Investigating students' perceived benefits of system- vs. teacher-based learning analytics feedback

Feedback is considered to be essential for supporting learning processes. As learning is increasingly facilitated through digital learning environments new methods such as learning analytics enable additional insights into learning processes. These data can be used as a source for offering feedback to learners using dashboards, messages, recommendations or prompts. However, research on benefits students perceive from feedback based on learning analytics is limited. Thus, this study investigates students’ perceptions of system- vs. teacher-based learning analytics feedback either with or without recommendations using a quasi-experimental approach. Findings indicate that benefits associated with the different feedback representations were perceived significantly different. Feedback with recommendations was perceived more beneficial than system-based feedback without recommendations. Future research might investigate students’ perceptions of and reactions to learning analytics feedback in authentic learning settings.