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Peralta, Montserrat; Alarcon, Rosa; Pichara, Karim E.; Mery, Tomas; Cano, Felipe; Bozo, Jorge – IEEE Transactions on Learning Technologies, 2018
Educational resources can be easily found on the Web. Most search engines base their algorithms on a resource's text or popularity, requiring teachers to navigate the results until they find an appropriate resource. This makes searching for resources a tedious and cumbersome task. Specialized repositories contain resources that are annotated with…
Descriptors: Educational Resources, Metadata, Foreign Countries, Bayesian Statistics
Yang, Zongkai; Yang, Juan; Rice, Kerry; Hung, Jui-Long; Du, Xu – IEEE Transactions on Learning Technologies, 2020
This article proposes two innovative approaches, the one-channel learning image recognition and the three-channel learning image recognition, to convert student's course involvements into images for early warning predictive analysis. Multiple experiments with 5235 students and 576 absolute/1728 relative input variables were conducted to verify…
Descriptors: Distance Education, At Risk Students, Artificial Intelligence, Man Machine Systems
Kinnebrew, John S.; Segedy, James R.; Biswas, Gautam – IEEE Transactions on Learning Technologies, 2017
Research in computer-based learning environments has long recognized the vital role of adaptivity in promoting effective, individualized learning among students. Adaptive scaffolding capabilities are particularly important in open-ended learning environments, which provide students with opportunities for solving authentic and complex problems, and…
Descriptors: Computer Assisted Instruction, Problem Solving, Learning, Student Behavior
Hung, Jui-Long; Shelton, Brett E.; Yang, Juan; Du, Xu – IEEE Transactions on Learning Technologies, 2019
Performance prediction is a leading topic in learning analytics research due to its potential to impact all tiers of education. This study proposes a novel predictive modeling method to address the research gaps in existing performance prediction research. The gaps addressed include: the lack of existing research focus on performance prediction…
Descriptors: Prediction, Models, At Risk Students, Identification
Lee, Victor R.; Drake, Joel R.; Thayne, Jeffrey L. – IEEE Transactions on Learning Technologies, 2016
Wearable activity tracking devices associated with the Quantified Self movement have potential benefit for educational settings because they produce authentic and granular data about activities and experiences already familiar to youth. This article explores how that potential could be realized through explicit acknowledgment of and response to…
Descriptors: Elementary School Students, Physical Activities, Measurement Equipment, Grade 5
Prieto, Luis P.; Sharma, Kshitij; Kidzinski, Lukasz; Dillenbourg, Pierre – IEEE Transactions on Learning Technologies, 2018
Orchestration load is the effort a teacher spends in coordinating multiple activities and learning processes. It has been proposed as a construct to evaluate the usability of learning technologies at the classroom level, in the same way that cognitive load is used as a measure of usability at the individual level. However, so far this notion has…
Descriptors: Eye Movements, Cognitive Ability, Usability, Classroom Techniques