1 TU Dresden (GERMANY)
2 FU Berlin (GERMANY)
About this paper:
Appears in: EDULEARN21 Proceedings
Publication year: 2021
Pages: 7441-7450
ISBN: 978-84-09-31267-2
ISSN: 2340-1117
doi: 10.21125/edulearn.2021.1508
Conference name: 13th International Conference on Education and New Learning Technologies
Dates: 5-6 July, 2021
Location: Online Conference
The use of learning analytics dashboards (LADs) is steadily growing. While they are implemented for a number of different purposes, their design process is often data-driven, and only some concepts are based on pedagogical theories (1). Often, a metacognitive approach is used, which focuses on self-regulated learning and the possibility to reflect on one’s own learning process (1). Other intentions might include cognitive, behavioural or emotional goals but such have not yet been extensively implemented or evaluated (1). The impact of LADs for individual learning processes has been investigated in various contexts. Research shows that their effect differs from learner to learner, and that there are at least some groups of learners who benefit from LADs (1–3). Especially those who are in a middle or low learning performance range, who have a low initial motivation and who tend to compare themselves with peers are likely to improve their learning performance using information from an LAD. That it is why the authors suggest to personalize the information and interventions in an LAD based on Open Learner Models (3).

There are several studies describing learners’ or teachers’ use of LADs, but they hardly focus on the didactical contexts and mostly separate teacher and learner activities. In the project “project title anonymized”, we aim at using LADs in the didactical context of mentoring, which we view as a framework for individual and personalized assistance in acquiring knowledge, providing emotional support and supporting career planning (4). We intend to design LADs that present the mentoring framework and its different components in a holistic and comprehensible way, thereby taking into account that the frame and its components need to be adaptable to individual needs, external changes and a range of different technical devices. We consider LADs as connecting elements for learners and teachers. LADs should support the individual process of knowledge acquisition and foster motivation and self-efficacy awareness by offering reliable information about individual achievements and gathered knowledge. For teachers, the information needs to be presented in a way that aids subsequent planning and the choice of concrete didactical interventions. To guide our own design process, we started with an exploratory survey of learners’ and teachers’ expectations of an LAD.

The paper describes the current status of our design process as well as first results of the associated surveys. As earlier studies have shown (5), students’ expectations of LADs are determined by their need for feedback and orientation concerning further learning. Those needs cannot merely be satisfied by displaying (log) data but require transparency of the underlying didactical concepts as well. Due to technical and data protection requirements, some teachers were sceptical of Learning Analytics in their own teaching contexts. Introducing an LAD that supports learners as well as teachers must take those doubts seriously and consider them already in the design process. It is therefore important to investigate further which information teachers need to be able to support their students’ individual learning processes. In our paper we summarize the results of our exploratory surveys, compare them to current LAD research and give insights into our design process for an LAD that integrates learner and teacher needs equally.
Learning Analytics, Dahsboards, Mentoring, Higher Education.