Schools Are Using AI to Track Student Progress, But Evidence of Results Remains Unclear
A comprehensive review of visual learning analytics tools—software that uses charts and automated analysis to help teachers monitor student performance—found moderate improvements in learning outcomes, but significant gaps in the research limit confidence in their effectiveness. For EdTech vendors and school administrators considering these platforms, the findings suggest promising potential alongside a cautionary tale about adoption ahead of solid evidence.
Originaltitel: Visual Learning Analytics for Educational Interventions in Primary and Secondary Schools: A Scoping Review
<p>Visual Learning Analytics (VLA) uses analytics to monitor and assess educational data by combining visual and automated analysis to provide educational explanations. Such tools could aid teachers in primary and secondary schools in making pedagogical decisions, however, the evidence of their effectiveness and benefits is still limited. With this scoping review, we provide a comprehensive overview of related research on proposed VLA methods, as well as identifying any gaps in the literature that could assist in describing new and helpful directions to the field. This review searched all relevant articles in five accessible databases — Scopus, Web of Science, ERIC, ACM, and IEEE Xplore — using 40 keywords. These studies were mapped, categorized, and summarized based on their objectives, the collected data, the intervention approaches employed, and the results obtained. The results determined what affordances the VLA tools allowed, what kind of visualizations were used to inform teachers and students, and, more importantly, positive evidence of educational interventions. We conclude that there are moderate-to-clear learning improvements within the limit of the studies’ interventions to support the use of VLA tools. More systematic research is needed to determine whether any learning gains are translated into long-term improvements.</p>