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Saqr, Mohammed – British Journal of Educational Technology, 2023
Learning analytics is a fast-growing discipline. Institutions and countries alike are racing to harness the power of using data to support students, teachers and stakeholders. Research in the field has proven that predicting and supporting underachieving students is worthwhile. Nonetheless, challenges remain unresolved, for example, lack of…
Descriptors: Learning Analytics, Generalizability Theory, Models, Grades (Scholastic)
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Heikkinen, Sami; Saqr, Mohammed; Malmberg, Jonna; Tedre, Matti – Education and Information Technologies, 2023
During the past years scholars have shown an increasing interest in supporting students' self-regulated learning (SRL). Learning analytics (LA) can be applied in various ways to identify a learner's current state of self-regulation and support SRL processes. It is important to examine how LA has been used to identify the need for support in…
Descriptors: Independent Study, Self Management, Learning Analytics, Intervention
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Viberg, Olga; Engström, Linda; Saqr, Mohammed; Hrastinski, Stefan – Education and Information Technologies, 2022
In order to successfully implement learning analytics (LA), we need a better understanding of student expectations of such services. Yet, there is still a limited body of research about students' expectations across countries. Student expectations of LA have been predominantly examined from a view that perceives students as a group of individuals…
Descriptors: Learning Analytics, Student Attitudes, Expectation, College Students
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Elmoazen, Ramy; Saqr, Mohammed; Khalil, Mohammad; Wasson, Barbara – Smart Learning Environments, 2023
Remote learning has advanced from the theoretical to the practical sciences with the advent of virtual labs. Although virtual labs allow students to conduct their experiments remotely, it is a challenge to evaluate student progress and collaboration using learning analytics. So far, a study that systematically synthesizes the status of research on…
Descriptors: Learning Analytics, Higher Education, Medical Education, Student Behavior
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Kleimola, Riina; López-Pernas, Sonsoles; Väisänen, Sanna; Saqr, Mohammed; Sointu, Erkko; Hirsto, Laura – Empirical Research in Vocational Education and Training, 2023
Learning analytics provides a novel means to examine various aspects of students' learning and to support them in their individual endeavors. The purpose of this study was to explore the potential of learning analytics to provide insights into non-traditional, vocational practical nurse students' (N = 132) motivational profiles for choosing their…
Descriptors: Nursing Students, Nontraditional Students, Learning Analytics, Learning Motivation
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Saqr, Mohammed; Peeters, Ward – British Journal of Educational Technology, 2022
Social Network Analysis (SNA) has enabled researchers to understand and optimize the key dimensions of collaborative learning. A majority of SNA research has so far used static networks, i.e., aggregated networks that compile interactions without considering "when" certain activities or relationships occurred. Compressing a temporal…
Descriptors: Social Networks, Network Analysis, Cooperative Learning, Electronic Learning
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Sointu, Erkko; Saqr, Mohammed; Valtonen, Teemu; Hallberg, Susanne; Väisänen, Sanna; Kankaanpää, Jenni; Tuominen, Ville; Hirsto, Laura – Journal of Technology and Teacher Education, 2023
Pre-service teacher training is research intensive in Finland. Additionally, teaching as a profession is highly valued among young people. However, quantitative methods courses are challenging for teacher students from many reasons. Particularly, this is due to previous negative experiences and emotions (among other things). Thus, novel approaches…
Descriptors: Emotional Response, Preservice Teachers, Student Behavior, Difficulty Level
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Saqr, Mohammed; López-Pernas, Sonsoles – International Journal of Computer-Supported Collaborative Learning, 2021
This study empirically investigates diffusion-based centralities as depictions of student role-based behavior in information exchange, uptake and argumentation, and as consistent indicators of student success in computer-supported collaborative learning. The analysis is based on a large dataset of 69 courses (n = 3,277 students) with 97,173 total…
Descriptors: Computer Uses in Education, Cooperative Learning, Learning Analytics, Student Behavior
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Saqr, Mohammed; Viberg, Olga; Vartiainen, Henriikka – International Journal of Computer-Supported Collaborative Learning, 2020
The increasing use of digital learning tools and platforms in formal and informal learning settings has provided broad access to large amounts of learner data, the analysis of which has been aimed at understanding students' learning processes, improving learning outcomes, providing learner support as well as teaching. Presently, such data has been…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Social Networks, Network Analysis
Saqr, Mohammed; Peeters, Ward; Viberg, Olga – Research and Practice in Technology Enhanced Learning, 2021
Writing in an academic context often requires students in higher education to acquire a new set of skills while familiarising themselves with the goals, objectives and requirements of the new learning environment. Students' ability to continuously self-regulate their writing process, therefore, is seen as a determining factor in their learning…
Descriptors: Academic Language, Self Management, Learning Strategies, Student Behavior
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Saqr, Mohammed; Jovanovic, Jelena; Viberg, Olga; Gaševic, Dragan – Studies in Higher Education, 2022
Predictors of student academic success do not always replicate well across different learning designs, subject areas, or educational institutions. This suggests that characteristics of a particular discipline and learning design have to be carefully considered when creating predictive models in order to scale up learning analytics. This study…
Descriptors: Meta Analysis, Learning Analytics, Predictor Variables, Correlation
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Saqr, Mohammed; López-Pernas, Sonsoles – Journal of Learning Analytics, 2022
There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by…
Descriptors: Measurement Techniques, Learning Analytics, Data Analysis, Academic Achievement