Introduction: The integration of Artificial Intelligence (AI) and gamification into higher education is reshaping educational practices by personalizing learning and fostering essential workforce skills. This study critically examines the effectiveness of these technologies, their impact on student engagement, and the factors influencing students’ acceptance. Methods: A systematic literature review complemented by Topic Modeling using Latent Dirichlet Allocation (LDA) identified key research themes. Subsequently, predictive modeling with machine learning algorithms, hyperparameter optimization, and Local Interpretable Model-Agnostic Explanations (LIME) were applied to classify academic documents and interpret influential factors. Results: Findings indicate that AI effectively customizes educational pathways, enhancing engagement and academic performance. Gamification notably supports soft skill development, providing more interactive assessments than traditional approaches. However, challenges related to data privacy and technological accessibility remain significant, particularly affecting international students and institutions with limited resources. Discussion: AI and gamification demonstrate considerable potential for transforming higher education through personalized learning and interactive skill assessments. Nevertheless, widespread adoption depends on addressing data privacy concerns and ensuring technological equity. Future research should investigate the long-term implications of these technologies in developing students’ adaptability within a dynamic global workforce.
Research AI: integrating AI and gamification in higher education for e-learning optimization and soft skills assessment through a cross-study synthesis
Marengo, Agostino;Pagano, Alessandro;Santamato, Vito
2025-01-01
Abstract
Introduction: The integration of Artificial Intelligence (AI) and gamification into higher education is reshaping educational practices by personalizing learning and fostering essential workforce skills. This study critically examines the effectiveness of these technologies, their impact on student engagement, and the factors influencing students’ acceptance. Methods: A systematic literature review complemented by Topic Modeling using Latent Dirichlet Allocation (LDA) identified key research themes. Subsequently, predictive modeling with machine learning algorithms, hyperparameter optimization, and Local Interpretable Model-Agnostic Explanations (LIME) were applied to classify academic documents and interpret influential factors. Results: Findings indicate that AI effectively customizes educational pathways, enhancing engagement and academic performance. Gamification notably supports soft skill development, providing more interactive assessments than traditional approaches. However, challenges related to data privacy and technological accessibility remain significant, particularly affecting international students and institutions with limited resources. Discussion: AI and gamification demonstrate considerable potential for transforming higher education through personalized learning and interactive skill assessments. Nevertheless, widespread adoption depends on addressing data privacy concerns and ensuring technological equity. Future research should investigate the long-term implications of these technologies in developing students’ adaptability within a dynamic global workforce.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


