PreprintCited by 26Artificial Intelligence in EducationAcademic integrity and plagiarismEthics and Social Impacts of AI

Reacting to Generative AI: Insights from Student and Faculty Discussions on Reddit

Open access
Wu, Chuhao, Wang, Xinyu, Carroll, John, Rajtmajer, Sarah·2024·ACM Web Science Conference (WebSci)

Abstract

Generative Artificial intelligence (GenAI) such as ChatGPT has elicited strong reactions from almost all stakeholders across the education system. Education-oriented and academic social media communities provide an important venue for these stakeholders to share experiences and exchange ideas about GenAI, which is constructive for developing human-centered policies. This study examines early user reactions to GenAI, consisting of 725 Reddit threads between 06/2022 and 05/2023. Through natural language processing (NLP) and content analysis, we observe an increasingly negative sentiment in the discussion and identify six main categories of student and faculty experiences of GenAI in education. These experiences reflect concerns about academic integrity and AI's negative impact on the value of traditional education. Our analysis also highlights an additional workload imposed by new technologies. Our findings suggest that dialogue between stakeholders in the education community is critical and can mitigate sources of tension between students and faculty.

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Research works printed but not linked: 40

  1. Alan Akbik, Tanja Bergmann, Duncan Blythe, Kashif Rasul, Stefan Schweter, and Roland Vollgraf. 2019. FLAIR: An Easy-to-Use Framework for State-of-the-Art NLP. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations). 54-59.
  2. Ashraf Alam. 2022. Employing adaptive learning and intelligent tutoring robots for virtual classrooms and smart campuses: reforming education in the age of artificial intelligence. In Advanced Computing and Intelligent Technologies: Proceedings of ICACIT 2022. Springer, 395-406.
  3. Carl Auerbach and Louise B Silverstein. 2003. Qualitative data: An introduction to coding and analysis. Vol. 21. NYU press.
  4. David Baidoo-Anu and Leticia Owusu Ansah. 2023. 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 (2023), 52-62.
  5. Cara Brems, Martina Temmerman, Todd Graham, and Marcel Broersma. 2017. Personal branding on Twitter: How employed and freelance journalists stage themselves on social media. Digital journalism 5, 4 (2017), 443-459.
  6. Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D. Kaplan, Pra- fulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, and Amanda Askell. 2020. Language Models Are Few-Shot Learners. Advances in neural information processing systems 33 (2020), 1877-1901.
  7. Wonchan Choi, Yan Zhang, and Besiki Stvilia. 2023. Exploring Applications and User Experience with Generative AI Tools: A Content Analysis of Reddit Posts on ChatGPT. Proceedings of the Association for Information Science and Technology 60, 1 (2023), 543-546.
  8. Clayton M Christensen and Henry J Eyring. 2011. The innovative university: Changing the DNA of higher education from the inside out. John Wiley & Sons.
  9. Nassim Dehouche. 2021. Plagiarism in the age of massive Generative Pre-trained Transformers (GPT-3). Ethics in Science and Environmental Politics 21 (2021), 17-23.
  10. Xuefan Dong and Ying Lian. 2021. A review of social media-based public opinion analyses: Challenges and recommendations. Technology in Society 67 (2021), 101724.
  11. Andy Extance. 2023. ChatGPT has entered the classroom: how LLMs could transform education. Nature 623, 7987 (2023), 474-477.
  12. Yunhe Feng, Pradhyumna Poralla, Swagatika Dash, Kaicheng Li, Vrushabh Desai, and Meikang Qiu. 2023. The impact of chatgpt on streaming media: A crowd- sourced and data-driven analysis using twitter and reddit. In 2023 IEEE 9th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing,(HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS). IEEE, 222-227.
  13. José-María Fernández-Batanero, Pedro Román-Graván, Miguel-María Reyes- Rebollo, and Marta Montenegro-Rueda. 2021. Impact of educational technology on teacher stress and anxiety: A literature review. International journal of envi- ronmental research and public health 18, 2 (2021), 548.
  14. Barbara Silveira Fraga, Ana Paula Couto da Silva, and Fabricio Murai. 2018. Online social networks in health care: a study of mental disorders on Reddit. In 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI). IEEE, 568-573.
  15. Catherine A Gao, Frederick M Howard, Nikolay S Markov, Emma C Dyer, Siddhi Ramesh, Yuan Luo, and Alexander T Pearson. 2022. Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers. BioRxiv (2022), 2022-12.
  16. Simone Grassini. 2023. Shaping the future of education: exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences 13, 7 (2023), 692.
  17. Farrokh Habibzadeh. 2023. GPTZero performance in identifying artificial intelligence-generated medical texts: a preliminary study. Journal of Korean Medical Science 38, 38 (2023).
  18. Jari J Hakanen, Arnold B Bakker, and Wilmar B Schaufeli. 2006. Burnout and work engagement among teachers. Journal of school psychology 43, 6 (2006), 495-513.
