Search results

Learning analytics are often used as proxies for student engagement. More qualitative data on how post-secondary students engage with course elements are needed to guide the design, development and deployment of learning analytics information, particularly in the use of nudge techniques.

In the context of a graduate-level quantitative course within a public health core curriculum, the following research questions were explored: What do students cite as their motivations when making decisions about whether, when or how to engage with course content and learning supports? and What are student reactions to visual prompts designed to activate these motivations? This qualitative study included two phases of interviews: (1) in-depth interviews with screen sharing as students interacted with the learning management system and (2) in-depth interviews as students reviewed pairs of visual prompts that could potentially be used as behavioral nudges.

The study found that student motivations when making decisions about course content and learning supports principally fell into three categories: learning, doing and performing and that all participants attributed their visual prompt preferences to personal motivations or self-perceptions as learners.

We acknowledge the limitations for external validity and generalizability of the findings in this study. The goal of this formative design research was not to assess the relationship between study habits and motivations and learning outcomes; rather, it was to provide insight to researchers and practitioners seeking to develop, test or employ nudges based on learner study habits. We also acknowledge the small sample size for Phase 2. The aim of Phase 2 was not to identify emergent themes through content analysis but to explore student reactions to nudges mapped to the Damgaard and Nielsen (2018) typology as part of investigating its salience in applications informed by Phase 1 learner study habits.

Insights from this study could not only be used to design engagement-focused interventions to be applied in education but also in sectors such as training or organizational development. Educators could incorporate the study’s findings to create more engaging learning environments or curricula, fostering active participation and improved learning outcomes and inform policies in education, public programs or workforce development by encouraging evidence-based engagement practices.

The motivation categories that emerged here – learning, doing and performing – are consistent with studies delving into motivational constructs in education like expectancy value theory, self-regulation and achievement orientation (Ames and Archer, 1988; Pintrich and De Groot, 1990; Wigfield, 1994) and can be leveraged to design interventions that increase engagement, which has been shown in previous work to be lower than hoped (Garbers et al., 2022) to support student educational outcomes.