Learning analytics dashboard: a tool for providing actionable insights to learners

Abstract

This study investigates current approaches to learning analytics (LA) dashboarding while highlighting challenges faced by education providers in their operationalization. We analyze recent dashboards for their ability to provide actionable insights which promote informed responses by learners in making adjustments to their learning habits. Our study finds that most LA dashboards merely employ surface-level descriptive analytics, while only few go beyond and use predictive analytics. In response to the identified gaps in recently published dashboards, we propose a state-of-the-art dashboard that not only leverages descriptive analytics components, but also integrates machine learning in a way that enables both predictive and prescriptive analytics. We demonstrate how emerging analytics tools can be used in order to enable learners to adequately interpret the predictive model behavior, and more specifically to understand how a predictive model arrives at a given prediction. We highlight how these capabilities build trust and satisfy emerging regulatory requirements surrounding predictive analytics. Additionally, we show how data-driven prescriptive analytics can be deployed within dashboards in order to provide concrete advice to the learners, and thereby increase the likelihood of triggering behavioral changes. Our proposed dashboard is the first of its kind in terms of breadth of analytics that it integrates, and is currently deployed for trials at a higher education institution.

Reference frames for learning analytics dashboards: The progress and social reference frame and occupational self‐efficacy

“…However, it is essential to consider the evolving nature and potential of LADs. Research by Susnjak et al (2022) propose advancing LADs from descriptive to predictive and prescriptive analytics to enhance self‐reflection and guide learners more effectively.…”

How Students Use Learning Analytics Dashboards in Higher Education: A Learning Performance Perspective

“…Importantly, the authors demonstrated that their LAD helped improve learning effectiveness. Susnjak et al (2022) analyzed recent LADs for their ability to provide actionable insights using a literature review and proposed an LAD that addressed many of the shortcomings. Their LAD proposed integrated descriptive, predictive, and data-driven prescriptive analytics into one display.…”

“…These studies either focused on improving teaching and learning (e.g., Schwendimann et al, 2016), or verifying an LAD's effectiveness in comprehension through the educational practice (Wang & Han, 2021). Susnjak et al (2022) reviewed 17 dashboards targeting learners and instructors. The authors observed that all LADs incorporated interface-level descriptive analytics, usually in the form of graphical displays depicting students' own information and comparisons with others.…”

Advancing from Prediction to Prescription: Strategies for Proactively and Thoughtfully Addressing Students' Needs

“…Research suggests that the use of predictive models can be a useful approach for determining which students to prioritize (Hall et al, 2021;Susnjak et al, 2022;Yu et al, 2020). Institutions are now refining their student success approaches even more by moving from using data to predict which students need assistance to using data to also prescribe specific interventions (Chen & Upah, 2018;Thompson et al, 2018).…”