Skip to main content
SpringerLink
Log in

Continuance Intention of ChatGPT Use by Students

  • Conference paper
  • First Online:
Transfer, Diffusion and Adoption of Next-Generation Digital Technologies (TDIT 2023)

Part of the book series: IFIP Advances in Information and Communication Technology ((IFIPAICT,volume 697))

Included in the following conference series:

Abstract

ChatGPT, an AI language model, has gained significant attention for its potential to enhance educational experiences and foster interactive learning environments. The potential of student interaction via ChatGPT has engendered significant debate around educational technology. It is apparent that the current literature has yet to fully explore the role of ChatGPT in management education. Amidst the increasing integration of ChatGPT into educational contexts, the concept of continuance intention takes center stage. This research paper delves into the nuanced landscape of students’ continuance intention regarding the use of ChatGPT in educational settings. We ground our study in Technology Continuance Theory and Theory of Planned Behavior to examine students’ continuance intention to use ChatGPT. By investigating the determinants that shape this intention, we aim to provide insights that inform educators and educational technology designers in optimizing the integration of AI-driven tools like ChatGPT. This study contributes to the growing body of research at the intersection of AI and education, offering valuable implications for both theory and practice.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Liebrenz, M., Schleifer, R., Buadze, A., Bhugra, D., Smith, A.: Generating scholarly content with ChatGPT: ethical challenges for medical publishing. The Lancet Digital Health 5(3), e105–e106 (2023). https://doi.org/10.1016/S2589-7500(23)00019-5

    Article  Google Scholar 

  2. Dwivedi, Y.K., et al.: Opinion Paper: “So what if ChatGPT wrote it?” multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. Int. J. Inf. Manage. 71, 102642 (2023). https://doi.org/10.1016/j.ijinfomgt.2023.102642

    Article  Google Scholar 

  3. Baidoo-Anu, D., Owusu Ansah, L.: Education in the Era of Generative Artificial intelligence (AI): understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI 7(1), 52–62 (2023)

    Google Scholar 

  4. Jovanovic, M., Campbell, M.: Generative artificial intelligence: trends and prospects. Computer 55(10), 107–112 (2022). https://doi.org/10.1109/MC.2022.3192720

    Article  Google Scholar 

  5. Abukmeil, M., Ferrari, S., Genovese, A., Piuri, V., Scotti, F.: A survey of unsupervised generative models for exploratory data analysis and representation learning. ACM Comput. Surv. 54(5), 1–40 (2022). https://doi.org/10.1145/3450963

    Article  Google Scholar 

  6. Milmo, D.: ChatGPT reaches 100 million users two months after launch. The Guardian (2023). https://www.theguardian.com/technology/2023/feb/02/chatgpt-100-million-users-open-ai-fastest-growing-app

  7. Ratten, V., Jones, P.: Generative artificial intelligence (ChatGPT): implications for management educators. The International J. Manage. Educ. 21(3), 100857 (2023). https://doi.org/10.1016/j.ijme.2023.100857

    Article  Google Scholar 

  8. Statista: Share of company employees worldwide using ChatGPT in work environments from February to March 2023 (2023). https://www.statista.com/statistics/1378709/global-employees-chatgpt-se/

  9. Goralski, M.A., Tan, T.K.: Artificial intelligence and poverty alleviation: emerging innovations and their implications for management education and sustainable development. The Int. J. Manage. Educ. 20(3), 100662 (2022). https://doi.org/10.1016/j.ijme.2022.100662

    Article  Google Scholar 

  10. Dowling, M., Lucey, B.: ChatGPT for (Finance) research: the Bananarama Conjecture. Financ. Res. Lett. 53, 103662 (2023). https://doi.org/10.1016/j.frl.2023.103662

    Article  Google Scholar 

  11. Kung, T.H., et al.: Performance of ChatGPT on USMLE: potential for AI-assisted medical education using large language models. PLOS Digit Health 2(2), e0000198 (2023). https://doi.org/10.1371/journal.pdig.0000198

