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Ignacio Villagrán; Rocio Hernández; Gregory Schuit; Andrés Neyem; Javiera Fuentes; Loreto Larrondo; Elisa Margozzini; María T. Hurtado; Zoe Iriarte; Constanza Miranda; Julián Varas; Isabel Hilliger – Journal of Learning Analytics, 2024
Remote technology has been widely incorporated into health professions education. For procedural skills training, effective feedback and reflection processes are required. Consequently, supporting a self-regulated learning (SRL) approach with learning analytics dashboards (LADs) has proven beneficial in online environments. Despite the potential…
Descriptors: Feedback (Response), Independent Study, Skill Development, Learning Analytics
Yueqiao Jin; Vanessa Echeverria; Lixiang Yan; Linxuan Zhao; Riordan Alfredo; Yi-Shan Tsai; Dragan Gasevic; Roberto Martinez-Maldonado – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across…
Descriptors: Learning Analytics, Accountability, Ethics, Artificial Intelligence
Tomás Bautista-Godínez; Gerardo Castañeda-Garza; Ricardo Pérez Mora; Hector G. Ceballos; Verónica Luna de la Luz; J. Gerardo Moreno-Salinas; Irma Rocío Zavala-Sierra; Roberto Santos-Solórzano; Carlos Iván Moreno Arellano; Melchor Sánchez-Mendiola – Journal of Learning Analytics, 2024
The adoption of learning analytics (LA) in higher education institutions (HEIs) in Mexico is still at an early stage despite increasing global interest and advances in the field. The use of educational data remains a challenging puzzle for many universities, which strive to provide students, teachers, and institutional administrators with…
Descriptors: Foreign Countries, Learning Analytics, Universities, Program Implementation
Knight, David B.; Brozina, Cory; Novoselich, Brian – Journal of Learning Analytics, 2016
This paper investigates how first-year engineering undergraduates and their instructors describe the potential for learning analytics approaches to contribute to student success. Results of qualitative data collection in a first-year engineering course indicated that both students and instructors emphasized a preference for learning analytics…
Descriptors: Undergraduate Students, Engineering Education, College Faculty, Attitude Measures
Aghababyan, Ani; Martin, Taylor; Janisiewicz, Philip; Close, Kevin – Journal of Learning Analytics, 2016
Learning analytics is an emerging discipline and, as such, benefits from new tools and methodological approaches. This work reviews and summarizes our workshop on microgenetic data analysis techniques using R, held at the second annual Learning Analytics Summer Institute in Cambridge, Massachusetts, on 30 June 2014. Specifically, this paper…
Descriptors: Educational Research, Data Collection, Data Analysis, Workshops
Epp, Carrie Demmans; Phirangee, Krystle; Hewitt, Jim – Journal of Learning Analytics, 2017
Identifying which online behaviours and interactions are associated with student perceptions of being supported will enable a deeper understanding of how those activities contribute to learning experiences. Student language is one aspect of their interaction in need of greater exploration within discourse-based online learning environments. As a…
Descriptors: Student Behavior, Computer Mediated Communication, Form Classes (Languages), Language Usage
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