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Co-designing, developing, and implementing multiple learning analytics dashboards for data-driven decision-making in education: a design-based research approach
Valladolid University, Spain.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Linnaeus University, Linnaeus Knowledge Environments, Digital Transformations.ORCID iD: 0000-0002-3738-7945
2026 (English)In: Educational technology research and development, ISSN 1042-1629, E-ISSN 1556-6501, Vol. 74, p. 517-548Article in journal (Refereed) Published
Abstract [en]

This research investigates the design, development and implementation of Multiple Learning Analytics Dashboards (MLADs) with the goal of enhancing data-driven decision-making among teachers in primary education. The study presents a Design-Based Research (DBR) approach to ensure the iterative development and refinement of MLADs through collaboration with educational professionals. The research involved four key steps in the presented DBR approach: 1) identifying the requirements through stakeholder interviews; 2) generating design ideas through brainstorming sessions and prototyping; 3) collaboratively designing and developing MLADs and conducting usability testing to gather feedback; and 4) implementing the MLADs in real-world educational settings. This paper outlines the research methodology, the participants involved, and the progress made toward developing these Learning Analytics Dashboards (LADs). The outcomes highlight the creation of tailored MLADs for teachers across multiple municipalities, as well as the lessons learned from real-world implementation. Additionally, we analyze user feedback from teachers regarding the dashboard's clarity, navigation, functionality, and design, providing a comprehensive view of the dashboard's usability and areas for future enhancement.

Place, publisher, year, edition, pages
Springer Nature, 2026. Vol. 74, p. 517-548
Keywords [en]
design-based research, learning analytics dashboards, primary education, co-design, user-centered design, data visualization, learning analytics, easyvis
National Category
Human Computer Interaction Computer Sciences
Identifiers
URN: urn:nbn:se:lnu:diva-143800DOI: 10.1007/s11423-025-10577-9ISI: 001629294800001Scopus ID: 2-s2.0-105023902693OAI: oai:DiVA.org:lnu-143800DiVA, id: diva2:2024663
Available from: 2025-12-30 Created: 2025-12-30 Last updated: 2026-05-11Bibliographically approved

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Masiello, Italo

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