Trusting the Algorithm: Emotional Engagement with ChatGPT in Higher Education
DOI:
https://doi.org/10.5281/zenodo.17423731Keywords:
ChatGPT, emotional intelligence, higher education, AI in learning, digital pedagogy, emotional framing, trust in AI.Abstract
This study examines emotional engagement with ChatGPT among 121 university students from diverse academic disciplines, focusing on the relationships between trust in the AI, the emotional framing of prompts, and the explicit use of ChatGPT for emotional support. Results reveal a paradox: higher trust correlates with increased emotional self-awareness (r = .386) and perceived emotional intelligence (r = .508), while deliberate emotional framing is linked to lower perceived AI emotional intelligence (r = –.412) and reduced emotional benefits (r = –.259). Students who use ChatGPT for emotional support report diminished emotional awareness (r = –.190) and less favourable emotional outcomes (r = –.270), indicating an “empathic expectation gap” where emotional intent exposes the system’s limitations. The findings highlight the need to integrate ChatGPT in digital pedagogy as a reflective tool rather than a substitute for human connection, with attention to ethical design, user education, and emotional literacy.References
Andries, V., & Robertson, J. (2023). Alexa doesn’t have that many feelings: Children’s understanding of AI through interactions with smart speakers in their homes. Computers and Education: Artificial Intelligence, 5, 100176. https://doi.org/10.1016/j.caeai.2023.100176
Feng, H., Zeng, Y., & Lu, E. (2022). Brain-inspired affective empathy computational model and its application on altruistic rescue task. Frontiers in Computational Neuroscience, 16, 784967. https://doi.org/10.3389/fncom.2022.784967
Gill, A., & Mathur, A. (2024). Emotional intelligence in the age of AI: Enhancing workforce development for human–machine collaboration. In Sustainable innovation for industry 6.0 (pp. 271–294). IGI Global. https://doi.org/10.4018/979-8-3693-3140-8.ch014
Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627–660. https://doi.org/10.5465/annals.2018.0057
Harari, Y. N. (2017). Reboot for the AI revolution. Nature, 550(7676), 324–327. https://doi.org/10.1038/550324a
Ovsyannikova, D., de Mello, V. O., & Inzlicht, M. (2025). Third-party evaluators perceive AI as more compassionate than expert humans. Communications Psychology, 3(1), 4. https://doi.org/10.1038/s44271-024-00182-6
Park, G., Yim, M. C., Chung, J., & Lee, S. (2023). Effect of AI chatbot empathy and identity disclosure on willingness to donate: The mediation of humanness and social presence. Behaviour & Information Technology, 42(12), 1998–2010. https://doi.org/10.1080/0144929X.2022.2105746
Shen, J., DiPaola, D., Ali, S., Sap, M., Park, H. W., & Breazeal, C. (2024). Empathy toward artificial intelligence versus human experiences and the role of transparency in mental health and social support chatbot design: Comparative study. JMIR Mental Health, 11, e62679. https://doi.org/10.2196/62679
Wang, Q., Walsh, S., Si, M., Kephart, J., Weisz, J. D., & Goel, A. K. (2024). Theory of mind in human–AI interaction. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1–6). Association for Computing Machinery. https://doi.org/10.1145/3613905.3636308
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Aljula Gjeloshi, Elena Kokthi

This work is licensed under a Creative Commons Attribution 4.0 International License.