Learning about learning : unravelling interactions in higher education with learning analytics

Abstract

Learning is a multidimensional process that evolves and changes, influenced and affected by several elements. The sudden shift in teaching modality when the pandemic hit implied changes in social interactions, digital platforms use, and collaboration dynamics; potentially impacting the students' learning experience.

This research, initially motivated by the unknown effect of the pandemic on teaching and learning practices, lies on the grounds of the Learning Analytics (LA) research field, focused on analysing and understanding learning processes and the environments in which they occur. The dissertation takes the standpoint of interactions with the aim of furthering our understanding of how different types of interactions occurring in higher education inform and relate to students' learning strategies and behaviours. In this dissertation, quantitative and qualitative approaches, as well as a variety of data sources, are used to explore the research question: How and to what extent can the analysis of interactions be used to inform features and changes in undergraduates' learning strategies and behaviours? In educational contexts, interactions correspond to the various ways of communication and engagement that occur between learners, instructors, learning material, and technology. The dissertation thereby presents five chapters focused on exploring several interaction types in the context of higher education, including interactions between humans (student, instructor) and systems (digital ecosystem, content).

The results presented in the chapters provide insights into the presence and evolution of study profiles, the relationship between usage of digital platforms and resources, assignment solving, and academic performance, the effect of a data-driven intervention of class schedules and its effect on students' learning activity and experiences, the design and adoption of an institutional programme for supporting instructors, as well as insights on the dynamics of discussion forum interactions in different teaching modalities, and their value and limitations for informing the identification of students at risk of failing.

Three main contributions are highlighted in this dissertation. Firstly, by analysing different types of interactions in higher education, the dissertation provides an overview of how these interactions influence each other as well as their relationship with students' learning strategies and behaviours. Furthermore, these insights are helpful for informing the development and adoption of LA research on interactions, which are illustrated in a conceptual framework integrating the dissertation findings, implications and recommendations. Secondly, the dissertation contributes to addressing shortcomings of LA research. It provides insights into students' behaviours and strategies, interactions, learning material usage, course improvements, and interventions in educational settings. Furthermore, practical recommendations in regards to data, resources, and support are provided. Finally, by taking into consideration students, instructors, and digital ecosystems, the dissertation offers insights into the effect of the pandemic on teaching and learning practices in higher education.