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David Williamson Shaffer; Yeyu Wang; Andrew Ruis – Journal of Learning Analytics, 2025
Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…
Descriptors: Learning Processes, Learning Analytics, Models, Data
Shiqi Liu; Sannyuya Liu; Xian Peng; Jianwen Sun; Zhi Liu – Journal of Educational Computing Research, 2025
Forum discussions in Massive Open Online Courses (MOOCs) play a crucial role in promoting learning engagement and academic achievement. In particular, discussion topics significantly influence learners' emotional and cognitive engagement. However, the complex interrelationships among these factors remain underexplored. This study introduces an…
Descriptors: MOOCs, Difficulty Level, Learner Engagement, Academic Achievement
Mthokozisi Masumbika Ncube; Patrick Ngulube – Discover Education, 2025
Despite the increasing interest in data analytics applications within postgraduate education research, there remains a significant gap in research dedicated to exploring mixed methods research for such investigations. This study undertook to bridge this gap by exploring the application and use of mixed methods research to examine data analytics…
Descriptors: Data Analysis, Graduate Students, Educational Research, Mixed Methods Research
Caitlin Snyder; Clayton Cohn; Joyce Horn Fonteles; Gautam Biswas – Grantee Submission, 2025
Recently, there has been a surge in developing curricula and tools that integrate computing (C) into Science, Technology, Engineering, and Math (STEM) programs. These environments foster authentic problem-solving while facilitating students' concurrent learning of STEM+C content. In our study, we analyzed students' behaviors as they worked in…
Descriptors: Learning Analytics, Problem Solving, STEM Education, Computation
Flora Ji-Yoon Jin; Debarshi Nath; Rui Guan; Tongguang Li; Xinyu Li; Rafael Ferreira Mello; Luiz Rodrigues; Cleon Pereira Junior; Heba Abuzayyad-Nuseibeh; Mladen Rakovic; Roberto Martinez-Maldonado; Dragan Gaševic; Yi-Shan Tsai – Journal of Computer Assisted Learning, 2025
Background: A key skill for self-regulated learners is the ability to critically interpret and act on feedback--key components of feedback literacy. Yet, the connection between feedback literacy and self-regulated learning (SRL) remains underexplored, particularly in terms of how different levels of feedback literacy influence SRL processes in…
Descriptors: Independent Study, Learning Analytics, Feedback (Response), Literacy
Markus W. H. Spitzer; Lisa Bardach; Eileen Richter; Younes Strittmatter; Korbinian Moeller – Journal of Computer Assisted Learning, 2025
Background: Many students face difficulties with algebra. At the same time, it has been observed that fraction understanding predicts achievements in algebra; hence, gaining a better understanding of how algebra understanding builds on fraction understanding is an important goal for research and educational practice. Objectives: However, a wide…
Descriptors: Psychological Patterns, Network Analysis, Fractions, Algebra
Mengke Wang; Taotao Long; Na Li; Yawen Shi; Zengzhao Chen – Education and Information Technologies, 2025
Feedback plays an indispensable role in pre-service teachers' microteaching practice. It provides essential information about their microteaching performance, which is of great significance in their reflection and improvement. As AI and teaching analytics advance, feedback is no longer exclusively human-generated. AI technologies are increasingly…
Descriptors: Feedback (Response), Preservice Teachers, Microteaching, Reflection
Emine Cabi; Hacer Türkoglu – International Review of Research in Open and Distributed Learning, 2025
Recent advancements in educational technology have enabled teachers to use learning analytics (LA) and flipped classrooms. The present study investigated the impact of a LA-based feedback system on students' academic achievement and self-regulated learning (SRL) in a flipped learning (FL) environment. The study used a pretest-posttest control…
Descriptors: Learning Analytics, Feedback (Response), Academic Achievement, Independent Study
Flora Ji-Yoon Jin; Bhagya Maheshi; Wenhua Lai; Yuheng Li; Danijela Gasevic; Guanliang Chen; Nicola Charwat; Philip Wing Keung Chan; Roberto Martinez-Maldonado; Dragan Gaševic; Yi-Shan Tsai – Journal of Learning Analytics, 2025
This paper explores the integration of generative AI (GenAI) in the feedback process in higher education through a learning analytics (LA) tool, examined from a feedback literacy perspective. Feedback literacy refers to students' ability to understand, evaluate, and apply feedback effectively to improve their learning, which is crucial for…
Descriptors: College Students, Student Attitudes, Artificial Intelligence, Learning Analytics
Tornike Giorgashvili; Ioana Jivet; Cordula Artelt; Daniel Biedermann; Daniel Bengs; Frank Goldhammer; Carolin Hahnel; Julia Mendzheritskaya; Julia Mordel; Monica Onofrei; Marc Winter; Ilka Wolter; Holger Horz; Hendrik Drachsler – Journal of Computer Assisted Learning, 2025
Background: Learning analytics dashboards (LAD) have been developed as feedback tools to help students self-regulate their learning (SRL) by using the large amounts of data generated by online learning platforms. Despite extensive research on LAD design, there remains a gap in understanding how learners make sense of information visualised on LADs…
Descriptors: Field Studies, Student Reaction, Feedback (Response), Learning Analytics
Jyoti Prakash Meher; Rajib Mall – IEEE Transactions on Education, 2025
Contribution: This article suggests a novel method for diagnosing a learner's cognitive proficiency using deep neural networks (DNNs) based on her answers to a series of questions. The outcome of the forecast can be used for adaptive assistance. Background: Often a learner spends considerable amounts of time in attempting questions on the concepts…
Descriptors: Cognitive Ability, Assistive Technology, Adaptive Testing, Computer Assisted Testing
S. Asha; V. P. Joshith – Journal of Educational Technology Systems, 2025
Learning analytics (LA) has become a critical field for transforming educational practices through data-driven insights. This study presents a comprehensive bibliometric analysis of LA research in higher education from 2013 to 2023, utilizing the Scientific Procedures and Rationales for Systematic Literature Review (SPAR-4-SLR) approach. By…
Descriptors: Bibliometrics, Learning Analytics, Educational Change, Educational Practices
Wen Chiang Lim; Neil T. Heffernan; Adam Sales – Grantee Submission, 2025
As online learning platforms become more popular and deeply integrated into education, understanding their effectiveness and what drives that effectiveness becomes increasingly important. While there is extensive prior research illustrating the benefits of intelligent tutoring systems (ITS) for student learning, there is comparatively less focus…
Descriptors: Intelligent Tutoring Systems, Computer Uses in Education, Prompting, Reports
Vanessa Echeverria; Gloria Fernandez Nieto; Linxuan Zhao; Evelyn Palominos; Namrata Srivastava; Dragan Gaševic; Viktoria Pammer-Schindler; Roberto Martinez-Maldonado – Journal of Computer Assisted Learning, 2025
Background: Dashboards play a prominent role in learning analytics (LA) research. In collaboration activities, dashboards can show traces of team participation. They are often evaluated based on students' perceived satisfaction and engagement with the dashboard. However, there is a notable methodological gap in understanding how these dashboards…
Descriptors: Learning Analytics, Educational Technology, Student Attitudes, Reflection
Marijn Martens; Ralf De Wolf; Lieven De Marez – Technology, Knowledge and Learning, 2025
Algorithmic decision-making systems such as Learning Analytics (LA) are widely used in an educational setting ranging from kindergarten to university. Most research focuses on how LA is used and adopted by teachers. However, the perspective of students and parents who experience the (in)direct consequences of these systems is underexplored. This…
Descriptors: Algorithms, Decision Making, Learning Analytics, Secondary School Students