    Article  Google Scholar 

  12. Pavlou and Fygenson: Understanding and predicting electronic commerce adoption: an extension of the theory of planned behavior. MIS Q. 30(1), 115 (2006). https://doi.org/10.2307/25148720

    Article  Google Scholar 

  13. Firat, M.: How chat GPT can transform autodidactic experiences and open education?. Open Science Framework, preprint (2023). https://doi.org/10.31219/osf.io/9ge8m

  14. Keiper, M.C., Fried, G., Lupinek, J., Nordstrom, H.: Artificial intelligence in sport management education: playing the AI game with ChatGPT. J. Hosp. Leis. Sport Tour. Educ. 33, 100456 (2023). https://doi.org/10.1016/j.jhlste.2023.100456

    Article  Google Scholar 

  15. Fesenmaier, D.R., Wöber, K.: AI, ChatGPT and the university. Ann. Tour. Res. 101, 103578 (2023). https://doi.org/10.1016/j.annals.2023.103578

    Article  Google Scholar 

  16. King, M.R., chatGPT: A conversation on artificial intelligence, chatbots, and plagiarism in higher education. Cel. Mol. Bioeng. 16(1), 1–2 (2023). https://doi.org/10.1007/s12195-022-00754-8

  17. Cotton, D.R.E., Cotton, P.A., Shipway, J.R.: Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, pp. 1–12 (2023). https://doi.org/10.1080/14703297.2023.2190148

  18. Foroughi, B., Iranmanesh, M., Hyun, S.S.: Understanding the determinants of mobile banking continuance usage intention. JEIM 32(6), 1015–1033 (2019). https://doi.org/10.1108/JEIM-10-2018-0237

    Article  Google Scholar 

  19. Khayer, A., Bao, Y.: The continuance usage intention of Alipay: Integrating context-awareness and technology continuance theory (TCT). BL 32(3), 211–229, (2019). https://doi.org/10.1108/BL-07-2019-0097

  20. Gilani, M.S., Iranmanesh, M., Nikbin, D., Zailani, S.: EMR continuance usage intention of healthcare professionals. Inform. Health Soc. Care 42(2), 153–165 (2017). https://doi.org/10.3109/17538157.2016.1160245

    Article  Google Scholar 

  21. Weng, G.S., Zailani, S., Iranmanesh, M., Hyun, S.S.: Mobile taxi booking application service’s continuance usage intention by users. Transp. Res. Part D: Transp. Environ. 57, 207–216 (2017). https://doi.org/10.1016/j.trd.2017.07.023

    Article  Google Scholar 

  22. Bhattacherjee, A., Perols, J., Sanford, C.: Information technology continuance: a theoretic extension and empirical test. J. Computer Information Syst. 49(1), 17–26 (2008). https://doi.org/10.1080/08874417.2008.11645302

    Article  Google Scholar 

  23. Jain, N.K., Kaul, D., Sanyal, P.: What drives customers towards mobile shopping? an integrative technology continuance theory perspective. APJML 34(5), 922–943 (2022). https://doi.org/10.1108/APJML-02-2021-0133

    Article  Google Scholar 

  24. Rahi, S., Khan, M.M., Alghizzawi, M.: Extension of technology continuance theory (TCT) with task technology fit (TTF) in the context of Internet banking user continuance intention. IJQRM 38(4), 986–1004 (2020). https://doi.org/10.1108/IJQRM-03-2020-0074

    Article  Google Scholar 

  25. Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211 (1991). https://doi.org/10.1016/0749-5978(91)90020-T

    Article  Google Scholar 

  26. Conner, M., Armitage, C.J.: Extending the theory of planned behavior: a review and avenues for further research. J. Appl. Social Pyschol. 28(15), 1429–1464 (1998). https://doi.org/10.1111/j.1559-1816.1998.tb01685.x

    Article  Google Scholar 

  27. George, J.F.: The theory of planned behavior and Internet purchasing. Internet Res. 14(3), 198–212 (2004). https://doi.org/10.1108/10662240410542634

