Adopting Learning Analytics To Inform Postgraduate Curriculum Design
Dennehy, Denis; Conboy, Kieran; Babu, Jaganath; Schneider, Johannes; Handali, Joshua; vom Brocke, Jan; Hoffmeister, Benedikt; Stein, Armin
Abstract
Understanding students’ sentiment is valuable to understanding the changes that could or should be made in curriculum design at third level. Learning analytics has shown potential for improving student learning experiences and supporting teacher inquiry. Yet, there is limited research that reports on the adoption and actual use of learning analytics to support teacher inquiry. This study captures sentiment of postgraduate students by integrating learning analytics with the steps of teacher inquiry. This study makes two important contributions to teaching and learning literature. First, it reports on the use of learning analytics to support teacher inquiry over three iterations of a business analytics programme between 2016 and 2019. Second, evidence-based recommendations on how to optimise learning analytics to support teacher inquiry are provided.
Keywords
Learning analytics; Sentiment analysis; Curriculum design