EasyVis dashboards within the MLADs framework

Product or Programme · All products and programmes
Evidence · 3 claims (3 for) · 1 study (1 design), q2 · 0 of 1 report an effect size · 3 claims rest on one study

Description

EasyVis dashboards are teacher-facing learning-analytics dashboards developed for primary schools in three Swedish municipalities by integrating EdTech activity data with municipal attendance and grade data.

Components

Claims

• Teacher feedback during co-design directly produced four dashboard design changes: predictive alerts, navigation redesign, integrated attendance-performance view, and a Help tab [+M]
• A Random Forest Classifier embedded in the MLADs achieved an F1-score of 0.82 and AUC of 0.89 for course-completion-risk alerts under five-fold cross-validation [+M]
• Post-implementation teacher survey rated text clarity, labeling and visual components positively while flagging navigation consistency, missing warnings, hidden supplementary information, and unclear input fields [+M]

Related Products and Programmes

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Key Sources

• Zeynab (Artemis) Mohseni, Italo Masiello. (2026). Co-designing, developing, and implementing multiple learning analytics dashboards for data-driven decision-making in education: a design-based research approach. Education Tech Research Dev. https://doi.org/10.1007/s11423-025-10577-9

Page metadata

Field	Value
type	product
id	easyvis-dashboards-within-the-mlads-framework
title	EasyVis dashboards within the MLADs framework
description	EasyVis dashboards are teacher-facing learning-analytics dashboards developed for primary schools in three Swedish municipalities by integrating EdTech activity data with municipal attendance and grade data.
status	review
product_kind	software
generated	by process:settle-candidates on 2026-10-29
trust	unverified — no one has confirmed this page's content

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