Students’ Motivation in the Artificial Intelligence Environment: A Systematic Review

Abstract

Students’ motivation affects several educational variables related to students’ learning, including the learning outcomes. Artificial intelligence tools are flourishing in educational contexts. Research related to artificial intelligence contexts needs to address the various aspects of students’ motivation in these contexts. The present research intended to perform a systematic review of research papers that addressed students’ motivation in the artificial intelligence context. Specifically, it intended to examine the types of such motivation in terms of four aspects: description, factors influencing the motivation type, factors influenced by the motivation type, and the type as a mediator between other educational variables. To look for appropriate papers, we used the terms ‘artificial intelligence’ and ‘students’ motivation’ as keys used to search appropriate papers in Scopus, Web of Science and ‘Scholar; and afterword’s we added terms as ‘influence’ or ‘impact’ and ‘mediator; The results of the review showed that not all four aspects were realized in the literature arrived at as a result of the collecting data process. The four aspects were found for some of the motivation types, such as intrinsic motivation, while other types did not have the four aspects, such as extrinsic motivation. We recommend that educational researchers address each one of the four aspects of the different motivation types in the artificial intelligence context. This approach would give educators means for understanding how to encourage students’ motivation to learn and thus their learning outcomes in the new educational context.