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Showing 1 to 15 of 47 results Save | Export
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Ma, Boxuan; Lu, Min; Taniguchi, Yuta; Konomi, Shin'ichi – Smart Learning Environments, 2022
With the increasing use of digital learning materials in higher education, the accumulated operational log data provide a unique opportunity to analyzing student learning behaviors and their effects on student learning performance to understand how students learn with e-books. Among the students' reading behaviors interacting with e-book systems,…
Descriptors: Behavior Patterns, Electronic Publishing, Books, Reading Processes
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Zheng, Lanqin; Zhong, Lu; Fan, Yunchao – Education and Information Technologies, 2023
Online collaborative learning (OCL) has been a mainstream pedagogy in the field of higher education. However, learners often produce off-topic information and engage less during online collaborative learning compared to other approaches. In addition, learners often cannot converge in knowledge, and they often do not know how to coregulate with…
Descriptors: Electronic Learning, Cooperative Learning, Undergraduate Students, Learning Analytics
Phillip Scott Moses – ProQuest LLC, 2024
The Society for Learning Analytics Research (SoLAR) defines learning analytics as "the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs" (SoLAR, n.d.). To fully realize the potential of learning…
Descriptors: Learning Analytics, Change Strategies, Learning Processes, Higher Education
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Liyin Zhang; Mian Wu; Fan Ouyang – Education and Information Technologies, 2024
The data-intensive research paradigm calls for using educational and learning data to generate actionable insights and improve the instruction and learning quality. Although previous research designed and employed teaching analytics or learning analytics tools, few research had incorporated multiple data sources to assess the overall teaching and…
Descriptors: In Person Learning, Small Classes, Foreign Countries, Learning Analytics
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Ean Teng Khor; Dave Darshan – International Journal of Information and Learning Technology, 2024
Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
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Keskin, Sinan; Yurdugül, Halil – Journal of Educational Technology and Online Learning, 2022
This study aims to examine e-learning experiences of the learners by using learner system interaction metrics. In this context, an e-learning environment has been structured within the scope of a course. Learners interacted with learning activities and leave various traces when they interact with others, contents, and assessment tasks. Log data…
Descriptors: Electronic Learning, Learning Experience, Models, Learning Activities
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Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
Majumdar, Rwitajit; Bakilapadavu, Geetha; Majumder, Reek; Chen, Mei-Rong Alice; Flanagan, Brendan; Ogata, Hiroaki – Research and Practice in Technology Enhanced Learning, 2021
This study investigates learner's reading behaviors in a critical reading task in humanities course using learning analytics techniques. "A Critical Analysis of Literature and Cinema" course was selected as a context. The course activities evolved over 10 years, and for this instance, some face-to-face classroom critical reading…
Descriptors: Learning Analytics, Humanities, Critical Reading, Electronic Publishing
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Gungadeen, Anuradha; Rajnee, Lobind – International Journal on E-Learning, 2023
With the current shift in educational settings to blended and flipped classroom and the introduction of learning management systems (LMS) such as Moodle, it is no surprise big data has found its place in education and is predicted to be extensively implemented in institutions of higher education (Johnson et al., 2013). In a flipped classroom…
Descriptors: Learning Analytics, Teacher Student Relationship, Peer Relationship, Interaction
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Cock, Jade; Marras, Mirko; Giang, Christian; Käser, Tanja – International Educational Data Mining Society, 2021
Interactive simulations allow students to independently explore scientific phenomena and ideally infer the underlying principles through their exploration. Effectively using such environments is challenging for many students and therefore, adaptive guidance has the potential to improve student learning. Providing effective support is, however,…
Descriptors: Prediction, Concept Formation, Scientific Concepts, Physics
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Mubarak, Ahmed A.; Cao, Han; Zhang, Weizhen – Interactive Learning Environments, 2022
Online learning has become more popular in higher education since it adds convenience and flexibility to students' schedule. But, it has faced difficulties in the retention of the continuity of students and ensure continual growth in course. Dropout is a concerning factor in online course continuity. Therefore, it has sparked great interest among…
Descriptors: Prediction, Dropouts, Interaction, Learning Analytics
Curran, Sue Ann Cecilia – ProQuest LLC, 2022
The purpose of learning analytics is to improve and optimize learning using student data (Siemens, 2013). An early alert warning is learning analytics designed to promote student success (Baneres et al., 2019; Foung, 2019; Lawson et al., 2016; Villano et al., 2018). An early alert has an intervention component that includes, at minimum, an email…
Descriptors: Failure, At Risk Students, Learning Analytics, Intervention
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Joel Weijia Lai; Wei Qiu; Maung Thway; Lei Zhang; Nurabidah Binti Jamil; Chit Lin Su; Samuel S. H. Ng; Fun Siong Lim – Journal of Learning Analytics, 2025
The growing use of generative AI (GenAI) has sparked discussions regarding integrating these tools into educational settings to enrich the learning experience of teachers and students. Self-regulated learning (SRL) research is pivotal in addressing this inquiry. One prevalent manifestation of GenAI is the large-language model (LLM) chatbot,…
Descriptors: Artificial Intelligence, Computer Software, Learning Analytics, Introductory Courses
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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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Celik, Ismail; Gedrimiene, Egle; Silvola, Anni; Muukkonen, Hanni – Policy Futures in Education, 2023
Emerging technological advancements can play an essential role in overcoming challenges caused by the COVID-19 pandemic. As a promising educational technology field, Learning Analytics (LA) tools or systems can offer solutions to COVID-19 pandemic-related needs, obstacles, and expectations in higher education. In the current study, we…
Descriptors: Higher Education, Electronic Learning, Distance Education, Pandemics
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