    Article  Google Scholar 

  28. Morris, M.G., Venkatesh, V., Ackerman, P.L.: Gender and age differences in employee decisions about new technology: an extension to the theory of planned behavior. IEEE Trans. Eng. Manage. 52(1), 69–84 (2005). https://doi.org/10.1109/TEM.2004.839967

    Article  Google Scholar 

  29. Yadav, J., Misra, M., Rana, N.P., Singh, K., Goundar, S.: Netizens’ behavior towards a blockchain-based esports framework: a TPB and machine learning integrated approach. IJSMS 23(4), 665–683 (2022). https://doi.org/10.1108/IJSMS-06-2021-0130

    Article  Google Scholar 

  30. Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319 (1989). https://doi.org/10.2307/249008

    Article  Google Scholar 

  31. Yan, M., Filieri, R., Gorton, M.: Continuance intention of online technologies: a systematic literature review. Int. J. Inf. Manage. 58, 102315 (2021). https://doi.org/10.1016/j.ijinfomgt.2021.102315

    Article  Google Scholar 

  32. Yan, M., Filieri, R., Raguseo, E., Gorton, M.: Mobile apps for healthy living: Factors influencing continuance intention for health apps. Technol. Forecast. Soc. Chang. 166, 120644 (2021). https://doi.org/10.1016/j.techfore.2021.120644

    Article  Google Scholar 

  33. Bhattacherjee, A.: Understanding information systems continuance: an expectation-confirmation model. MIS Q. 25(3), 351 (2001). https://doi.org/10.2307/3250921

    Article  Google Scholar 

  34. Al Amin, M., Arefin, M.S., Sultana, N., Islam, M.R., Jahan, I., Akhtar, A.: Evaluating the customers’ dining attitudes, e-satisfaction and continuance intention toward mobile food ordering apps (MFOAs): evidence from Bangladesh. EJMBE 30(2), 211–229 (2021). https://doi.org/10.1108/EJMBE-04-2020-0066

  35. Huang, C.-K., Chen, C.-D., Liu, Y.-T.: To stay or not to stay? discontinuance intention of gamification apps. ITP 32(6), 1423–1445 (2019). https://doi.org/10.1108/ITP-08-2017-0271

    Article  Google Scholar 

  36. Liao, C., Palvia, P., Chen, J.-L.: Information technology adoption behavior life cycle: toward a technology continuance theory (TCT). Int. J. Inf. Manage. 29(4), 309–320 (2009). https://doi.org/10.1016/j.ijinfomgt.2009.03.004

    Article  Google Scholar 

  37. Ajzen, I., Fishbein, M.: Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin 84(5), 888–918 (1977). https://doi.org/10.1037/0033-2909.84.5.888

  38. Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manage. Sci. 46(2), 186–204 (2000). https://doi.org/10.1287/mnsc.46.2.186.11926

    Article  Google Scholar 

  39. Kock, N.: Common method bias in PLS-SEM: a full collinearity assessment approach. International J. e-Collaboration 11(4), 1 (2015). https://doi.org/10.4018/ijec.2015100101

    Article  Google Scholar 

  40. Podsakoff, P.M., MacKenzie, S.B., Lee, J.-Y., Podsakoff, N. P.: Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology 88(5), 879–903 (2003). https://doi.org/10.1037/0021-9010.88.5.879

  41. CĂ´rte-Real, N., Ruivo, P., Oliveira, T.: Leveraging internet of things and big data analytics initiatives in European and American firms: Is data quality a way to extract business value? Information & Management 57(1), 103141 (2020). https://doi.org/10.1016/j.im.2019.01.003

    Article  Google Scholar 

  42. Fornell, C., Larcker, D.F.: Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 18(1), 39 (1981). https://doi.org/10.2307/3151312

    Article  Google Scholar 

  43. Bagozzi, R.P., Yi, Y.: On the evaluation of structural equation models. JAMS 16(1), 74–94 (1988). https://doi.org/10.1007/BF02723327

    Article  Google Scholar 

  44. Hu, L., Bentler, P.M.: Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Modeling 6(1), 1–55 (1999). https://doi.org/10.1080/10705519909540118

