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Christothea Herodotou; Sagun Shrestha; Catherine Comfort; Heshan Andrews; Paul Mulholland; Vaclav Bayer; Claire Maguire; John Lee; Miriam Fernandez – Journal of Learning Analytics, 2025
In this paper, we explore the design of a student-facing dashboard for online and distance learning with a focus on capturing and addressing specific learning needs. A participatory process involving 20 students was employed, which included a screening questionnaire and focus group discussions. The selection of data points to be displayed on the…
Descriptors: Electronic Learning, Distance Education, Student Attitudes, Educational Technology
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Xavier Ochoa; Xiaomeng Huang; Yuli Shao – Journal of Learning Analytics, 2025
Generative AI (GenAI) has the potential to revolutionize the analysis of educational data, significantly impacting learning analytics (LA). This study explores the capability of non-experts, including administrators, instructors, and students, to effectively use GenAI for descriptive LA tasks without requiring specialized knowledge in data…
Descriptors: Learning Analytics, Artificial Intelligence, Computer Software, Scores
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Muslim, Arham; Chatti, Mohamed Amine; Bashir, Muhammad Bassim; Barrios Varela, Oscar Eduardo; Schroeder, Ulrik – Journal of Learning Analytics, 2018
Open Learning Analytics (OLA) is an emerging concept in the field of Learning Analytics (LA). It deals with learning data collected from multiple environments and contexts, analyzed with a wide range of analytics methods to address the requirements of different stakeholders. Due to this diversity in different dimensions of OLA, the LA developers…
Descriptors: Data Analysis, Learning, Models, Design
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Stanislav Pozdniakov; Roberto Martinez-Maldonado; Yi-Shan Tsai; Vanessa Echeverria; Zachari Swiecki; Dragan Gaševic – Journal of Learning Analytics, 2025
Recent research on learning analytics dashboards has focused on designing user interfaces that offer various forms of "visualization guidance" (often referring to notions such as "data storytelling" or "narrative visualization") to teachers (e.g., emphasizing data points or trends with colour and adding annotations),…
Descriptors: Visual Aids, Learning Analytics, Technological Literacy, Pedagogical Content Knowledge
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Campos, Fabio C.; Ahn, June; DiGiacomo, Daniela K.; Nguyen, Ha; Hays, Maria – Journal of Learning Analytics, 2021
With the spread of learning analytics (LA) dashboards in K-12 schools, educators are increasingly expected to make sense of data to inform instruction. However, numerous features of school settings, such as specialized vantage points of educators, may lead to different ways of looking at data. This observation motivates the need to carefully…
Descriptors: Middle School Teachers, Mathematics Teachers, Learning Analytics, Comprehension
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Khosravi, Hassan; Shabaninejad, Shiva; Bakharia, Aneesha; Sadiq, Shazia; Indulska, Marta; Gasevic, Dragan – Journal of Learning Analytics, 2021
Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…
Descriptors: Learning Analytics, Visual Aids, Artificial Intelligence, Information Retrieval
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Echeverria, Vanessa; Martinez-Maldonado, Roberto; Shum, Simon Buckingham; Chiluiza, Katherine; Granda, Roger; Conati, Christina – Journal of Learning Analytics, 2018
From a human-centred computing perspective, supporting the interpretation of educational dashboards and visualizations by the people intended to use them exposes critical design challenges that may often be trivialized. Empirical evidence already shows that "usable" visualizations are not necessarily effective from an educational…
Descriptors: Story Telling, Visual Learning, Data Analysis, Visual Aids
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Martinez-Maldonado, Roberto; Pardo, Abelardo; Mirriahi, Negin; Yacef, Kalina; Kay, Judy; Clayphan, Andrew – Journal of Learning Analytics, 2015
Designing, validating, and deploying learning analytics tools for instructors or students is a challenge that requires techniques and methods from different disciplines, such as software engineering, human-computer interaction, computer graphics, educational design, and psychology. Whilst each has established its own design methodologies, we now…
Descriptors: Data Analysis, Learning, Design, Validity
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Charleer, Sven; Klerkx, Joris; Duval, Erik – Journal of Learning Analytics, 2014
This article explores how information visualization techniques can be applied to learning analytics data to help teachers and students deal with the abundance of learner traces. We also investigate how the affordances of large interactive surfaces can facilitate a collaborative sense-making environment for multiple students and teachers to explore…
Descriptors: Information Management, Information Utilization, Student Records, Progress Monitoring
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Nagy, Robin – Journal of Learning Analytics, 2016
There is an urgent need for our educational system to shift assessment regimes from a narrow, high-stakes focus on grades, to more holistic definitions that value the qualities that lifelong learners will need. The challenge for learning analytics in this context is to deliver actionable assessments of these hard-to-quantify qualities, valued by…
Descriptors: Learner Engagement, Student Evaluation, Secondary School Students, Visual Aids