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Xia, Xiaona; Qi, Wanxue – International Journal of Educational Technology in Higher Education, 2023
The temporal sequence of learning behavior is multidimensional and continuous in MOOCs. On the one hand, it supports personalized learning methods, achieves flexible time and space. On the other hand, it also makes MOOCs produce a large number of dropouts and incomplete learning behaviors. Dropout prediction and decision feedback have become an…
Descriptors: MOOCs, Dropouts, Prediction, Decision Making
Ramaswami, Gomathy; Susnjak, Teo; Mathrani, Anuradha; Umer, Rahila – Technology, Knowledge and Learning, 2023
Learning analytics dashboards (LADs) provide educators and students with a comprehensive snapshot of the learning domain. Visualizations showcasing student learning behavioral patterns can help students gain greater self-awareness of their learning progression, and at the same time assist educators in identifying those students who may be facing…
Descriptors: Prediction, Learning Analytics, Learning Management Systems, Identification
Zheng, Lanqin; Niu, Jiayu; Zhong, Lu – British Journal of Educational Technology, 2022
Learning analytics (LA) has been widely adopted in research on education. However, most studies in the area have conducted LA after computer-supported collaborative learning (CSCL) activities rather than during CSCL. To address this problem, this study proposed a LA-based real-time feedback approach based on a deep neural network model to improve…
Descriptors: Learning Analytics, Feedback (Response), Outcomes of Education, Cooperative Learning
Okan Bulut; Tarid Wongvorachan – OTESSA Conference Proceedings, 2022
Feedback is an essential part of the educational assessment that improves student learning. As education changes with the advancement of technology, educational assessment has also adapted to the advent of Artificial Intelligence (AI). Despite the increasing use of online assessments during the last decade, a limited number of studies have…
Descriptors: Feedback (Response), Artificial Intelligence, Technology Uses in Education, Natural Language Processing
The Choice between Cognitive Diagnosis and Item Response Theory: A Case Study from Medical Education
Youn Seon Lim; Catherine Bangeranye – International Journal of Testing, 2024
Feedback is a powerful instructional tool for motivating learning. But effective feedback, requires that instructors have accurate information about their students' current knowledge status and their learning progress. In modern educational measurement, two major theoretical perspectives on student ability and proficiency can be distinguished.…
Descriptors: Cognitive Measurement, Diagnostic Tests, Item Response Theory, Case Studies
Caitlin Mills, Editor; Giora Alexandron, Editor; Davide Taibi, Editor; Giosuè Lo Bosco, Editor; Luc Paquette, Editor – International Educational Data Mining Society, 2025
The University of Palermo is proud to host the 18th International Conference on Educational Data Mining (EDM) in Palermo, Italy, from July 20 to July 23, 2025. EDM is the annual flagship conference of the International Educational Data Mining Society. This year's theme is "New Goals, New Measurements, New Incentives to Learn." The theme…
Descriptors: Artificial Intelligence, Data Analysis, Computer Science Education, Technology Uses in Education
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
Zhang, Mengxue; Wang, Zichao; Baraniuk, Richard; Lan, Andrew – International Educational Data Mining Society, 2021
Feedback on student answers and even during intermediate steps in their solutions to open-ended questions is an important element in math education. Such feedback can help students correct their errors and ultimately lead to improved learning outcomes. Most existing approaches for automated student solution analysis and feedback require manually…
Descriptors: Mathematics Instruction, Teaching Methods, Intelligent Tutoring Systems, Error Patterns
Liu, Sannyuya; Peng, Xian; Cheng, Hercy N. H.; Liu, Zhi; Sun, Jianwen; Yang, Chongyang – Journal of Educational Computing Research, 2019
Course reviews, which is designed as an interactive feedback channel in Massive Open Online Courses, has promoted the generation of large-scale text comments. These data, which contain not only learners' concerns, opinions and feelings toward courses, instructors, and platforms but also learners' interactions (e.g., post, reply), are generally…
Descriptors: Course Evaluation, Online Courses, Student Attitudes, Course Content
Botelho, Anthony F.; Varatharaj, Ashvini; Patikorn, Thanaporn; Doherty, Diana; Adjei, Seth A.; Beck, Joseph E. – IEEE Transactions on Learning Technologies, 2019
The increased usage of computer-based learning platforms and online tools in classrooms presents new opportunities to not only study the underlying constructs involved in the learning process, but also use this information to identify and aid struggling students. Many learning platforms, particularly those driving or supplementing instruction, are…
Descriptors: Student Attrition, Student Behavior, Early Intervention, Identification
Simonson, Michael, Ed.; Seepersaud, Deborah, Ed. – Association for Educational Communications and Technology, 2021
For the forty-fourth time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented online and onsite during the annual AECT Convention. Volume 1 contains papers dealing primarily with research and development topics. Papers dealing with…
Descriptors: Educational Technology, Technology Uses in Education, Feedback (Response), Course Evaluation

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