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Amanpreet Kaur; Kuljit Kaur Chahal – Education and Information Technologies, 2024
Research so far has overlooked the contribution of students' noncognitive factors to their performance in introductory programming in the context of personalized learning support. This study uses learning analytics to design and implement a Dashboard to understand the contribution of introductory programming students' learning motivation,…
Descriptors: Learning Analytics, Introductory Courses, Programming, Computer Science Education
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Chin-Yuan Lai; Li-Ju Chen – Educational Technology & Society, 2025
Web-based multimedia annotation is a valuable tool for engaging learners with diverse materials. This study aimed to assess the effects of multimedia annotation on student performance, self-regulation, and cognitive load in an online learning environment. We developed and implemented a multimedia annotation system in an online biology class using…
Descriptors: Multimedia Materials, Instructional Effectiveness, Metacognition, Cognitive Ability
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Cleon Xavier; Luiz Rodrigues; Newarney Costa; Rodrigues Neto; Gabriel Alves; Taciana Pontual Falcao; Dragan Gasevic; Rafael Ferreira Mello – IEEE Transactions on Learning Technologies, 2025
Providing timely and personalized feedback on open-ended student responses is a challenge in education due to the increased workloads and time constraints educators face. While existing research has explored how learning analytic approaches can support feedback provision, previous studies have not sufficiently investigated educators' perspectives…
Descriptors: Teacher Empowerment, Learning Analytics, Artificial Intelligence, Computer Software
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Paul Tschisgale; Marcus Kubsch; Peter Wulff; Stefan Petersen; Knut Neumann – Physical Review Physics Education Research, 2025
Problem solving is considered an essential ability for becoming an expert in physics, and individualized feedback on the structure of problem-solving processes is a key component to support students in developing this ability. Problem-solving processes consist of multiple elements whose order forms the sequential structure of these processes.…
Descriptors: Problem Solving, Physics, Science Instruction, Teaching Methods
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Shihui Feng; David Gibson; Dragan Gaševic – Journal of Learning Analytics, 2025
Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Student Role, Learning Analytics
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Eran Hadas; Arnon Hershkovitz – Journal of Learning Analytics, 2025
Creativity is an imperative skill for today's learners, one that has important contributions to issues of inclusion and equity in education. Therefore, assessing creativity is of major importance in educational contexts. However, scoring creativity based on traditional tools suffers from subjectivity and is heavily time- and labour-consuming. This…
Descriptors: Creativity, Evaluation Methods, Computer Assisted Testing, Artificial Intelligence
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Chang Lu; Okan Bulut; Carrie Demmans Epp; Mark Gierl – Distance Education, 2025
Engagement is essential for improving academic outcomes, especially in technology-enhanced learning (TEL) environments where self-regulated learning is critical. This study investigated the longitudinal impacts of different levels of engagement on undergraduate students' short-term and long-term academic outcomes in TEL. Using a learning analytics…
Descriptors: Learner Engagement, Outcomes of Education, Technology Uses in Education, Educational Technology
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Eva de Schipper; Remco Feskens; Franck Salles; Saskia Keskpaik; Reinaldo dos Santos; Bernard Veldkamp; Paul Drijvers – Large-scale Assessments in Education, 2025
Background: Students take many tests and exams during their school career, but they usually receive feedback about their test performance based only on an analysis of the item responses. With the increase in digital assessment, other data have become available for analysis as well, such as log data of student actions in online assessment…
Descriptors: Problem Solving, Mathematics Instruction, Learning Analytics, Identification
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Melis Dülger; Anouschka van Leeuwen; Jeroen Janssen; Liesbeth Kester – Education and Information Technologies, 2025
Self-regulated learning (SRL) is crucial for fostering lifelong learning skills in students, encompassing planning, monitoring, and controlling abilities. Previous research indicates that many students struggle to regulate their learning effectively. In the Netherlands, adaptive learning technologies are widely used to support math education in…
Descriptors: Educational Technology, Technology Uses in Education, Elementary School Teachers, Direct Instruction
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Lucia M. Reyes; Michael A. Cook; Steven M. Ross – Center for Research and Reform in Education, 2025
In March of 2025, brightwheel, a San Francisco-based educational technology company, partnered with the Center for Research and Reform in Education (CRRE) at Johns Hopkins University to test brightwheel's product, the Experience Assessment. The assessment was designed to provide early childhood educators with an objective and systematic way to…
Descriptors: Psychometrics, Educational Technology, Early Childhood Education, Young Children
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Diana Šimic; Barbara Šlibar; Jelena Gusic Mundar; Sabina Rako – Technology, Knowledge and Learning, 2025
Researchers and practitioners from different disciplines (e.g., educational science, computer science, statistics) continuously enter the rapidly developing research field of learning analytics (LA) and bring along different perspectives and experiences in research design and methodology. Scientific communities share common problems, concepts,…
Descriptors: Learning Analytics, Higher Education, Science Education, Publications
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Tamra Ross; Rachel Sondergaard; Cindy Ives; Andrew Han; Sabine Graf – Technology, Knowledge and Learning, 2025
To meet student demand for responsive, adaptable, and up-to-date online courses, educators and learning designers need tools to analyse student interactions with their peers, educators and learning resources. Learning Management Systems (LMSs) store large volumes of detailed user data, but offer only limited, pre-set reports and visualizations to…
Descriptors: Access to Information, Learning Analytics, Instructional Design, Evaluation Methods
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Dominguez, Federico; Ochoa, Xavier; Zambrano, Dick; Camacho, Katherine; Castells, Jaime – IEEE Transactions on Learning Technologies, 2021
Multimodal learning analytics, which is collection, analysis, and report of diverse learning traces to better understand and improve the learning process, has been producing a series of interesting prototypes to analyze learning activities that were previously hard to objectively evaluate. However, none of these prototypes have been taken out of…
Descriptors: Learning Modalities, Learning Analytics, Automation, Oral Language
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Ruiz-Calleja, Adolfo; Prieto, Luis P.; Ley, Tobias; Rodriguez-Triana, Maria Jesus; Dennerlein, Sebastian – IEEE Transactions on Learning Technologies, 2021
Despite the ubiquity of learning in workplace and professional settings, the learning analytics (LA) community has paid significant attention to such settings only recently. This may be due to the focus on researching formal learning, as workplace learning is often informal, hard to grasp, and not unequivocally defined. This article summarizes the…
Descriptors: Learning Analytics, Professional Education, Workplace Learning, Educational Trends
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Xing, Wanli; Du, Dongping; Bakhshi, Ali; Chiu, Kuo-Chun; Du, Hanxiang – IEEE Transactions on Learning Technologies, 2021
Predictive modeling in online education is a popular topic in learning analytics research and practice. This study proposes a novel predictive modeling method to improve model transferability over time within the same course and across different courses. The research gaps addressed are limited evidence showing whether a predictive model built on…
Descriptors: Electronic Learning, Bayesian Statistics, Prediction, Models
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