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Showing 1 to 15 of 160 results Save | Export
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Kok, Ellen M.; Jarodzka, Halszka; Sibbald, Matt; van Gog, Tamara – Cognitive Science, 2023
In online lectures, unlike in face-to-face lectures, teachers lack access to (nonverbal) cues to check if their students are still "with them" and comprehend the lecture. The increasing availability of low-cost eye-trackers provides a promising solution. These devices measure unobtrusively where students look and can visualize these data…
Descriptors: Prediction, Listening Comprehension, Video Technology, Lecture Method
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Henderson, Nathan; Min, Wookhee; Emerson, Andrew; Rowe, Jonathan; Lee, Seung; Minogue, James; Lester, James – International Educational Data Mining Society, 2021
Recent years have seen significant interest in multimodal frameworks for modeling learner engagement in educational settings. Multimodal frameworks hold particular promise for predicting visitor engagement in interactive science museum exhibits. Multimodal models often utilize video data to capture learner behavior, but video cameras are not…
Descriptors: Museums, Audiences, Participation, Exhibits
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Babette Bühler; Efe Bozkir; Patricia Goldberg; Ömer Sümer; Sidney D'Mello; Peter Gerjets; Ulrich Trautwein; Enkelejda Kasneci – International Journal of Artificial Intelligence in Education, 2025
Student's shift of attention away from a current learning task to task-unrelated thought, also called mind wandering, occurs about 30% of the time spent on education-related activities. Its frequent occurrence has a negative effect on learning outcomes across learning tasks. Automated detection of mind wandering might offer an opportunity to…
Descriptors: Attention, Automation, Identification, Video Technology
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Karasavvidis, Ilias; Papadimas, Charalampos; Ragazou, Vasiliki – Themes in eLearning, 2022
The digital trails that students leave behind on e-learning environments have attracted considerable attention in the past decade. Typically, some of these traces involve the production of different kinds of texts. While students routinely produce a bulk of texts in online learning settings, the potential of such linguistic features has not been…
Descriptors: Video Technology, Electronic Learning, Prediction, Academic Achievement
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Hanqiang Liu; Xiao Chen; Feng Zhao – Education and Information Technologies, 2024
Massive open online courses (MOOCs) have become one of the most popular ways of learning in recent years due to their flexibility and convenience. However, high dropout rate has become a prominent problem that hinders the further development of MOOCs. Therefore, the prediction of student dropouts is the key to further enhance the MOOCs platform.…
Descriptors: MOOCs, Video Technology, Behavior Patterns, Prediction
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Sprenger, David A.; Schwaninger, Adrian – British Journal of Educational Technology, 2023
The technology acceptance model (TAM) uses perceived usefulness and perceived ease of use to predict the intention to use a technology which is important when deciding to invest in a technology. Its extension for e-learning (the general extended technology acceptance model for e-learning; GETAMEL) adds subjective norm to predict the intention to…
Descriptors: Video Technology, Demonstrations (Educational), Prediction, Intention
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Yürüm, Ozan Rasit; Taskaya-Temizel, Tugba; Yildirim, Soner – Education and Information Technologies, 2023
Video clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students' test…
Descriptors: Video Technology, Educational Technology, Learning Management Systems, Data Collection
Jia Tracy Shen; Michiharu Yamashita; Ethan Prihar; Neil Heffernan; Xintao Wu; Sean McGrew; Dongwon Lee – Grantee Submission, 2021
Educational content labeled with proper knowledge components (KCs) are particularly useful to teachers or content organizers. However, manually labeling educational content is labor intensive and error-prone. To address this challenge, prior research proposed machine learning based solutions to auto-label educational content with limited success.…
Descriptors: Mathematics Education, Knowledge Level, Video Technology, Educational Technology
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Grace D. Jaiyeola; Aaron Y. Wong; Richard L. Bryck; Caitlin Mills; Stephen Hutt – International Educational Data Mining Society, 2025
This study explores the use of webcam-based eye tracking during a learning task to predict and better understand neurodivergence with the aim of improving personalized learning to support diverse learning needs. Using WebGazer, a webcam-based eye tracking technology, we collected gaze data from 354 participants as they engaged in educational…
Descriptors: Video Technology, Eye Movements, Neurodevelopmental Disorders, Artificial Intelligence
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Pierratos, Theodoros – Physics Education, 2021
Due to the conditions imposed worldwide by the pandemic, students' access to school laboratories is limited, if not impossible. To provide students with raw experimental data to assess, analyse and reason out, we have filmed experiments that can be used in a flipped classroom. This paper presents an experiment which makes use of an array of six…
Descriptors: Science Instruction, Physics, Flipped Classroom, Science Laboratories
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Henrietta Weinberg; Florian Müller; Rouwen Cañal-Bruland – Cognitive Research: Principles and Implications, 2025
Due to severe time constraints, goalkeepers regularly face the challenging task to make decisions within just a few hundred milliseconds. A key finding of anticipation research is that experts outperform novices by using advanced cues which can be derived from either kinematic or contextual information. Yet, how context modulates decision-making…
Descriptors: Cues, Athletics, Decision Making, Specialists
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Linyu Yu; Peter F. Halpin; Matthew L. Bernacki; Sirui Ren; Robert D. Plumley; Jeffrey A. Greene – Journal of Learning Analytics, 2025
Digital traces have been used to measure self-regulated learning (SRL), yet the validity of inferences made about these traces has often been questioned. Recently, researchers have used multiple channels of data -- including digital traces, verbalizations, and self-reports -- to validate inferences about individual SRL events. Research on the…
Descriptors: Learning Analytics, Independent Study, Learning Processes, Undergraduate Students
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Ying Guo; Cynthia Puranik; Yanli Xie; Megan Schneider Dinnesen – Reading Research Quarterly, 2025
Examining the impact of reading instruction on writing can help to refine the theoretical models to better explain how skills in reading support skills in writing and inform the development of literacy curricula that leverage the synergies between reading and writing instruction. Therefore, the purposes of this study are to investigate if the…
Descriptors: Kindergarten, Reading Writing Relationship, Reading Instruction, Curriculum Development
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Abdullahi Yusuf; Norah Md Noor; Shamsudeen Bello – Education and Information Technologies, 2024
Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In…
Descriptors: Learning Analytics, Student Behavior, Video Technology, Classification
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Nordmann, Emily; Clark, Anne; Spaeth, Elliott; MacKay, Jill R. D. – Higher Education: The International Journal of Higher Education Research, 2022
Much has been written about instructor attitudes towards lecture capture, particularly concerning political issues such as opt-out policies and the use of recordings by management. Additionally, the pedagogical concerns of lecturers have been extensively described and focus on the belief that recording lectures will impact on attendance and will…
Descriptors: Active Learning, Prediction, Positive Attitudes, Teacher Attitudes
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