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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
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
Kivimäki, Ville; Pesonen, Joonas; Romanoff, Jani; Remes, Heikki; Ihantola, Petri – Journal of Learning Analytics, 2019
The collection and selection of the data used in learning analytics applications deserve more attention. Optimally, selection of data should be guided by pedagogical purposes instead of data availability. Using design science research methodology, we designed an artifact to collect time-series data on students' self-regulated learning and…
Descriptors: Concept Mapping, Diaries, Data Collection, Independent Study
Mangaroska, Katerina; Sharma, Kshitij; Gaševic, Dragan; Giannakos, Michalis – Journal of Learning Analytics, 2020
Programming is a complex learning activity that involves coordination of cognitive processes and affective states. These aspects are often considered individually in computing education research, demonstrating limited understanding of how and when students learn best. This issue confines researchers to contextualize evidence-driven outcomes when…
Descriptors: Learning Analytics, Data Collection, Instructional Design, Learning Modalities
Chen, Bodong – Journal of Learning Analytics, 2015
In this commentary on Van Leeuwen (2015, this issue), I explore the relation between theory and practice in learning analytics. Specifically, I caution against adhering to one specific theoretical doctrine while ignoring others, suggest deeper applications of cognitive load theory to understanding teaching with analytics tools, and comment on…
Descriptors: Data Collection, Data Analysis, Theory Practice Relationship, Learning Theories
Dowell, Nia M. M.; Graesser, Arthur C. – Journal of Learning Analytics, 2014
An emerging trend toward computer-mediated collaborative learning environments promotes lively exchanges between learners in order to facilitate learning. Discourse can play an important role in enhancing epistemology, pedagogy, and assessments in these environments. In this paper, we highlight some of our recent work showing the advantages using…
Descriptors: Cognitive Processes, Affective Behavior, Computational Linguistics, Intelligent Tutoring Systems
van Leeuwen, Anouschka – Journal of Learning Analytics, 2015
Learning analytics (LA) are summaries, visualizations, and analyses of student data that could improve learning in multiple ways, for example by supporting teachers. However, not much research is available yet concerning how LA may support teachers to diagnose student progress and to intervene during student learning activities. There is evidence…
Descriptors: Data Collection, Data Analysis, Student Evaluation, Cognitive Processes