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

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

 

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