The digitalisation of students’ lives leads to the almost ubiquitous use of apps for all parts of life. The digitalisation of university learning has led to many learning management systems in use in institutions of higher education. However, it has not quite kept up with the demand for highly flexible learning at all hours and in all locations. Learning apps are not used frequently by universities to improve students’ personalised learning. The paper reports on an app that combines self-regulated learning and the Quantified-Self approach to support such ubiquitous learning. When students track their learning in an app, they can later on benefit from the tracked data on an individual as well as aggregated level. Data analyses provide the potential for individual evaluation of the learning or comparison to peers. Thus, this study derives an extensive set of user stories for such app from the literature. Those user stories are the basis for evaluating the approach by turning them into visualisations that are then tested based on a mixed-method approach. The evaluation finds differences among the evaluated visualisations regarding ease of understanding, intuitive operations, visual appeal, and metacognition as well as potential for further improvement. From the findings an improved set of visualisations is generated and the results are fed back into the user stories.
Witt, Josepha; Melzer, Philipp; and Schoop, Mareike, "Using a Quantified-Self App to Personalise Learning -- A Comparison of Visualisations for the Evaluation of the Learning Process" (2019). UK Academy for Information Systems Conference Proceedings 2019. 43.