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Jelena N. Larsen; Kine M. D. Maxwell; Mohammad Khalil – Journal of Learning Analytics, 2025
Effective learning design (LD) grounded in sound pedagogy is a critical driver of student success. Therefore, it is important to explore how LD of online learning environments influences student ability to manage their own learning. This understanding can inform the development of online programs that prioritize student-driven learning. Research…
Descriptors: Literature Reviews, Learning Analytics, Instructional Design, Student Motivation
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Talbi, Omar; Ouared, Abdelkader – Education and Information Technologies, 2022
Determining student motivation within the context of Learning Analytics is fundamental for academic students to realize their educational goals. We aim to perceive the student's motivation state at a high level of abstraction and act accordingly to deal with motivation issues. We investigate how Model-Driven Engineering paradigms capture the…
Descriptors: Goal Orientation, Student Motivation, Learning Analytics, Teaching Methods
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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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Muhittin Sahin – Interactive Learning Environments, 2024
Learning analytics aims to improve learning and teaching in digital learning environments by optimizing them. Real-time feedback, suggestions, directions, and interventions are structured in the digital learning environments. In order to structure more effective interventions, it is crucial to ascertain which of these services offered to students…
Descriptors: Learning Analytics, Intervention, Student Attitudes, Preferences
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Kew, Si Na; Tasir, Zaidatun – Education and Information Technologies, 2022
The emergence of Learning Analytics has brought benefits to the educational field, as it can be used to analyse authentic data from students to identify the problems encountered in e-learning and to provide intervention to assist students. However, much is still unknown about the development of Learning Analytics intervention in terms of providing…
Descriptors: Learning Analytics, Intervention, Electronic Learning, Educational Technology
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Utamachant, Piriya; Anutariya, Chutiporn; Pongnumkul, Suporn – Smart Learning Environments, 2023
Apart from good instructional design and delivery, effective intervention is another key to strengthen student academic performance. However, intervention has been recognized as a great challenge. Most instructors struggle to identify at-risk students, determine a proper intervention approach, trace and evaluate whether the intervention works.…
Descriptors: Intervention, Learning Analytics, Learning Management Systems, Programming
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Faisal Channa; Muhterem Dindar; Andy Nguyen; Rohit Mishra – Scandinavian Journal of Educational Research, 2024
This study explored the sequential interplay between challenges and regulatory processes in high- and low-performing collaborative groups. 66 students from a Finnish higher education institution participated in a collaborative task in groups of three. Approximately 34 h of video data were coded. The sequential analysis revealed that both groups…
Descriptors: Cooperative Learning, High Achievement, Low Achievement, Foreign Countries
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Gabbay, Hagit; Cohen, Anat – International Educational Data Mining Society, 2023
In MOOCs for programming, Automated Testing and Feedback (ATF) systems are frequently integrated, providing learners with immediate feedback on code assignments. The analysis of the large amounts of trace data collected by these systems may provide insights into learners' patterns of utilizing the automated feedback, which is crucial for the…
Descriptors: MOOCs, Feedback (Response), Teaching Methods, Learning Strategies
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Torres Castro, Uriel Eduardo; Pineda-Báez, Clelia – Journal of Further and Higher Education, 2023
The objective of this article is to analyse the development and content of research in the global literature on student agency in higher education (SAHE) based on a bibliometric review of 224 articles published in the Scopus database during the period 2000-2022. VOSviewer, Excel, and Tableau software were used to analyse the texts. The review…
Descriptors: Personal Autonomy, Higher Education, Social Cognition, Student Motivation
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Yildirim, Denizer; Gülbahar, Yasemin – Technology, Knowledge and Learning, 2022
This study aims to determine indicators that affect students' final performance in an online learning environment using predictive learning analytics in an ICT course and Turkey context. The study takes place within a large state university in an online computer literacy course (14 weeks in one semester) delivered to freshmen students (n = 1209).…
Descriptors: Electronic Learning, Foreign Countries, Computer Literacy, College Freshmen
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Karaoglan Yilmaz, Fatma Gizem; Yilmaz, Ramazan – Innovations in Education and Teaching International, 2021
In this research, the effect of the use of learning analytics (LA) based feedback as a metacognitive tool on the learners' transactional distance and motivation was examined. The research was carried out according to experimental design and was carried out on 81 university students. The students were randomly assigned to the experimental and…
Descriptors: Learning Analytics, Metacognition, Student Motivation, College Freshmen
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Tim Urdan, Editor; Eleftheria N. Gonida, Editor – Advances in Motivation and Achievement, 2023
Stuart A. Karabenick was a prolific scholar and a co-editor of the "Advances in Motivation and Achievement" book series. At the time of his passing on August 1st, 2020, he was a Professor Emeritus at Easter Michigan University and a Research-Professor Emeritus at the University of Michigan. Throughout his long career in Educational…
Descriptors: Self Management, Help Seeking, Teacher Motivation, Educational Psychology
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Švábenský, Valdemar; Baker, Ryan S.; Zambrano, Andrés; Zou, Yishan; Slater, Stefan – International Educational Data Mining Society, 2023
Students who take an online course, such as a MOOC, use the course's discussion forum to ask questions or reach out to instructors when encountering an issue. However, reading and responding to students' questions is difficult to scale because of the time needed to consider each message. As a result, critical issues may be left unresolved, and…
Descriptors: Generalization, Computer Mediated Communication, MOOCs, State Universities
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Çebi, Ayça; Güyer, Tolga – Education and Information Technologies, 2020
In this study, students' interactions with different learning activities are examined and the relation among learning performance with different interaction patterns, learning performance, self-regulated learning (SRL) strategies and motivation is presented. Learning materials including different kinds of activities are prepared and presented to…
Descriptors: Interaction, Behavior Patterns, Learning Analytics, Electronic Learning
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Asmaa Sakr; Tariq Abdullah – Education and Information Technologies, 2024
Virtual and Augmented Reality technologies have emerged as promising tools in the education sector, offering new possibilities for immersive learning experiences. Many researchers have focused their research on examining the potential of these technologies in education from different perspectives. However, it was discovered that there are research…
Descriptors: Computer Simulation, Technology Uses in Education, Physical Environment, Learning Analytics
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