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Showing 1 to 15 of 53 results Save | Export
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Shiqi Liu; Sannyuya Liu; Xian Peng; Jianwen Sun; Zhi Liu – Journal of Educational Computing Research, 2025
Forum discussions in Massive Open Online Courses (MOOCs) play a crucial role in promoting learning engagement and academic achievement. In particular, discussion topics significantly influence learners' emotional and cognitive engagement. However, the complex interrelationships among these factors remain underexplored. This study introduces an…
Descriptors: MOOCs, Difficulty Level, Learner Engagement, Academic Achievement
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Serena Lee-Cultura; Kshitij Sharma; Michail N. Giannakos – IEEE Transactions on Learning Technologies, 2024
Teacher dashboards provide insights on students' progress through visualizations and scores derived from data generated during teaching and learning activities (e.g., response times and task correctness) to improve teaching. Despite the potential usefulness of enhancing teacher dashboards, and the respective teaching practices, with rich…
Descriptors: Educational Technology, Learning Analytics, Technology Uses in Education, Student Evaluation
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Jyoti Prakash Meher; Rajib Mall – IEEE Transactions on Education, 2025
Contribution: This article suggests a novel method for diagnosing a learner's cognitive proficiency using deep neural networks (DNNs) based on her answers to a series of questions. The outcome of the forecast can be used for adaptive assistance. Background: Often a learner spends considerable amounts of time in attempting questions on the concepts…
Descriptors: Cognitive Ability, Assistive Technology, Adaptive Testing, Computer Assisted Testing
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Liu, Lingyan; Zhao, Bo; Rao, Yiqiang – International Journal of Information and Communication Technology Education, 2022
A lot of studies have shown that there is an "inverse U-curve" relationship between learners' grades and cognitive load. Learners' grades are closely related to their learning behavior characteristics on online learning. Is there any relationship between online learners' behavior characteristics and cognitive load? Based on this, the…
Descriptors: Cognitive Processes, Difficulty Level, Learning Analytics, Electronic Learning
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Aditya Shah; Ajay Devmane; Mehul Ranka; Prathamesh Churi – Education and Information Technologies, 2024
Online learning has grown due to the advancement of technology and flexibility. Online examinations measure students' knowledge and skills. Traditional question papers include inconsistent difficulty levels, arbitrary question allocations, and poor grading. The suggested model calibrates question paper difficulty based on student performance to…
Descriptors: Computer Assisted Testing, Difficulty Level, Grading, Test Construction
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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
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Zhao, Fuzheng; Liu, Gi-Zen; Zhou, Juan; Yin, Chengjiu – Educational Technology & Society, 2023
Big data in education promotes access to the analysis of learning behavior, yielding many valuable analysis results. However, with obscure and insufficient guidelines commonly followed when applying the analysis results, it is difficult to translate information knowledge into actionable strategies for educational practices. This study aimed to…
Descriptors: Learning Analytics, Man Machine Systems, Artificial Intelligence, Learning Strategies
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Ramli, Izzat Syahir Mohd; Maat, Siti Mistima; Khalid, Fariza – Cypriot Journal of Educational Sciences, 2022
Game-based learning has received increasing attention in recent years as it could help improve pupils' motivation, self-efficacy, and achievement. Technological innovations like learning analytics (LA) and GBL offer pedagogical support for teachers. GBL could significantly support pupils' learning as a learning approach compared to conventional…
Descriptors: Game Based Learning, Learning Analytics, Elementary School Mathematics, Cognitive Processes
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Xavier Ochoa; Xiaomeng Huang; Yuli Shao – Journal of Learning Analytics, 2025
Generative AI (GenAI) has the potential to revolutionize the analysis of educational data, significantly impacting learning analytics (LA). This study explores the capability of non-experts, including administrators, instructors, and students, to effectively use GenAI for descriptive LA tasks without requiring specialized knowledge in data…
Descriptors: Learning Analytics, Artificial Intelligence, Computer Software, Scores
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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Khulbe, Manisha; Tammets, Kairit – Technology, Knowledge and Learning, 2023
Insights derived from classroom data can help teachers improve their practice and students' learning. However, a number of obstacles stand in the way of widespread adoption of data use. Teachers are often sceptical about the usefulness of data. Even when willing to work with data, they often do not have the relevant skills. Tools for analysis of…
Descriptors: Faculty Development, Learning Analytics, Intervention, Teacher Attitudes
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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
Marco D'Alessio – ProQuest LLC, 2024
Learning designers face challenges integrating learning analytics (LA) when designing learner-content interactions in corporate online education. The quality of the learning design directly affects learners' engagement and impacts the transfer of learning at work. This qualitative study aimed to explore the perspectives of experienced learning…
Descriptors: Curriculum Design, Attitudes, Learning Analytics, Data Use
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Pelanek, Radek – Journal of Learning Analytics, 2021
In this work, we consider learning analytics for primary and secondary schools from the perspective of the designer of a learning system. We provide an overview of practically useful analytics techniques with descriptions of their applications and specific illustrations. We highlight data biases and caveats that complicate the analysis and its…
Descriptors: Learning Analytics, Elementary Schools, Secondary Schools, Educational Technology
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Tsutsumi, Emiko; Kinoshita, Ryo; Ueno, Maomi – International Educational Data Mining Society, 2021
Knowledge tracing (KT), the task of tracking the knowledge state of each student over time, has been assessed actively by artificial intelligence researchers. Recent reports have described that Deep-IRT, which combines Item Response Theory (IRT) with a deep learning model, provides superior performance. It can express the abilities of each student…
Descriptors: Item Response Theory, Prediction, Accuracy, Artificial Intelligence
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