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Prasoon Patidar; Tricia J. Ngoon; Neeharika Vogety; Nikhil Behari; Chris Harrison; John Zimmerman; Amy Ogan; Yuvraj Agarwal – Journal of Learning Analytics, 2024
Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…
Descriptors: Learning Analytics, Classroom Observation Techniques, Data Analysis, Student Behavior
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Faucon, Louis; Olsen, Jennifer K.; Haklev, Stian; Dillenbourg, Pierre – Journal of Learning Analytics, 2020
In classrooms, some transitions between activities impose (quasi-)synchronicity, meaning there is a need for learners to move between activities at the same time. To make real-time decisions about when to move to the next activity, teachers need to be able to balance the progress of their students as they work at different paces. In this paper, we…
Descriptors: Classroom Techniques, Prediction, Learning Activities, Student Behavior
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Krumm, Andrew E.; Beattie, Rachel; Takahashi, Sola; D'Angelo, Cynthia; Feng, Mingyu; Cheng, Britte – Journal of Learning Analytics, 2016
This paper outlines the development of practical measures of productive persistence using digital learning system data. Practical measurement refers to data collection and analysis approaches originating from improvement science; productive persistence refers to the combination of academic and social mindsets as well as learning behaviours that…
Descriptors: Measurement, Persistence, Electronic Learning, Data Analysis
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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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Douglas, Kerrie A.; Bermel, Peter; Alam, Md Monzurul; Madhavan, Krishna – Journal of Learning Analytics, 2016
MOOCs attract a large number of learners with largely unknown diversity in terms of motivation, ability, and goals. To understand more about learners in highly technical engineering MOOCs, this study investigates patterns of learners' (n = 337) behaviour and performance in the Nanophotonic Modelling MOOC, offered through nanoHUB-U. The authors…
Descriptors: Online Courses, Large Group Instruction, Distance Education, Technology Uses in Education
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Epp, Carrie Demmans; Phirangee, Krystle; Hewitt, Jim – Journal of Learning Analytics, 2017
Identifying which online behaviours and interactions are associated with student perceptions of being supported will enable a deeper understanding of how those activities contribute to learning experiences. Student language is one aspect of their interaction in need of greater exploration within discourse-based online learning environments. As a…
Descriptors: Student Behavior, Computer Mediated Communication, Form Classes (Languages), Language Usage
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Dvorak, Tomas; Jia, Miaoqing – Journal of Learning Analytics, 2016
This study analyzes the relationship between students' online work habits and academic performance. We utilize data from logs recorded by a course management system (CMS) in two courses at a small liberal arts college in the U.S. Both courses required the completion of a large number of online assignments. We measure three aspects of students'…
Descriptors: Online Courses, Educational Technology, Study Habits, Academic Achievement
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Lowes, Susan; Lin, Peiyi; Kinghorn, Brian – Journal of Learning Analytics, 2015
As enrolment in online courses has grown and LMS data has become accessible for analysis, researchers have begun to examine the link between in-course behaviours and course outcomes. This paper explores the use of readily available LMS data generated by approximately 700 students enrolled in the 12 online courses offered by Pamoja Education, the…
Descriptors: Integrated Learning Systems, Student Behavior, Online Courses, Asynchronous Communication