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Showing 1 to 15 of 25 results Save | Export
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Wannapon Suraworachet; Qi Zhou; Mutlu Cukurova – Journal of Computer Assisted Learning, 2025
Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real-world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback…
Descriptors: Graduate Students, Student Attitudes, Artificial Intelligence, Cooperative Learning
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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
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Karaoglan Yilmaz, Fatma Gizem – Journal of Computing in Higher Education, 2022
This research examined the effect of learning analytics (LA) on students' metacognitive awareness and academic achievement in an online learning environment. In this study, a mixed methods approach was used and applied as a quasi-experimental design. The results of LA were sent to students weekly in LA group (experimental group) via learning…
Descriptors: Learning Analytics, Feedback (Response), Metacognition, Academic Achievement
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Conrad Borchers; Cindy Peng; Qianru Lyu; Paulo F. Carvalho; Kenneth R. Koedinger; Vincent Aleven – Grantee Submission, 2025
Many AIED systems support self-regulated learning, yet, support for setting and achieving practice goals has received little attention. We examine how middle school students respond to system-recommended practice goals, building on the success of similar data-driven recommendations in other domains. We introduce an adaptive dashboard in an…
Descriptors: Goal Orientation, Student Attitudes, Self Control, Intelligent Tutoring Systems
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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
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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)
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Damien S. Fleur; Max Marshall; Miguel Pieters; Natasa Brouwer; Gerrit Oomens; Angelos Konstantinidis; Koos Winnips; Sylvia Moes; Wouter van den Bos; Bert Bredeweg; Erwin A. van Vliet – Journal of Learning Analytics, 2023
Personalized feedback is important for the learning process, but it is time consuming and particularly problematic in large-scale courses. While automatic feedback may help for self-regulated learning, not all forms of feedback are effective. Social comparison offers powerful feedback but is often loosely designed. We propose that intertwining…
Descriptors: Feedback (Response), Peer Influence, Learning Analytics, Undergraduate Students
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Ouyang, Fan; Li, Xu; Jiao, Pengcheng; Peng, Xian; Chen, Wenzhi – International Journal of Distance Education Technologies, 2021
The design of social learning analytics (SLA) tools has become a practical means to make available learning information with a goal to improve students' regulation, reflection, and engagement in online learning. This design-based research uses the multi-method analytics to iteratively design, implement, and modify the SLA tool that makes available…
Descriptors: Learning Analytics, Socialization, Electronic Learning, Computer Mediated Communication
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Grace Leah Akinyi; Robert Oboko; Lawrence Muchemi – Electronic Journal of e-Learning, 2024
The future of university learning in Sub-Saharan Africa has become increasingly digitally transformed by both e-Learning, and learning analytics, post-COVID-19 pandemic. Learning analytics intervention is critical for effective support of socially-shared regulated learning skills, which are crucial for twenty-first-century e-Learners.…
Descriptors: Electronic Learning, Student Attitudes, Learning Analytics, Feedback (Response)
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Esnaashari, Shadi; Gardner, Lesley A.; Arthanari, Tiru S.; Rehm, Michael – Journal of Computer Assisted Learning, 2023
Background: It is vital to understand students' Self-Regulatory Learning (SRL) processes, especially in Blended Learning (BL), when students need to be more autonomous in their learning process. In studying SRL, most researchers have followed a variable-oriented approach. Moreover, little has been known about the unfolding process of students' SRL…
Descriptors: Metacognition, Student Attitudes, Learning Strategies, Questionnaires
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Flora Ji-Yoon Jin; Bhagya Maheshi; Roberto Martinez-Maldonado; Dragan Gasevic; Yi-Shan Tsai – Journal of Learning Analytics, 2024
Feedback is essential in learning. The emerging concept of feedback literacy underscores the skills students require for effective use of feedback. This highlights students' responsibilities in the feedback process. Yet, there is currently a lack of mechanisms to understand how students make sense of feedback and whether they act on it. This gap…
Descriptors: Scaffolding (Teaching Technique), Feedback (Response), Learning Analytics, Literacy
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Karmijn van de Oudeweetering; Jeremy Knox; Mathias Decuypere – Learning, Media and Technology, 2024
This paper examines the enactment of feedback in Massive Open Online Courses (MOOCs), focusing on analytics dashboards. Building on scholarship that recognizes data practices as entangled and 'messy', the paper problematizes the model of the feedback loop that assumes that analytics dashboards 'feed back' data to instructors and/or learners…
Descriptors: MOOCs, Learning Analytics, Instructional Design, Student Role
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Karaoglan Yilmaz, Fatma Gizem; Yilmaz, Ramazan – Technology, Knowledge and Learning, 2020
There is a growing interest in the use of learning analytics in higher education institutions. Learning analytics also appear to have the potential to be used to provide personalized feedback and support in online learning. However, when the literature is examined, the use of learning analytics for this purpose appears as a gap to be investigated.…
Descriptors: Student Attitudes, Individualized Instruction, Electronic Learning, Feedback (Response)
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Arjan J. F. Kok; Lex Bijlsma; Cornelis Huizing; Ruurd Kuiper; Harrie Passier – Informatics in Education, 2024
This paper presents the first experiences of the use of an online open-source repository with programming exercises. The repository is independent of any specific teaching approach. Students can search for and select an exercise that trains the programming concepts that they want to train and that only uses the programming concepts they already…
Descriptors: Programming Languages, Computer Science Education, Open Source Technology, Teaching Methods
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Lixiang Yan; Vanessa Echeverria; Yueqiao Jin; Gloria Fernandez-Nieto; Linxuan Zhao; Xinyu Li; Riordan Alfredo; Zachari Swiecki; Dragan Gaševic; Roberto Martinez-Maldonado – British Journal of Educational Technology, 2024
Multimodal learning analytics (MMLA) offers the potential to provide evidence-based insights into complex learning phenomena such as collaborative learning. Yet, few MMLA applications have closed the learning analytics loop by being evaluated in real-world educational settings. This study evaluates the effectiveness of an MMLA solution in…
Descriptors: Learning Analytics, Cooperative Learning, Longitudinal Studies, Allied Health Occupations Education
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