The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review

Abstract

The growing integration of artificial intelligence (AI) dialogue systems within educational and research settings highlights the importance of learning aids. Despite examination of the ethical concerns associated with these technologies, there is a noticeable gap in investigations on how these ethical issues of AI contribute to students’ over-reliance on AI dialogue systems, and how such over-reliance affects students’ cognitive abilities. Overreliance on AI occurs when users accept AI-generated recommendations without question, leading to errors in task performance in the context of decision-making. This typically arises when individuals struggle to assess the reliability of AI or how much trust to place in its suggestions. This systematic review investigates how students’ over-reliance on AI dialogue systems, particularly those embedded with generative models for academic research and learning, affects their critical cognitive capabilities including decision-making, critical thinking, and analytical reasoning. By using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, our systematic review evaluated a body of literature addressing the contributing factors and effects of such over-reliance within educational and research contexts. The comprehensive literature review spanned 14 articles retrieved from four distinguished databases: ProQuest, IEEE Xplore, ScienceDirect, and Web of Science. Our findings indicate that over-reliance stemming from ethical issues of AI impacts cognitive abilities, as individuals increasingly favor fast and optimal solutions over slow ones constrained by practicality. This tendency explains why users prefer efficient cognitive shortcuts, or heuristics, even amidst the ethical issues presented by AI technologies.

WITHDRAWN: The role of students’ higher-order thinking skills in the relationship between academic achievements and machine learning using generative AI chatbots

“…The results of the present study align with those of prior research (Hopcan et al, 2023;Jeon et al, 2023;Zhai et al, 2024) pertaining to the features of AI chatbots. Speci cally, by elucidating their advancements and potentials, these features can in uence students' perceptions and higher-order thinking skills, as well as their attitudes toward machine learning and AI technologies.…”

“…The integration of higher-order thinking skills, machine learning, and generative AI chatbots is transforming human-computer interaction, particularly in higher education. Recent research (e.g., Jia & Tun, 2024;Zhai et al, 2024) highlights AI's potential to revolutionize learning, enhancing critical thinking, self-e cacy, and student engagement. While AI can boost learning effectiveness and support higherorder thinking development, it also raises concerns regarding misuse and its impact on students' learning achievements.…”

“…The absence of signi cant mediating effects is a relatively underexplored aspect of research on higher-order thinking skills, prompting questions about speci c contextual factors that may in uence students' academic achievements using generative AI and machine learning technologies. The existing literature (Hopcan et al, 2023;Zhai et al, 2024) falls short of adequately addressing the potential moderating effects of these factors on the relationships under investigation. While previous studies (Baskoro et al, 2023;Lu et al, 2024) have highlighted the relevance of higher-order thinking skills and their associations with academic performance and machine learning, the moderating role of creativity, as well as the interplay between problem-solving and critical thinking as both mediators and moderators, remains conspicuously unexplored.…”