    Article  Google Scholar 

  45. Foroughi, B., Sitthisirinan, S., Iranmanesh M., Nikbin, D., Ghobakhloo, M.: Determinants of travel apps continuance usage intention: extension of technology continuance theory. Current Issues in Tourism, pp. 1–17 (2023). https://doi.org/10.1080/13683500.2023.2169109

Download references

Author information

Authors and Affiliations

  1. School of Business and Management, Christ (Deemed to be University), Ghaziabad, India

    Christina Sanchita Shah & Smriti Mathur

  2. Institute of Management Studies, Ghaziabad, India

    Sushant Kr. Vishnoi

Authors
  1. Christina Sanchita Shah
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Smriti Mathur
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sushant Kr. Vishnoi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Christina Sanchita Shah .

Editor information

Editors and Affiliations

  1. IIM Nagpur, Nagpur, India

    Sujeet K. Sharma

  2. Swansea University, Swansea, UK

    Yogesh K. Dwivedi

  3. IIM Nagpur, Nagpur, India

    Bhimaraya Metri

  4. University of Bradford, Bradford, UK

    Banita Lal

  5. Royal Holloway, University of London, Egham, UK

    Amany Elbanna

Appendix A

Appendix A

The survey items are as follows:

  • Perceived Usefulness

  • Using the ChatGPT improves my performance in my learning.

  • Using the ChatGPT improves my productivity in my learning.

  • Using the ChatGPT enhances my effectiveness in my learning.

  • I find the ChatGPT to be useful in my learning.

  • Perceived Ease of Use

  • My interaction with the ChatGPT is clear and understandable.

  • Interaction with the ChatGPT does not require a lot of my mental effort.

  • I find it easy to get the ChatGPT to do what I want it to do.

  • I find the ChatGPT to be easy to use.

  • Satisfaction

  • My overall experience of ChatGPT use was: very satisfied.

  • My overall experience of ChatGPT use was: very pleased.

  • My overall experience of ChatGPT use was: very contented.

  • My overall experience of ChatGPT use was: absolutely delighted.

  • Confirmation

  • My experience with using ChatGPT was better than what I expected

  • The service level provided by ChatGPT was better than my expectation

  • Overall, most of my expectations from using ChatGPT were confirmed.

  • Attitude

  • Using ChatGPT for learning would be a good idea.

  • Using ChatGPT for learning would be a wise idea.

  • I like the idea of using ChatGPT for learning.

  • Using ChatGPT would be a pleasant experience.

  • Continuance intention

  • I intend to continue using ChatGPT rather than discontinue its use.

  • My intentions are to continue using ChatGPT than use any alternative means.

  • If I could, I would like to continue using ChatGPT as much as possible.

  • Subjective Norm

  • My friends approve of my decision to use ChatGPT

  • My close family approve of my decision to use ChatGPT

  • My colleagues and peers approve of my decision to use ChatGPT

  • I feel social pressure to use ChatGPT

  • The people in my life whose opinion I value would think that I should use ChatGPT

  • Perceived Behavioral Control

  • It is possible for me to use ChatGPT

  • It is easy for me to use ChatGPT

  • I myself decide whether to use ChatGPT or not

  • For me, using ChatGPT is easy

  • If I wanted to, I could easily use ChatGPT

Rights and permissions

Reprints and permissions

Copyright information

© 2024 IFIP International Federation for Information Processing

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Shah, C.S., Mathur, S., Vishnoi, S.K. (2024). Continuance Intention of ChatGPT Use by Students. In: Sharma, S.K., Dwivedi, Y.K., Metri, B., Lal, B., Elbanna, A. (eds) Transfer, Diffusion and Adoption of Next-Generation Digital Technologies. TDIT 2023. IFIP Advances in Information and Communication Technology, vol 697. Springer, Cham. https://doi.org/10.1007/978-3-031-50188-3_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-50188-3_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50187-6

  • Online ISBN: 978-3-031-50188-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships

Search

Navigation