Exploring User Perspectives on ChatGPT: Applications, Perceptions, and Implications for AI-Integrated Education
Abstract
To foster the development of pedagogically potent and ethically sound AI-integrated learning landscapes, it is pivotal to critically explore the perceptions and experiences of the users immersed in these contexts. In this study, we perform a thorough qualitative content analysis across four key social media platforms. Our goal is to understand the user experience (UX) and views of early adopters of ChatGPT across different educational sectors. The results of our research show that ChatGPT is most commonly used in the domains of higher education, K-12 education, and practical skills training. In social media dialogues, the topics most frequently associated with ChatGPT are productivity, efficiency, and ethics. Early adopters' attitudes towards ChatGPT are multifaceted. On one hand, some users view it as a transformative tool capable of amplifying student self-efficacy and learning motivation. On the other hand, there is a degree of apprehension among concerned users. They worry about a potential overdependence on the AI system, which they fear might encourage superficial learning habits and erode students' social and critical thinking skills. This dichotomy of opinions underscores the complexity of Human-AI Interaction in educational contexts. Our investigation adds depth to this ongoing discourse, providing crowd-sourced insights for educators and learners who are considering incorporating ChatGPT or similar generative AI tools into their pedagogical strategies.
Cite
@article{arxiv.2305.13114,
title = {Exploring User Perspectives on ChatGPT: Applications, Perceptions, and Implications for AI-Integrated Education},
author = {Reza Hadi Mogavi and Chao Deng and Justin Juho Kim and Pengyuan Zhou and Young D. Kwon and Ahmed Hosny Saleh Metwally and Ahmed Tlili and Simone Bassanelli and Antonio Bucchiarone and Sujit Gujar and Lennart E. Nacke and Pan Hui},
journal= {arXiv preprint arXiv:2305.13114},
year = {2023}
}
Comments
This is the authors' preprint version of the paper accepted by the Journal of Computers in Human Behavior: Artificial Humans (doi: https://doi.org/10.1016/j.chbah.2023.100027)