The Role of Active Learning Strategies Enhanced by Learning Analytics in Improving Students’ Learning Motivation in Digital Learning Environments

Abstract

This study explores the impact of active learning strategies enhanced by learning analytics on students’ motivation in digital learning environments. The main objective is to examine how integrating interactive pedagogical approaches with data-driven tools can increase engagement, support self-regulated learning, and improve overall motivation. The study targeted students in primary and secondary schools in Saudi Arabia, with a sample of 332 students selected through stratified random sampling. A mixed-methods approach was employed, combining a structured questionnaire with semi-structured interviews and focus groups. The instruments were validated for content, construct, and reliability (Cronbach’s alpha ≥ 0.80). Results indicate strong positive correlations between active learning strategies and motivation (r=0.642, p<0.01), and between learning analytics and motivation (r=0.593, p<0.01). Multiple regression revealed that the combination of both strategies explained 52.7% of the variance in motivation, with a significant interaction effect (β=0.174, p=0.001). No significant differences were found based on gender or grade level. The study recommends integrating active learning strategies with learning analytics, providing personalized feedback, teacher training, and supportive infrastructure to foster engagement and motivation. These findings highlight the potential of data-informed, student-centered digital learning environments to enhance learning outcomes.