The Adoption of Learning Analytics in Blended Learning Environments: An Exploratory Study in Singapore

In the aftermath of COVID-19, blended learning (BL) has emerged as the dominant mode of learning. With our university transitioning to a new campus where BL is expected to seamlessly integrate into its physical design, it is anticipated to become an indispensable component of the student experience. However, there appears to be a paucity of research into students’ perceptions of digital support and satisfaction with interactions within BLEs at higher education, especially in the post-COVID-19 era. In this paper, we utilize the learning analytics (LA) cycle as an overarching framework to shape our study’s methodology. Our aim was to examine students’ perceptions of digital relatedness support (DRS) and satisfaction with learner-technology interaction (SLTI) across three modules (n = 305) at our university. To achieve this objective, we conducted a cross-sectional survey complemented by focus group discussions (FGDs). Over 50% of respondents had positive perceptions of DRS and SLTI. In addition, statistically significant differences were observed between two pairs and one pair of modules for DRS and SLTI, respectively. The FGD data provided some possible reasons for the differences in DRS and SLTI scores across modules. This paper concludes with some recommendations to enhance DRS and SLTI.