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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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Dirk Tempelaar; Bart Rienties; Bas Giesbers; Quan Nguyen – Journal of Learning Analytics, 2023
Learning analytics needs to pay more attention to the temporal aspect of learning processes, especially in self-regulated learning (SRL) research. In doing so, learning analytics models should incorporate both the duration and frequency of learning activities, the passage of time, and the temporal order of learning activities. However, where this…
Descriptors: Time Factors (Learning), Learning Analytics, Models, Statistical Analysis
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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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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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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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Tempelaar, Dirk – International Association for Development of the Information Society, 2022
E-tutorial learning aids as worked examples and hints have been established as effective instructional formats in problem-solving practices. However, less is known about variations in the use of learning aids across individuals at different stages in their learning process in student-centred learning contexts. This study investigates different…
Descriptors: Learning Analytics, Student Centered Learning, Learning Processes, Student Behavior
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Tempelaar, Dirk – Assessment & Evaluation in Higher Education, 2020
How can we best facilitate students most in need of learning support, entering a challenging quantitative methods module at the start of their bachelor programme? In this empirical study into blended learning and the role of assessment for and as learning, we investigate learning processes of students with different learning profiles.…
Descriptors: Learning Analytics, Formative Evaluation, Blended Learning, Undergraduate Students
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Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan – Educational Technology & Society, 2021
Precision education requires two equally important conditions: accurate predictions of academic performance based on early observations of the learning process and the availability of relevant educational intervention options. The field of learning analytics (LA) has made important contributions to the realisation of the first condition,…
Descriptors: Learning Analytics, Individualized Instruction, Blended Learning, Electronic Learning
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Tempelaar, Dirk – International Association for Development of the Information Society, 2021
The search for rigor in learning analytics applications has placed survey data in the suspect's corner, favoring more objective trace data. A potential lack of objectivity in survey data is the existence of response styles, the tendency of respondents to answer survey items in a particular biased manner, such as yeah saying or always disagreeing.…
Descriptors: Learning Analytics, Responses, Surveys, Bias
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Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan – International Association for Development of the Information Society, 2019
Learning analytic models are built upon traces students leave in technology-enhanced learning platforms as the digital footprints of their learning processes. Learning analytics uses these traces of learning engagement to predict performance and provide learning feedback to students and teachers when these predictions signal the risk of failing a…
Descriptors: Learner Engagement, Outcomes of Education, Learning Processes, Learning Analytics
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Spector, Michael, Ed.; Kumar, Vivekanandan, Ed.; Essa, Alfred, Ed.; Huang, Yueh-Min, Ed.; Koper, Rob, Ed.; Tortorella, Richard A. W., Ed.; Chang, Ting-Wen, Ed.; Li, Yanyan, Ed.; Zhang, Zhizhen, Ed. – Lecture Notes in Educational Technology, 2018
This book demonstrates teachers' and learners' experiences with big data in education; education and cloud computing; and new technologies for teacher support. It also discusses the advantages of using these frontier technologies in teaching and learning and predicts the future challenges. As such, it enables readers to better understand how…
Descriptors: Educational Technology, Technological Advancement, Data Use, Technology Uses in Education