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Showing 106 to 120 of 168 results Save | Export
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Talebinamvar, Mobina; Zarrabi, Forooq – Language Testing in Asia, 2022
Feedback is an essential component of learning environments. However, providing feedback in populated classes can be challenging for teachers. On the one hand, it is unlikely that a single kind of feedback works for all students considering the heterogeneous nature of their needs. On the other hand, delivering personalized feedback is infeasible…
Descriptors: Feedback (Response), Writing Evaluation, Writing (Composition), Learning Analytics
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Chavan, Pankaj; Mitra, Ritayan – Journal of Learning Analytics, 2022
The use of online video lectures in universities, primarily for content delivery and learning, is on the rise. Instructors' ability to recognize and understand student learning experiences with online video lectures, identify particularly difficult or disengaging content and thereby assess overall lecture quality can inform their instructional…
Descriptors: Learning Analytics, Video Technology, Lecture Method, Online Courses
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Sridharan, Shwetha; Saravanan, Deepti; Srinivasan, Akshaya Kesarimangalam; Murugan, Brindha – Education and Information Technologies, 2021
There exist numerous resources online to gain the desired level of knowledge on any topic. However, this complicates the process of selecting the most appropriate resources. Every learner differs in terms of their learning speed, proficiency, and preferred mode of learning. This paper develops an adaptive learning management system to tackle this…
Descriptors: Integrated Learning Systems, Computer Assisted Instruction, Individualized Instruction, Learning Analytics
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Silvia García-Méndez; Francisco de Arriba-Pérez; Francisco J. González-Castaño – International Association for Development of the Information Society, 2023
Mobile learning or mLearning has become an essential tool in many fields in this digital era, among the ones educational training deserves special attention, that is, applied to both basic and higher education towards active, flexible, effective high-quality and continuous learning. However, despite the advances in Natural Language Processing…
Descriptors: Higher Education, Artificial Intelligence, Computer Software, Usability
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Matcha, Wannisa; Uzir, Nora'ayu Ahmad; Gasevic, Dragan; Pardo, Abelardo – IEEE Transactions on Learning Technologies, 2020
This paper presents a systematic literature review of learning analytics dashboards (LADs) research that reports empirical findings to assess the impact on learning and teaching. Several previous literature reviews identified self-regulated learning as a primary focus of LADs. However, there has been much less understanding how learning analytics…
Descriptors: Learning Analytics, Computer Interfaces, Educational Research, Learning Strategies
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Ahmad Uzir, Nora'ayu; Gaševic, Dragan; Matcha, Wannisa; Jovanovic, Jelena; Pardo, Abelardo – Journal of Computer Assisted Learning, 2020
This paper aims to explore time management strategies followed by students in a flipped classroom through the analysis of trace data. Specifically, an exploratory study was conducted on the dataset collected in three consecutive offerings of an undergraduate computer engineering course (N = 1,134). Trace data about activities were initially coded…
Descriptors: Time Management, Blended Learning, Learning Analytics, Undergraduate Students
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Leu, Katherine – RTI International, 2020
Postsecondary education is awash in data. Postsecondary institutions track data on students' demographics, academic performance, course-taking, and financial aid, and have put these data to use, applying data analytics and data science to issues in college completion. Meanwhile, an extensive amount of higher education data are being collected…
Descriptors: Learning Analytics, Postsecondary Education, Academic Achievement, Graduation Rate
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Ahmad Faza; Ilyana Agri Lestari – International Review of Research in Open and Distributed Learning, 2025
When students enter higher education, self-regulated learning (SRL) involving goal setting, planning, monitoring, and reflection is crucial for academic success. This study systematically reviews SRL strategies, supporting technologies, and their impacts, especially with the shift to online learning due to the COVID-19 pandemic. Following…
Descriptors: Metacognition, Educational Benefits, Learning Management Systems, Goal Orientation
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Moonen-van Loon, Joyce M. W.; Govaerts, Marjan; Donkers, Jeroen; van Rosmalen, Peter – IEEE Transactions on Learning Technologies, 2022
Self-directed learning is generally considered a key competence in higher education. To enable self-directed learning, assessment practices increasingly embrace assessment for learning rather than the assessment of learning, shifting the focus from grades and scores to provision of rich, narrative, and personalized feedback. Students are expected…
Descriptors: Competency Based Education, Portfolios (Background Materials), Feedback (Response), Independent Study
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Li, Jessica; Wong, Seohyun Claire; Yang, Xue; Bell, Allison – Educational Technology Research and Development, 2020
How should learner analytics and different media be used to optimize feedback to increase students' motivation and sense of learning community in online learning programs? This study was designed to examine the usage of feedback delivery methods (text only, video only, or both) and learner analytics (individual vs. class average) to answer the…
Descriptors: Learning Analytics, Feedback (Response), Student Participation, Electronic Learning
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Morakinyo Akintolu; Akinpelu A. Oyekunle – Journal of Educators Online, 2025
This paper provides a comprehensive overview of the research on the application of artificial intelligence (AI) in primary education to explore its potential to enhance teaching and learning processes. Through a systematic review of the relevant literature, this study identifies key areas in which AI can significantly impact primary education and…
Descriptors: Data Analysis, Learning Analytics, Artificial Intelligence, Computer Software
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Lim, Lisa-Angelique; Dawson, Shane; Gaševic, Dragan; Joksimovic, Srecko; Pardo, Abelardo; Fudge, Anthea; Gentili, Sheridan – Assessment & Evaluation in Higher Education, 2021
Research and development in learning analytics has established viable solutions for scaling personalised feedback to all students. However, questions remain regarding how such feedback is perceived, interpreted and acted upon by stakeholders. The present study reports on the analysis of focus group data from four courses to understand students'…
Descriptors: Student Attitudes, College Students, Emotional Response, Individualized Instruction
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Hunt, Pihel; Leijen, Äli; van der Schaaf, Marieke – Education Sciences, 2021
While there is now extensive research on feedback in the context of higher education, including pre-service teacher education, little has been reported regarding the use of feedback from teachers to other teachers. Moreover, literature on the potential advantages that the use of technology, for example electronic portfolios and learning analytics,…
Descriptors: Teacher Attitudes, Teacher Evaluation, Peer Evaluation, Feedback (Response)
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Li, Xiaoyu; Xia, Jianping – Science Insights Education Frontiers, 2020
The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new…
Descriptors: Foreign Countries, Middle School Students, Data Analysis, Data Collection
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Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan – Applied Cognitive Psychology, 2020
Worked-examples have been established as an effective instructional format in problem-solving practices. However, less is known about variations in the use of worked examples across individuals at different stages in their learning process in student-centred learning contexts. This study investigates different profiles of students' learning…
Descriptors: Individual Differences, Preferences, Demonstrations (Educational), Learning Analytics
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