Artificial intelligence in everyday classrooms: Effects of a purpose-built AI study assistant on secondary students’ learning, motivation, and engagement
TL;DR
The findings suggest that purpose-built AI study assistants can support academic learning when integrated into regular classroom instruction, however, short-term exposure and predominantly task-focused interactions may limit their influence on motivational and engagement-related outcomes.
Abstract
Background Recent advances in artificial intelligence (AI) have accelerated the development of educational technologies intended to support students’ learning processes. However, classroom-based evidence on the educational impact of purpose-built AI applications remains limited, particularly across national contexts. Methods This study examined the effects of an AI conversational study assistant (Study Buddy) on secondary students’ academic performance, motivation, and engagement in authentic school settings. A quasi-experimental design was employed across two case studies conducted in Cyprus (Grade 10 Physics, N = 47) and Greece (Grade 7 History, N = 70). In each context, intact classes were assigned to experimental and control conditions. Academic performance was assessed using curriculum-aligned teacher-developed tests, while motivation and engagement were measured using the Motivation and Engagement Survey. In addition, system-generated usage logs were analyzed descriptively to document student access, interaction intensity, and patterns of tool use during the intervention. Statistical analyses included descriptive statistics and parametric or non-parametric group comparisons depending on distributional assumptions. Results Students who used Study Buddy demonstrated significantly higher learning gains in Physics and higher post-test scores in History compared to peers in control groups. In contrast, no statistically significant differences were observed for motivation or engagement in either case study. Usage log analysis indicated that students actively engaged with the application and that interaction patterns reflected the instructional design of each case study. Conclusions The findings suggest that purpose-built AI study assistants can support academic learning when integrated into regular classroom instruction. However, short-term exposure and predominantly task-focused interactions may limit their influence on motivational and engagement-related outcomes. The study contributes classroom-based, cross-national evidence on educational AI tools and highlights the importance of instructional design and teacher mediation in shaping both usage patterns and learning outcomes.