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PreprintCited by 14Artificial Intelligence in EducationAI in Service InteractionsArtificial Intelligence in Healthcare and Education

Me and My AI Bot: Exploring the 'AIholic' Phenomenon and University Students' Dependency on Generative AI Chatbots - Is This the New Academic Addiction?

Open access
Salah, Mohammed, Abdelfattah, Fadi, Alhalbusi, Hussam, Mukhaini, Muna Al·2023·Research Square
DOI 10.21203/rs.3.rs-3508563/v1
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Abstract

Amidst the buzz of technological advancement in education, our study unveils a more disconcerting narrative surrounding student chatbot interactions. Our investigation has found that students, primarily driven by intrinsic motivations like competence and relatedness, increasingly lean on chatbots. This dependence is not just a preference but borders on an alarming reliance, magnified exponentially by their individual risk perceptions. While celebrating AI's rapid integration in education is tempting, our results raise urgent red flags. Many hypotheses were supported, pointing toward a potential over-dependence on chatbots. Nevertheless, the unpredictable outcomes were most revealing, exposing the unpredictable terrain of AI's role in education. It is no longer a matter of if but how deep the rabbit hole of dependency goes. As we stand on the cusp of an educational revolution, caution is urgently needed. Before we wholly embrace chatbots as primary educators, it is imperative to understand the repercussions of replacing human touch with AI interactions. This study serves as a stark wake-up call, urging stakeholders to reconsider the unchecked integration of chatbots in learning environments. The future of education may very well be digital, but at what cost to human connection and autonomy?

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Crossref · 10.21203/rs.3.rs-3508563/v1

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88 of 88 references verified0 citation errors · 0 not checkable

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  • Need for relatedness predicts LLM-CB dependence.

    “Similarly, Salah identified individual needs (need for competence, need for relatedness, need for autonomy) as predictors of LLM-CB dependence119.”

    From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [119]

    The Theoretical Model Hypothesis Testing section reports that relatedness predicted an inability to reduce chatbot use (H5). It also says the proposed link between relatedness and actual dependency level was unsupported (H6), so the claim is supported only if dependence refers to difficulty reducing use, not actual dependency level. No page number is provided in our copy. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Need for autonomy predicts LLM-CB dependence.

    “Similarly, Salah identified individual needs (need for competence, need for relatedness, need for autonomy) as predictors of LLM-CB dependence119.”

    From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [119]

  • Need for competence predicts LLM-CB dependence.

    “Similarly, Salah identified individual needs (need for competence, need for relatedness, need for autonomy) as predictors of LLM-CB dependence119.”

    From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [119]

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Cites

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1 of the 89 references couldn’t be matched to a known paper.

Research works printed but not linked: 4

  1. Brandtzaeg, P. B., & Følstad, A. (2018). Chatbots: changing user needs and motivations. interactions, 25(5), 38-43. .
  2. Luigjes, J., Lorenzetti, V., de Haan, S., Youssef, G. J., Murawski, C., Sjoerds, Z., van den Brink, W., Denys, D., Fontenelle, L. F., & Yücel, M. (2019). De ning compulsive behavior. Neuropsychology review, 29, 4-13.
  3. Nosrati, S., Sabzali, M., Heidari, A., Sar , T., & Sabbar, S. (2020). Chatbots, counselling, and discontents of the digital life. Journal of Cyberspace Studies, 4(2), 153-172.
  4. Yadav, D., Malik, P., Dabas, K., & Singh, P. (2019). Feedpal: Understanding opportunities for chatbots in breastfeeding education of women in india. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1-30.

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Authors
Salah, M., Abdelfattah, F., Alhalbusi, H., & Mukhaini, M. A.
Affiliations
  • Modern College of Business and Science (OM)
  • Ahmed Bin Mohammed Military College (QA)
ORCID
Venue
Research Square
Publisher
Springer Science and Business Media LLC
Published
2023-10-31
DOI
10.21203/rs.3.rs-3508563/v1
OpenAlex
W4388048911
Cited by
12
References
89
Citations by year
2026: 4 · 2025: 4 · 2024: 3 · 2023: 1
Type
posted content
Language
en
Open access
Licence
Locations
Research Square (acceptedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
generative AI chatbots, university students, intrinsic motivation, risk perception, student independence

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