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Winne, Philip H. – Metacognition and Learning, 2022
Metacognition is the engine of self-regulated learning. At the object level, learners seek information and choose learning tactics and strategies they forecast will develop knowledge. At the meta level, learners gather and analyze data about learning events to draw conclusions, such as: Is this tactic a good fit to conditions? Was it effective?…
Descriptors: Metacognition, Learning Strategies, Computer Software, Data Analysis
Han, Insook; Obeid, Iyad; Greco, Devon – Technology, Knowledge and Learning, 2023
This report describes the use of electroencephalography (EEG) to collect online learners' physiological information. Recent technological advancements allow the unobtrusive collection of live neurosignals while learners are engaged in online activities. In the context of multimodal learning analytics, we discuss the potential use of this new…
Descriptors: Learning Analytics, Diagnostic Tests, Metacognition, Brain Hemisphere Functions
Vigentini, Lorenzo; Swibel, Brad; Hasler, Garth – Journal of Learning Analytics, 2022
While Learning Analytics (LA) have gained momentum in higher education, there are still few examples of application in the school sector. Even fewer cases are reported of systematic, organizational adoption to drive the support of student learning trajectories that includes teachers, pastoral leaders, and academic managers. This paper presents one…
Descriptors: Learning Analytics, Educational Improvement, Secondary School Students, Learning Management Systems
Winne, Philip H.; Teng, Kenny; Chang, Daniel; Lin, Michael Pin-Chuan; Marzouk, Zahia; Nesbit, John C.; Patzak, Alexandra; Rakovic, Mladen; Samadi, Donya; Vytasek, Jovita – Journal of Learning Analytics, 2019
Data used in learning analytics rarely provide strong and clear signals about how learners process content. As a result, learning as a process is not clearly described for learners or for learning scientists. GaĊĦevic, Dawson, and Siemens (2015) urged data be sought that more straightforwardly describe processes in terms of events within learning…
Descriptors: Learning Analytics, Learning Processes, Independent Study, Computer Software
Chen, Li; Lu, Min; Goda, Yoshiko; Yamada, Masanori – International Association for Development of the Information Society, 2019
Metacognition is an aspect in self-regulated learning and is necessary to achieve such learning in an effective and efficient manner. However, it is not always easy and accurate for learners to monitor or assess their own metacognition. In this study, we designed a learning analytics dashboard to improve self-regulated learning in online…
Descriptors: Learning Analytics, Metacognition, Learning Strategies, Information Management
Bull, Susan – Research and Practice in Technology Enhanced Learning, 2016
Today's technology-enabled learning environments are becoming quite different from those of a few years ago, with the increased processing power as well as a wider range of educational tools. This situation produces more data, which can be fed back into the learning process. Open learner models have already been investigated as tools to promote…
Descriptors: Educational Technology, Electronic Learning, Models, Computer Assisted Instruction