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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
Adelson de Araujo; Pantelis M. Papadopoulos; Susan McKenney; Ton de Jong – Journal of Computer Assisted Learning, 2024
Background: Sustaining productive student-student dialogue in online collaborative inquiry learning is challenging, and teacher support is limited when needed in multiple groups simultaneously. Collaborative conversational agents (CCAs) have been used in the past to support student dialogue. Yet, research is needed to reveal the characteristics…
Descriptors: Learning Analytics, Computer Mediated Communication, Artificial Intelligence, Dialogs (Language)
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
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
Rebecka Rundquist; Kristina Holmberg; John Rack; Zeynab Mohseni; Italo Masiello – Journal of Learning Analytics, 2024
The generation, use, and analysis of educational data comes with many promises and opportunities, especially where digital materials allow usage of learning analytics (LA) as a tool in data-based decision-making (DBDM). However, there are questions about the interplay between teachers, students, context, and technology. Therefore, this paper…
Descriptors: Learning Analytics, Elementary Secondary Education, Mathematics Education, Data Analysis
Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
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
Savi, Alexander O.; Deonovic, Benjamin E.; Bolsinova, Maria; van der Maas, Han L. J.; Maris, Gunter K. J. – Journal of Educational Data Mining, 2021
In learning, errors are ubiquitous and inevitable. As these errors may signal otherwise latent cognitive processes, tutors--and students alike--can greatly benefit from the information they provide. In this paper, we introduce and evaluate the Systematic Error Tracing (SET) model that identifies the possible causes of systematically observed…
Descriptors: Learning Processes, Cognitive Processes, Error Patterns, Models
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
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
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