Learning analytics to develop future competences in higher education: a case study

Abstract

AbstractHigher education institutions are challenged to develop innovative educational solutions to meet the competence development requirements set by the emerging future. This qualitative case study aims to identify the future competences considered important for higher education students to acquire during their studies and how the development of these competences can be supported with learning analytics. Reflection on these issues is based on three dimensions (subject development, object, and social environment) of future competences. A special emphasis is placed on the views of 19 teaching professionals gathered from group interviews and analyzed through a qualitative content analysis. The findings indicate that subject development-related future competences, such as reflective competence, self-awareness and self-management, learning literacy, and personal agency and self-efficacy were strongly identified as necessary future competences. The potential of learning analytics to support their development was also widely recognized as it provides means to reflect on learning and competence development and increase one’s self-awareness of strengths and weaknesses. In addition, learning analytics was considered to promote goal-orientation, metacognition and learning to learn, active engagement as well as learning confidence. To deal with complex topics and tasks, students should also acquire object-related competences, such as changeability and digital competence. In addition, they need cooperation and communication competence as well as a developmental mindset to operate successfully in social environments. The use of learning analytics to support most of these object and social environment-related competences was considered promising as it enables the wide exploitation of digital tools and systems, the analysis and visualization of social interactions, and the formation of purposeful learning groups and communal development practices. However, concrete ways of applying learning analytics were largely unacknowledged. This study provides useful insights on the relationship of important future competences and learning analytics while expanding on previous research and conceptual modelling. The findings support professionals working at higher education institutions in facilitating successful conditions for the development of future competences and in advancing purposeful use of learning analytics.