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Zeynab Mohseni; Italo Masiello; Rafael M. Martins; Susanna Nordmark – Journal of Learning Analytics, 2024
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…
Descriptors: Learning Analytics, Visual Learning, Visualization, Intervention
Stanislav Pozdniakov; Jonathan Brazil; Mehrnoush Mohammadi; Mollie Dollinger; Shazia Sadiq; Hassan Khosravi – Journal of Learning Analytics, 2025
Engaging students in creating high-quality novel content, such as educational resources, promotes deep and higher-order learning. However, students often lack the necessary training or knowledge to produce such content. To address this gap, this paper explores the potential of incorporating generative AI (GenAI) to review students' work and…
Descriptors: Student Evaluation, Artificial Intelligence, Student Developed Materials, Feedback (Response)
Shihui Feng; David Gibson; Dragan Gaševic – Journal of Learning Analytics, 2025
Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Student Role, Learning Analytics
Dollinger, Mollie; Liu, Danny; Arthars, Natasha; Lodge, Jason M. – Journal of Learning Analytics, 2019
The value of technology lies not only with the service or functionality of the tool, but also with its subsequent value to the people who use it. New learning analytics (LA) software and platforms for capturing data and improving student learning are frequently introduced; however, they suffer from issues of adoption and continued usage by…
Descriptors: Learning Analytics, Foreign Countries, Cooperation, Stakeholders
Munguia, Pablo; Brennan, Amelia – Journal of Learning Analytics, 2020
No course exists in isolation, so examining student progression through courses within a broader program context is an important step in integrating course-level and program-level analytics. Integration in this manner allows us to see the impact of course-level changes to the program, as well as identify points in the program structure where…
Descriptors: Learning Analytics, Courses, College Programs, Foreign Countries
Trezise, Kelly; Ryan, Tracii; de Barba, Paula; Kennedy, Gregor – Journal of Learning Analytics, 2019
Rural teachers and educators are increasingly called upon to build partnerships with families who use languages other than English in the home (US DOE, 2016). This is equally true for rural schools, where the number of multilingual families is small, and the language and cultural backgrounds of students differs from those of school. This article…
Descriptors: College Students, Cheating, Identification, Learning Analytics
Vigentini, Lorenzo; Swibel, Brad; Hasler, Garth – Journal of Learning Analytics, 2022
While Learning Analytics (LA) have gained momentum in higher education, there are still few examples of application in the school sector. Even fewer cases are reported of systematic, organizational adoption to drive the support of student learning trajectories that includes teachers, pastoral leaders, and academic managers. This paper presents one…
Descriptors: Learning Analytics, Educational Improvement, Secondary School Students, Learning Management Systems
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
Harrison, Scott; Villano, Renato; Lynch, Grace; Chen, George – Journal of Learning Analytics, 2021
Early alert systems (EAS) are an important technological tool to help manage and improve student retention. Data spanning 16,091 students over 156 weeks was collected from a regionally based university in Australia to explore various microeconometric approaches that establish links between EAS and student retention outcomes. Controlling for…
Descriptors: Learning Analytics, School Holding Power, Integrated Learning Systems, Microeconomics
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
Iraj, Hamideh; Fudge, Anthea; Khan, Huda; Faulkner, Margaret; Pardo, Abelardo; Kovanovic, Vitomir – Journal of Learning Analytics, 2021
One of the major factors affecting student learning is feedback. Although the importance of feedback has been recognized in educational institutions, dramatic changes--such as bigger class sizes and a more diverse student population--challenged the provision of effective feedback. In light of these changes, educators have increasingly been using…
Descriptors: Learner Engagement, Learning Analytics, Feedback (Response), Class Size
Matcha, Wannisa; Gasevic, Dragan; Uzir, Nora'ayu Ahmad; Jovanovic, Jelena; Pardo, Abelardo; Lim, Lisa; Maldonado-Mahauad, Jorge; Gentili, Sheridan; Perez-Sanagustin, Mar; Tsai, Yi-Shan – Journal of Learning Analytics, 2020
Generalizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning…
Descriptors: Learning Analytics, Learning Strategies, Instructional Design, Delivery Systems