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Maarten Sluijs; Uwe Matzat – Journal of Computer Assisted Learning, 2024
Background: Technological innovations such as Learning Management Systems (LMS) are becoming more and more prevalent in the learning environments of students. Distilling and acting on knowledge gathered from these systems, the field known as learning analytics, allows educators to hone their craft and support students more effectively by providing…
Descriptors: Time Management, Learning Analytics, Learning Management Systems, Predictive Measurement
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Sahin Kizil, Aysel – Journal of Computer Assisted Learning, 2023
Background: Data-driven learning (DDL) has been regarded as one of the promising approaches that could effectively enhance writing performance of English as a foreign language (EFL) learners. Although extensive research has been conducted on the use of DDL in developing various aspects of writing skill, there exist only few studies to date that…
Descriptors: Learning Analytics, English (Second Language), Second Language Learning, Second Language Instruction
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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
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Zamecnik, Andrew; Kovanovíc, Vitomir; Joksimovíc, Srécko; Grossmann, Georg; Ladjal, Djazia; Marshall, Ruth; Pardo, Abelardo – Journal of Computer Assisted Learning, 2023
Background: Maintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work-integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal…
Descriptors: Data Use, Group Dynamics, College Students, Cooperative Learning
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Cheng, Ching-I. – Journal of Computer Assisted Learning, 2023
Background: Taiwan's higher education institutions prioritize interdisciplinary knowledge and cultural competence in cultural design, emphasizing the value of immersion in the local environment to develop cultural competence. However, challenges arise from the disappearance of traditional local lifestyles and limitations of traditional outdoor…
Descriptors: Foreign Countries, Learning Analytics, Handheld Devices, Computer Oriented Programs
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Chen, Si; Ouyang, Fan; Jiao, Pengcheng – Journal of Computer Assisted Learning, 2022
Background: Online Collaborative Writing (OCW) has been reported to be useful to improve writing quality in higher education. However, challenges emerge during the collaborative processes, mainly centering on how to sustain active interactions and communications in order to complete a high quality of writing. Objectives: Using the design-based…
Descriptors: Learner Engagement, Computer Mediated Communication, Collaborative Writing, Cooperative Learning
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Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michail – Journal of Computer Assisted Learning, 2022
Background: Problem-solving is a multidimensional and dynamic process that requires and interlinks cognitive, metacognitive, and affective dimensions of learning. However, current approaches practiced in computing education research (CER) are not sufficient to capture information beyond the basic programming process data (i.e., IDE-log data).…
Descriptors: Cognitive Processes, Psychological Patterns, Problem Solving, Programming
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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
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Sidi, Yael; Blau, Ina; Shamir-Inbal, Tamar – Journal of Computer Assisted Learning, 2022
Background: Hyper-video technology allows reflection on learning materials by writing personal notes and by interactions with lecturers and peers through shared posts and replies. While research shows that integrating hyper-videos in educational systems can promote the learning processes and outcomes, an open question remains regarding its actual…
Descriptors: Active Learning, Cooperative Learning, College Students, Documentation
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Han, Feifei; Pardo, Abelardo; Ellis, Robert A. – Journal of Computer Assisted Learning, 2020
This study examines the extent to which the learning orientations identified by student self-reports and the observation of their online learning events were related to each other and to their academic performance. The participants were 322 first-year engineering undergraduates, who were enrolled in a blended course. Using students' self-report on…
Descriptors: College Students, Electronic Learning, Blended Learning, Curriculum Design
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Whitelock-Wainwright, Alexander; Gaševic, Dragan; Tsai, Yi-Shan; Drachsler, Hendrik; Scheffel, Maren; Muñoz-Merino, Pedro J.; Tammets, Kairit; Delgado Kloos, Carlos – Journal of Computer Assisted Learning, 2020
To assist higher education institutions in meeting the challenge of limited student engagement in the implementation of Learning Analytics services, the Questionnaire for Student Expectations of Learning Analytics (SELAQ) was developed. This instrument contains 12 items, which are explained by a purported two-factor structure of "Ethical and…
Descriptors: Questionnaires, Test Construction, Test Validity, Learning Analytics
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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