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Moon, Jewoong; Ke, Fengfeng; Sokolikj, Zlatko; Dahlstrom-Hakki, Ibrahim – Journal of Learning Analytics, 2022
Using multimodal data fusion techniques, we built and tested prediction models to track middle-school student distress states during educational gameplay. We collected and analyzed 1,145 data instances, sampled from a total of 31 middle-school students' audio- and video-recorded gameplay sessions. We conducted data wrangling with student gameplay…
Descriptors: Learning Analytics, Stress Variables, Educational Games, Middle School Students
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Chavan, Pankaj; Mitra, Ritayan – Journal of Learning Analytics, 2022
The use of online video lectures in universities, primarily for content delivery and learning, is on the rise. Instructors' ability to recognize and understand student learning experiences with online video lectures, identify particularly difficult or disengaging content and thereby assess overall lecture quality can inform their instructional…
Descriptors: Learning Analytics, Video Technology, Lecture Method, Online Courses
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Nawaz, Sadia; Kennedy, Gregor; Bailey, James; Mead, Chris – Journal of Learning Analytics, 2020
Confusion is an important epistemic emotion because it can help students focus their attention and effort when solving complex learning tasks. However, unresolved confusion can be detrimental because it may result in students' disengagement. This is especially concerning in simulation environments using discovery-based learning, which puts more of…
Descriptors: Psychological Patterns, Emotional Response, Simulated Environment, Discovery Learning
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Ferguson, Rebecca; Clow, Doug; Griffiths, Dai; Brasher, Andrew – Journal of Learning Analytics, 2019
Learning analytics involve the measurement, collection, analysis, and reporting of data about learners and their contexts, in order to understand and optimize learning and the environments in which it occurs. Since emerging as a distinct field in 2011, learning analytics has grown rapidly, and early adopters around the world are developing and…
Descriptors: Educational Research, Data Collection, Data Analysis, Educational Technology
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Aghababyan, Ani; Martin, Taylor; Janisiewicz, Philip; Close, Kevin – Journal of Learning Analytics, 2016
Learning analytics is an emerging discipline and, as such, benefits from new tools and methodological approaches. This work reviews and summarizes our workshop on microgenetic data analysis techniques using R, held at the second annual Learning Analytics Summer Institute in Cambridge, Massachusetts, on 30 June 2014. Specifically, this paper…
Descriptors: Educational Research, Data Collection, Data Analysis, Workshops
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Dowell, Nia M. M.; Graesser, Arthur C.; Cai, Zhiqiang – Journal of Learning Analytics, 2016
The goal of this article is to preserve and distribute the information presented at the LASI (2014) workshop on Coh-Metrix, a theoretically grounded, computational linguistics facility that analyzes texts on multiple levels of language and discourse. The workshop focused on the utility of Coh-Metrix in discourse theory and educational practice. We…
Descriptors: Discourse Analysis, Workshops, Computational Linguistics, Guidelines