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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
Wollny, Sebastian; Di Mitri, Daniele; Jivet, Ioana; Muñoz-Merino, Pedro; Scheffel, Maren; Schneider, Jan; Tsai, Yi-Shan; Whitelock-Wainwright, Alexander; Gaševic, Dragan; Drachsler, Hendrik – Journal of Computer Assisted Learning, 2023
Background: Learning Analytics (LA) is an emerging field concerned with measuring, collecting, and analysing data about learners and their contexts to gain insights into learning processes. As the technology of Learning Analytics is evolving, many systems are being implemented. In this context, it is essential to understand stakeholders'…
Descriptors: Foreign Countries, College Students, Learning Analytics, Expectation
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
Mangaroska, Katerina; Martinez-Maldonado, Roberto; Vesin, Boban; Gaševic, Dragan – Journal of Computer Assisted Learning, 2021
Multimodal data have the potential to explore emerging learning practices that extend human cognitive capacities. A critical issue stretching in many multimodal learning analytics (MLA) systems and studies is the current focus aimed at supporting researchers to model learner behaviours, rather than directly supporting learners. Moreover, many MLA…
Descriptors: Computer Science Education, Student Attitudes, Learning Modalities, Learning Analytics
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
Ameloot, Elise; Rotsaert, Tijs; Schellens, Tammy – Journal of Computer Assisted Learning, 2022
Background: Although blended learning (BL) has multiple educational prospects, it also poses challenges such as keeping students motivated. Objectives: This study investigates students' perceptions of how learning analytics (LA) can be used to support the design of a BL environment in order to promote students' basic need for relatedness, which is…
Descriptors: Learning Analytics, Blended Learning, Student Attitudes, Need Gratification
Whitelock-Wainwright, Alexander; Gaševic, Dragan; Tejeiro, Ricardo; Tsai, Yi-Shan; Bennett, Kate – Journal of Computer Assisted Learning, 2019
Student engagement within the development of learning analytics services in Higher Education is an important challenge to address. Despite calls for greater inclusion of stakeholders, there still remains only a small number of investigations into students' beliefs and expectations towards learning analytics services. Therefore, this paper presents…
Descriptors: Expectation, Learning Analytics, Questionnaires, College Students
Luzhen Tang; Kejie Shen; Huixiao Le; Yuan Shen; Shufang Tan; Yueying Zhao; Torsten Juelich; Xinyu Li; Dragan Gaševic; Yizhou Fan – Journal of Computer Assisted Learning, 2024
Background: Learners' writing skills are critical to their academic and professional development. Previous studies have shown that learners' self-assessment during writing is essential for assessing their writing products and monitoring their writing processes. However, conducting practical self-assessments of writing remains challenging for…
Descriptors: Self Evaluation (Individuals), Formative Evaluation, Writing Assignments, Writing Skills
Alam, Md. I.; Malone, Lauren; Nadolny, Larysa; Brown, Michael; Cervato, Cinzia – Journal of Computer Assisted Learning, 2023
Background: The substantial growth in gamification research has connected gamified learning to enhanced engagement, improved performance, and greater motivation. Similar to gamification, personalized learning analytics dashboards can enhance student engagement. Objectives: This study explores the student experiences and academic achievements using…
Descriptors: Academic Achievement, Game Based Learning, Introductory Courses, STEM Education

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