Complementary or contradictory? The double-edged sword of AI’s impact on effort regulation in higher education

Effort regulation, or the ability to manage and control one’s effort during learning, is a consistent predictor of academic achievement in higher education. The rapid rise of artificial intelligence and its impact on higher education learning environments raises questions about how students are adjusting how they apply and manage effort in their learning. Examining the dynamic interplay between use of AI and effort regulation is necessary to develop effective higher education practices and policies that support improved learning processes for students in the context of AI. This study employed a mixed methods design to explore 1,316 undergraduate pre-service teachers’ perceptions of the relationships between effort regulation and AI use. Quantitative findings showed that students with stronger effort regulation were significantly less likely to use AI. Similarly, qualitative findings showed over half of the sample (52.59%) perceived that using AI could lead to overall disengagement from university work, learning loss, and lack of skill development. When triangulated, findings suggested that students who perceived effort regulation as critical to their learning and skill development were less inclined to use AI because they perceived AI use as undermining their effort regulation and meaningful engagement. These findings have implications for higher education practice: these suggest a need to explicitly communicate to students the importance of effort regulation in learning and the appropriate ways in which AI can be used to enhance effort regulation.