Insight of supporting the learning of a challenging content for special education preservice teachers with learning analytics
Abstract: Teaching as a profession is valued in Finland among young people applying for universities, and research methods are important part of teacher training. Quantitative research methods, although at times considered exhaustively rigorous, are part of the teacher training. Thus, new ways for teaching with technology and supporting innovatively learning are required. For this task, an exclusively online, flipped learning approach with novel technological approaches were developed and investigated. The technology included a digital learning environment, tandem use of conferencing systems (i.e., Zoom® and Teams®), and active use of learning and dispositional learning analytics for supporting the students. To study the functionality of the framework, we used dispositional learning analytics data with pre-post-test design for time management, task avoidance, perceived negative emotions, certainty of career choice, grades as well as knowledge for, and attitudes of learning analytics among preservice teachers (N = 58). Bootstrapped paired sample t-tests were used for the analysis. Results included statistically significant changes with the zone of desired effect sizes in task avoidance, time management, anxiety, knowledge for, and attitudes of learning analytics. The results indicate that flipped approaches in online settings can be used with preservice teacher for challenging content.