracking Down on use of ChatGPT by Staffers—Here’s Why. Forbes. https://www.forbes.com/sites/siladityaray/2023/05/19/apple-joins-a-growing-list-of-companies-cracking-down-on-use-of-chatgpt-by-staffers-heres-why/?sh=2169888f28ff

Sallam, M. (2023). ChatGPT utility in healthcare education, research, and practice: systematic review on the promising perspectives and valid concerns. Healthcare, 11(6), 887. https://doi.org/10.3390/healthcare11060887

Trust, T., Whalen, J., & Mouza, C. (2023). Editorial: ChatGPT: Challenges, opportunities, and implications for teacher education. Contemporary Issues in Technology and Teacher Education, 23(1), 1-23. https://citejournal.org/volume-23/issue-1-23/editorial/editorial-chatgpt-challenges-opportunities-and-implications-for-teacher-education

Uche, A. (2023, 26 June). 5 Reasons Why Companies Are Banning ChatGPT. Make Use Of. https://www.makeuseof.com/reasons-why-companies-banning-chatgpt/

Universities in Japan restrict students’ use of ChatGPT. (2023, 10 Apr). The Straits Times. https://www.straitstimes.com/asia/east-asia/universities-in-japan-restrict-students-use-of-chatgpt

Yau, C., & Chan, K. (2023, 17 February). University of Hong Kong temporarily bans students from using ChatGPT, other AI-based tools for coursework. South China Morning Post. https://www.scmp.com/news/hong-kong/education/article/3210650/university-hong-kong-temporarily-bans-students-using-chatgpt-other-ai-based-tools-coursework

Yordan, J. (2023, 25 May). Lazada launches ChatGPT-powered chatbot. TechInAsia. https://www.techinasia.com/lazada-launches-ecommerce-ai-chatbot-powered-chatgpt

 

Developing a Card Game to Promote Interest and Awareness of Microbiomes Among Diverse Undergraduate Students

NUS CDTL Lighting Talks , , , , ,

CH’NG Jun-Hong1*, CHAN Chuu Ling1, GOH Lih Ing1, CHONG Hao Kai Nathanael1,
LEE Russell2, and LEE Li Neng2
1Department of Microbiology & Immunology, Yong Loo Lin School of Medicine
2Department of Psychology, Faculty of Arts and Social Sciences
*micchn@nus.edu.sg

 

Ch’ng, J. H., Chan, C. L., Goh, L. I., Chong, N. H. K., Lee, R., Lee, L. N. (2023). Developing a card game to promote interest and awareness of microbiomes among diverse undergraduate students [Lightning talk]. In Higher Education Campus Conference (HECC) 2023, 7 December, National University of Singapore. https://blog.nus.edu.sg/hecc2023proceedings/developing-a-card-game-to-promote-interest-and-awareness-of-microbionmes-among-diverse-undergraduate-students/

 

SUB-THEME

Interdisciplinarity and Education

 

KEYWORDS

Microbiology, microbiome, card game, interdisciplinary, general education

 

CATEGORY

Lightning Talks

 

ABSTRACT

Microbes are linked to infections, sickness, and death. Yet, this view is hardly complete: microbes are everywhere, part of everyday life and prerequisites for our own good health and that of our planet’s. Microbes are also recognised as crucial and versatile tools to address the UN Sustainability Development Goals; a microbial Swiss Army knife that ought to be at everyone’s disposal as we tackle some of the world’s most complex problems from pandemics to climate change, food sustainability to environmental pollution.

 

To appreciate the impact of microbes and maximise their utility, learners need make connections with other disciplines, interests, and experiences in everyday life. This needs to happen at both the research and education fronts, with the latter involving the promotion of microbiology beyond the schools of medicine and sciences, to better engage students from all disciplines. This presents many challenges as students may neither have the interest nor confidence to even begin the journey. Consequently, tools that inspire curiosity while empowering self-directed learning are critical to engage learners coming from disparate disciplines.

 

We are in the process of developing a card game that looks commercially produced, is easy to pick up and fun to play, while not requiring any domain knowledge to enjoy and get good at. In this pilot study, 40 undergraduate students, primarily from medicine, life sciences and psychology, were asked to read through the game instructions before giving feedback on the instructions. They then played two rounds of the game, without supervision, before providing feedback on their experience. Feedback, both quantitative and qualitative, was collected using Qualtrics and observations by session facilitators were also recorded. Quantitative feedback was analysed using descriptive statistics while qualitative data was coded for semi-quantitative analysis or to look for specific constructive suggestions to improve game play/design.

 

The game was well-received across disciplinary backgrounds with positive feedback (5-point scale) on game mechanics being fun (4.17±0.63), attractive artwork (3.83±1.00) and scientific snippets (3.79±1.04), positive re-playability (3.46±0.84), player engagement for non-microbiologists (3.63±1.04), and usefulness of knowledge taught (3.54±1.10). Areas for improvement evidenced from feedback included unclear instructions (2.74±0.98), limited content taught (2.76±0.93), not generating interest to attend formal microbiome classes (2.88±1.17) and not prompting lifestyle changes (1.98±1.11).

 

Data from this pilot study enabled us to further refine the microbiome card game (mechanics, instruction, artwork) and to identify the self-reported learning gains arising from unsupervised gameplay. The latter further led us to develop assessment tools for downstream work to quantify learning gains using pre- and post-play testing.

 

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