Learning Analytics in Higher Education -- Exploring Students and Teachers Expectations in Germany

TL;DR

This study explores the expectations and attitudes of students and teachers in German higher education towards learning analytics, providing insights for effective implementation and development of such technologies.

Contribution

It applies the Sheila framework to assess stakeholder aspirations, comparing ideal and expected scenarios among students and teachers in a German university.

Findings

Students and teachers have differing expectations of learning analytics.

Attitudes vary across disciplines and stakeholder groups.

Practical implications for implementing learning analytics are discussed.

Abstract

Technology enhanced learning analytics has the potential to play a significant role in higher education in the future. Opinions and expectations towards technology and learning analytics, thus, are vital to consider for institutional developments in higher education institutions. The Sheila framework offers instruments to yield exploratory knowledge about stakeholder aspirations towards technology, such as learning analytics in higher education. The sample of the study consists of students (N = 1169) and teachers (N = 497) at a higher education institution in Germany. Using self-report questionnaires, we assessed students and teachers attitudes towards learning analytics in higher education teaching, comparing ideal and expected circumstances. We report results on the attitudes of students, teachers, as well as comparisons of the two groups and different disciplines. We discuss the results with regard to practical implications for the implementation and further developments of learning analytics in higher education.