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Co-Developing an Easy-to-Use Learning Analytics Dashboard for Teachers in Primary/Secondary Education: A Human-Centered Design Approach
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (EdTechLnu;DISA;CSS)ORCID iD: 0000-0002-3297-0189
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). Linnaeus University, Faculty of Social Sciences, Department of Pedagogy and Learning. Linnaeus University, Linnaeus Knowledge Environments, Digital Transformations. (EdTechLnu;DISA;CSS)ORCID iD: 0000-0002-3738-7945
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (ISOVIS;DISA;CSS)ORCID iD: 0000-0002-2901-935X
2023 (English)In: Education Sciences, E-ISSN 2227-7102, Vol. 13, no 12, article id 1190Article in journal (Refereed) Published
Abstract [en]

Learning Analytics Dashboards (LADs) can help provide insights and inform pedagogical decisions by supporting the analysis of large amounts of educational data, obtained from sources such as Digital Learning Materials (DLMs). Extracting requirements is a crucial step in developing a LAD, as it helps identify the underlying design problem that needs to be addressed. In fact, determining the problem that requires a solution is one of the primary objectives of requirements extraction. Although there have been studies on the development of LADs for K12 education, these studies have not specifically emphasized the use of a Human-Centered Design (HCD) approach to better comprehend the teachers’ requirements and produce more stimulating insights. In this paper we apply prototyping, which is widely acknowledged as a successful way for rapidly implementing cost-effective designs and efficiently gathering stakeholder feedback, to elicit such requirements. We present a three-step HCD approach, involving a design cycle that employs paper and interactive prototypes to guide the systematic and effective design of LADs that truly meet teacher requirements in primary/secondary education, actively engaging them in the design process. We then conducted interviews and usability testing to co-design and develop a LAD that can be used in classroom’s everyday learning activities. Our results show that the visualizations of the interactive prototype were easily interpreted by the participants, verifying our initial goal of co-developing an easy-to-use LAD.

Place, publisher, year, edition, pages
MDPI, 2023. Vol. 13, no 12, article id 1190
Keywords [en]
learning analytics dashboard; human-centered design; paper prototype; interactive prototype; usability test; K12; educational data
National Category
Computer Systems
Research subject
Computer Science, Information and software visualization
Identifiers
URN: urn:nbn:se:lnu:diva-125814DOI: 10.3390/educsci13121190ISI: 001130760800001Scopus ID: 2-s2.0-85180651196OAI: oai:DiVA.org:lnu-125814DiVA, id: diva2:1815547
Available from: 2023-11-29 Created: 2023-11-29 Last updated: 2025-02-11Bibliographically approved
In thesis
1. Development of Visual Learning Analytic Tools to Explore Performance and Engagement of Students in Primary, Secondary, and Higher Education
Open this publication in new window or tab >>Development of Visual Learning Analytic Tools to Explore Performance and Engagement of Students in Primary, Secondary, and Higher Education
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Schools and educational institutions collect large amounts of data about students and their learning, including text, grades, quizzes, timestamps, and other activities. However, in primary and secondary education, this data is often dispersed across different digital platforms, lacking standardized methods for collection, processing, analysis, and presentation. These issues hinder teachers and students from making informed decisions or strategic and effective use of data. This presents a significant obstacle to progress in education and the effective development of Educational Technology (EdTech) products. Visual Learning Analytics (VLA) tools, also known as Learning Analytics Dashboards (LADs), are designed to visualize student data to support pedagogical decision-making. Despite their potential, the effectiveness of these tools remains limited. Addressing these challenges requires both technical solutions and thoughtful design considerations, as explored in Papers 1 through 5 of this thesis. Paper 1 examines the design aspects of VLA tools by evaluating higher education data and various visualization and Machine Learning (ML) techniques. Paper 2 provides broader insights into the VLA landscape through a systematic review, mapping key concepts and research gaps in VLA and emphasizing the potential of VLA tools to enhance pedagogical decisions and learning outcomes. Meanwhile, Paper 3 delves into a technical solution (data pipeline and data standard) considering a secure Swedish warehouse, SUNET. This includes a data standard for integrating educational data into SUNET, along with customized scripts to reformat, merge, and hash multiple student datasets. Papers 4 and 5 focus on design aspects, with Paper 4 discussing the proposed Human-Centered Design (HCD) approach involving teachers in co-designing a simple VLA tool. Paper 5 introduces a scenario-based framework for Multiple Learning Analytics Dashboards (MLADs) development, stressing user engagement for tailored LADs that facilitate informed decision-making in education. The dissertation offers a comprehensive approach to advancing VLA tools, integrating technical solutions with user-centric design principles. By addressing data integration challenges and involving users in tool development, these efforts aim to empower teachers in leveraging educational data for improved teaching and learning experiences.

Place, publisher, year, edition, pages
Växjö, Sweden: Linnaeus University Press, 2024. p. 98
Series
Linnaeus University Dissertations ; 532
Keywords
Visual learning analytics tool, learning analytics dashboard, systematic review, data standard, data management, human-centered design, scenario-based framework, intervention, educational data, primary education, higher education
National Category
Computer and Information Sciences Computer Sciences Human Computer Interaction
Research subject
Computer and Information Sciences Computer Science, Computer Science; Computer Science, Information and software visualization; Computer and Information Sciences Computer Science
Identifiers
urn:nbn:se:lnu:diva-131834 (URN)10.15626/LUD.532.2024 (DOI)9789180821766 (ISBN)9789180821773 (ISBN)
Public defence
2024-09-13, Weber, Hus K, Växjö, 10:00 (English)
Opponent
Supervisors
Available from: 2024-08-20 Created: 2024-08-15 Last updated: 2024-08-21Bibliographically approved

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Mohseni, ZeynabMasiello, ItaloMartins, Rafael Messias

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