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Learning analytics (LA) can be an effective support for self-regulation of higher education students. Supporting different students on their academic paths requires considering students' self-efficacy beliefs and data-literacy skills as well as their varying uses and interpretations of LA. In this quasi-experimental study, we collected quantitative survey data on higher education students (N = 105) with and without access to a student-facing LA dashboard designed to support students on an academic path level. We collected data on students' perceived support for study planning and monitoring at three timepoints during one academic year. Utilizing latent growth curve modeling, the study investigated how students with different self-efficacy beliefs and data-literacy skills perceive receiving self-regulation support from LA throughout an academic year compared to peers with only regular digital tools. Our results showed that students with access to the LA dashboard reported a larger increase in perceived support compared to peers with access to only regular digital tools. Students with high data-literacy skills perceived receiving more support from LA compared to peers with low data-literacy. Students' self-efficacy beliefs did not significantly impact the extent of perceived support from LA. The results highlight the ethical risk of complex digital solutions, which, over time, put less technology-savvy students at a greater disadvantage and mainly benefit already higher-skilled students. The results strengthen current understanding on how LA supports higher education students on their academic paths but call for further investigation into ways of fostering students' data-literacy skills to maximize the support and overcome equity concerns.
Kaveri et al. (2025) studied this question.