Emerging Technology-Based Motivational Strategies: A Systematic Review with Meta-Analysis - Jhon Alé; María Luisa Arancibia (Education Sciences)
To contribute to the design of better teaching strategies mediated by emerging technologies, the aim of this systematic review and meta-analysis was to estimate the effect sizes of the attention, relevance, confidence, and satisfaction (ARCS) motivational model with technologies such as AI and XR regarding academic performance and student motivation. From a sample of 2656 studies obtained from WoS, Scopus, ERIC, and APAPsycNet, 32 primary studies with quasi-experimental designs were selected, where the ARCS model and some types of emerging technology were used. To estimate the possible risks of bias and overestimation, preliminary tests with funnel plots were used. The effect sizes were calculated with Cohen’s d using random-effects models. Moderations were also examined using fixed-effects models and heterogeneity tests. The results showed a moderate effect on academic performance (ES: 0.596, 95% CI: 0.443–0.748) and a strong effect on motivation (ES: 0.886, 95% CI: 0.640–1.133), both with low bias. According to the moderator analysis on academic performance, no significant differences were found between face-to-face and virtual teaching. Furthermore, the greatest effects on academic performance were observed when using AI and XR in subjects like the natural sciences and arts and when combining the motivational model with strategies such as gamification and project-based learning. Finally, gamification and game-based learning proved to be an effective strategy to increase motivation.