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Yueqiao Jin; Vanessa Echeverria; Lixiang Yan; Linxuan Zhao; Riordan Alfredo; Yi-Shan Tsai; Dragan Gasevic; Roberto Martinez-Maldonado – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) integrates novel sensing technologies and artificial intelligence algorithms, providing opportunities to enhance student reflection during complex, collaborative learning experiences. Although recent advancements in MMLA have shown its capability to generate insights into diverse learning behaviours across…
Descriptors: Learning Analytics, Accountability, Ethics, Artificial Intelligence
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Mallavarapu, Aditi; Lyons, Leilah; Uzzo, Stephen – Journal of Learning Analytics, 2022
Large-group (n > 8) co-located collaboration has not been adequately studied because it demands different conceptual framings than those used to study small-group collaboration, while also posing pragmatic constraints on data collection. Working within these pragmatic constraints, we use video data to devise an indicator of the current…
Descriptors: Social Networks, Network Analysis, Cooperative Learning, Data Collection
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Hoppe, H. Ulrich – Journal of Learning Analytics, 2015
This commentary elaborates on the role of "grounding" as a focal theoretical concept and aims to contextualize the claims formulated by Schneider and Pea (2015, this issue) in previous CSCL discussions. It provides fingerposts for enriching and refining the concept of grounding from a pedagogical point of view. It also suggests using the…
Descriptors: Eye Movements, Interaction, Cooperative Learning, Semantics
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Sharma, Kshitij; Chavez-Demoulin, Valérie; Dillenbourg, Pierre – Journal of Learning Analytics, 2017
The statistics used in education research are based on central trends such as the mean or standard deviation, discarding outliers. This paper adopts another viewpoint that has emerged in statistics, called extreme value theory (EVT). EVT claims that the bulk of normal distribution is comprised mainly of uninteresting variations while the most…
Descriptors: Foreign Countries, Educational Research, Statistical Distributions, Theories
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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
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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
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Halatchliyski, Iassen; Hecking, Tobias; Göhnert, Tilman; Hoppe, H. Ulrich – Journal of Learning Analytics, 2014
This paper introduces the scientometric method of main path analysis and its application in an exemplary study of the paths of knowledge development and the roles of contributors in Wikiversity. Data from two scientific domains in this online learning community has been used. We see this as a step forward in adapting and adopting network analysis…
Descriptors: Path Analysis, Knowledge Level, Communities of Practice, Computer Mediated Communication
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Teplovs, Chris – Journal of Learning Analytics, 2015
This commentary reflects on the contributions to learning analytics and theory by a paper that describes how multiple theoretical frameworks were woven together to inform the creation of a new, automated discourse analysis tool. The commentary highlights the contributions of the original paper, provides some alternative approaches, and touches on…
Descriptors: Data Analysis, Data Collection, Theory Practice Relationship, Instructional Design
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Schneider, Bertrand; Pea, Roy – Journal of Learning Analytics, 2015
In a previous study, we found that real-time mutual gaze perception (i.e., being able to see the gaze of your partner in real time on a computer screen while solving a learning task) had a positive effect on student collaboration and learning (Schneider & Pea, 2013). The goals of this paper are (1) to explore a variety of computational…
Descriptors: Eye Movements, Computer Mediated Communication, Discussion (Teaching Technique), Predictor Variables
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Kelly, Nick; Thompson, Kate; Yeoman, Pippa – Journal of Learning Analytics, 2015
This paper describes theory-led design as a way of developing novel tools for learning analytics (LA). It focuses upon the domain of automated discourse analysis (ADA) of group learning activities to help an instructor to orchestrate online groups in real-time. The paper outlines the literature on the development of LA tools within the domain of…
Descriptors: Data Analysis, Data Collection, Computer Assisted Instruction, Cooperative Learning
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Gunnarsson, Bjorn Levi; Alterman, Richard – Journal of Learning Analytics, 2014
Promoting blog content is a social activity--a means of communicating one student's appreciation of another student's work. This article explores the feasibility of using student promotions of content, in a blogosphere, to identify quality content, and implications for students and instructors. We show that students actively and voluntarily…
Descriptors: Electronic Publishing, Web Sites, Diaries, Social Media
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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