University teachers have known for years that traditional lectures often are not a good choice for educating students. They offer a āone size fits allā teaching that does not consider studentsā divergent needs, skills, and interests. Within recent years, however, Learning Analytics-based teaching methods have been developed that enable teachers to take into account some student differences. These methods utilize clickstream data that students generate while they use Learning Management Systems, such as Canvas, and facilitate differentiated teaching. Furthermore, Learning Analytics-based teaching reduces the distance between students and teachers in blended learning as the clickstream data can inform the teachers about a lack of student engagement that they may otherwise not detect.
Many teachers hesitate to apply Learning Analytics because they do not know how to incorporate them into their teaching. In theĀ PAELLA project, we created a short online tutorial that guides teachers through the process of how to prepare, execute, and evaluate a Learning Analytics-based educational intervention in ongoing courses. Teachers can offer such interventions to specific subgroups of students in a course. The interventions enable them to consider some differences between students. TheĀ online tutorialĀ takes up to 40 minutes to watch.