  19. Mubin Ul Haque, Isuru Dharmadasa, Zarrin Tasnim Sworna, Roshan Namal Rajapakse, and Hussain Ahmad. 2022. " I think this is the most disruptive technology": Exploring Sentiments of ChatGPT Early Adopters using Twitter Data. arXiv preprint arXiv:2212.05856 (2022). · arXiv
  20. Sue Hrasky and David Kronenberg. 2011. Curriculum redesign as a faculty- centred approach to plagiarism reduction. International Journal for Educational Integrity 7, 2 (2011).
  21. Hui-Wen Huang, Zehui Li, and Linda Taylor. 2020. The Effectiveness of Us- ing Grammarly to Improve Students' Writing Skills. In Proceedings of the 5th International Conference on Distance Education and Learning. 122-127.
  22. Eva Jereb, Matjaž Perc, Barbara Lämmlein, Janja Jerebic, Marko Urh, Iztok Podbre- gar, and Polona Šprajc. 2018. Factors influencing plagiarism in higher education: A comparison of German and Slovene students. PloS one 13, 8 (2018), e0202252.
  23. Georgios Lampropoulos, Richard E Ferdig, and Regina Kaplan-Rakowski. 2023. A Social Media Data Analysis of General and Educational Use of ChatGPT: Understanding Emotional Educators. Available at SSRN 4468181 (2023).
  24. Xiao Ma, Jeff Hancock, and Mor Naaman. 2016. Anonymity, intimacy and self- disclosure in social media. In Proceedings of the 2016 CHI conference on human factors in computing systems. 3857-3869.
  25. Ehsan Mohammadi, Mike Thelwall, Mary Kwasny, and Kristi L Holmes. 2018. Academic information on Twitter: A user survey. PloS one 13, 5 (2018), e0197265.
  26. Junaid Qadir. 2023. Engineering education in the era of ChatGPT: Promise and pitfalls of generative AI for education. In 2023 IEEE Global Engineering Education Conference (EDUCON). IEEE, 1-9.
  27. Md Mostafizer Rahman and Yutaka Watanobe. 2023. ChatGPT for education and research: Opportunities, threats, and strategies. Applied Sciences 13, 9 (2023), 5783.
  28. Matthew Rowe and Harith Alani. 2014. Mining and comparing engagement dynamics across multiple social media platforms. In Proceedings of the 2014 ACM conference on Web science. 229-238.
  29. Jürgen Rudolph, Samson Tan, and Shannon Tan. 2023. ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning and Teaching 6, 1 (2023).
  30. Ben Shneiderman. 2022. Human-centered AI. Oxford University Press.
  31. Emmanuel Sibomana, Irenee Ndayambaje, and Emmanuel Uwambayinema. 2018. Plagiarism in higher education environment: Causes and solutions. Rwandan journal of education 4, 2 (2018), 15-23.
  32. Harpreet Singh, Mohammad-Hassan Tayarani-Najaran, and Muhammad Yaqoob. 2023. Exploring Computer Science Students' Perception of ChatGPT in Higher Education: A Descriptive and Correlation Study. Education Sciences 13, 9 (2023), 924.
  33. Jan Smits and Tijn Borghuis. 2022. Generative AI and Intellectual Property Rights. In Law and Artificial Intelligence: Regulating AI and Applying AI in Legal Practice. Springer, 323-344.
  34. Sarin Sok and Kimkong Heng. 2023. ChatGPT for education and research: A review of benefits and risks. Available at SSRN 4378735 (2023).
  35. Shaina J Sowles, Melissa J Krauss, Lewam Gebremedhn, and Patricia A Cavazos- Rehg. 2017. "I feel like I've hit the bottom and have no idea what to do": Supportive social networking on Reddit for individuals with a desire to quit cannabis use. Substance abuse 38, 4 (2017), 477-482.
  36. Meng-Lin Tsai, Chong Wei Ong, and Cheng-Liang Chen. 2023. Exploring the use of large language models (LLMs) in chemical engineering education: Building core course problem models with Chat-GPT. Education for Chemical Engineers 44 (2023), 71-95.
  37. Sanna Vehviläinen, Erika Löfström, and Anne Nevgi. 2018. Dealing with pla- giarism in the academic community: Emotional engagement and moral distress. Higher Education 75 (2018), 1-18.
  38. Hengki Wijaya and Kara Elizabeth Gruber. 2018. Ethics perspective and regulation of plagiarism in Higher Education. International Journal of Humanities and Innovation (IJHI) 1, 1 (2018), 17-25.
  39. Bin Zhang, Haibin Xia, and Hun-ok Lim. 2019. Development of an AI based teach- ing assisting system. In Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing. 1-5.
  40. Wenkai Zhou, Chi Zhang, Linwan Wu, and Meghana Shashidhar. 2023. ChatGPT and marketing: Analyzing public discourse in early Twitter posts. Journal of Marketing Analytics (2023), 1-14.

Cited by

Sorted by citations

Authors
Wu, C., Wang, X., Carroll, J., & Rajtmajer, S.
Affiliations
Pennsylvania State University (US)
Venue
ACM Web Science Conference (WebSci)
Published
2024-01-18
Pages
103-113
OpenAlex
W4394879862
Cited by
26
References
16
Citations by year
2026: 10 · 2025: 13 · 2024: 3
FWCI
9.88
Type
conference paper
Language
en
Open access
Locations
  • ACM Web Science Conference (WebSci) (publishedVersion)
  • EdArXiv (OSF Preprints) (submittedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Social Sciences › Safety Research › Academic integrity and plagiarism
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
generative AI in education, ChatGPT, student and faculty perceptions, Reddit discussions, academic integrity, AI policy in higher education, stakeholder conflict

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