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Showing 1 to 15 of 18 results Save | Export
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René Lobo-Quintero; Roberto Sánchez-Reina; Davinia Hernández-Leo – Journal of Learning Analytics, 2024
Computer-Supported Collaborative Learning (CSCL) is recognized as an effective methodology for fostering social interaction mediated by technology in ways that potentially trigger learning. The successful implementation of CSCL hinges on factors such as the scripting mechanics for activity sequencing proposed by Collaborative Learning Flow…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Learner Engagement, Student Participation
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Pankaj Chejara; Luis P. Prieto; Yannis Dimitriadis; Maria Jesus Rodriguez-Triana; Adolfo Ruiz-Calleja; Reet Kasepalu; Shashi Kant Shankar – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) research has shown the feasibility of building automated models of collaboration quality using artificial intelligence (AI) techniques (e.g., supervised machine learning (ML)), thus enabling the development of monitoring and guiding tools for computer-supported collaborative learning (CSCL). However, the…
Descriptors: Learning Analytics, Attribution Theory, Acoustics, Artificial Intelligence
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Bertrand Schneider; Gahyun Sung – Journal of Learning Analytics, 2024
Over the last decade, the prevalence of online learning has dramatically increased. As part of their curriculum, students are expected to spend more and more time watching videos. These videos tend to follow a widespread format: a screen recording of slides with a picture-in-picture (PiP) image of the instructor's face. While this format is…
Descriptors: Visual Aids, Nonverbal Communication, Human Body, Computer Assisted Instruction
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Shihui Feng; David Gibson; Dragan Gaševic – Journal of Learning Analytics, 2025
Understanding students' emerging roles in computer-supported collaborative learning (CSCL) is critical for promoting regulated learning processes and supporting learning at both individual and group levels. However, it has been challenging to disentangle individual performance from group-based deliverables. This study introduces new learning…
Descriptors: Computer Assisted Instruction, Cooperative Learning, Student Role, Learning Analytics
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Cukurova, Mutlu; Khan-Galaria, Madiha; Millán, Eva; Luckin, Rose – Journal of Learning Analytics, 2022
One-to-one online tutoring provided by human tutors can improve students' learning outcomes. However, monitoring the quality of such tutoring is a significant challenge. In this paper, we propose a learning analytics approach to monitoring online one-to-one tutoring quality. The approach analyzes teacher behaviours and classifies tutoring sessions…
Descriptors: Learning Analytics, Tutoring, Educational Quality, Behavior Patterns
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Zhang Yingbin; Paquette, Luc; Baker, Ryan S.; Ocumpaugh, Jaclyn; Bosch, Nigel; Biswas, Gautam; Munshi, Anabil – Journal of Learning Analytics, 2021
Confusion may benefit learning when it is resolved or partially resolved. Metacognitive strategies (MS) may help learners to resolve confusion when it occurs during learning and problem solving. This study examined the relationship between confusion and MS that students evoked in Betty's Brain, a computer-based learning-by-modelling environment…
Descriptors: Metacognition, Brain, Grade 6, Emotional Response
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Yiqiu Zhou; Jina Kang – Journal of Learning Analytics, 2023
Collaboration is a complex, multidimensional process; however, details of how multimodal features intersect and mediate group interactions have not been fully unpacked. Characterizing and analyzing the temporal patterns based on multimodal features is a challenging yet important work to advance our understanding of computer-supported collaborative…
Descriptors: Attention Control, Cooperative Learning, Data Analysis, Computer Assisted Instruction
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Lämsä, Joni; Uribe, Pablo; Jiménez, Abelino; Caballero, Daniela; Hämäläinen, Raija; Araya, Roberto – Journal of Learning Analytics, 2021
Scholars have applied automatic content analysis to study computer-mediated communication in computer-supported collaborative learning (CSCL). Since CSCL also takes place in face-to-face interactions, we studied the automatic coding accuracy of manually transcribed face-to-face communication. We conducted our study in an authentic higher-education…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Synchronous Communication, Learning Analytics
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Ostrow, Korinn S.; Wang, Yan; Heffernan, Neil T. – Journal of Learning Analytics, 2017
Data is flexible in that it is molded by not only the features and variables available to a researcher for analysis and interpretation, but also by how those features and variables are recorded and processed prior to evaluation. "Big Data" from online learning platforms and intelligent tutoring systems is no different. The work presented…
Descriptors: Data, Comparative Analysis, Scoring, Mathematics Skills
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Porter, Tenelle; Molina, Diego Catalán; Blackwell, Lisa; Roberts, Sylvia; Quirk, Abigail; Duckworth, Angela L.; Trzesniewski, Kali – Journal of Learning Analytics, 2020
Mastery behaviours -- seeking out challenging tasks and continuing to work on them despite difficulties -- are integral to achievement but difficult to measure with precision. The current study reports on the development and validation of the computer-based persistence, effort, resilience, and challenge-seeking (PERC) task in two demographically…
Descriptors: Mastery Learning, Resilience (Psychology), Difficulty Level, Computer Assisted Instruction
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Brinkhuis, Matthieu J. S.; Savi, Alexander O.; Hofman, Abe D.; Coomans, Frederik; van der Maas, Han L. J.; Maris, Gunter – Journal of Learning Analytics, 2018
With the advent of computers in education, and the ample availability of online learning and practice environments, enormous amounts of data on learning become available. The purpose of this paper is to present a decade of experience with analyzing and improving an online practice environment for math, which has thus far recorded over a billion…
Descriptors: Data Analysis, Mathematics Instruction, Accuracy, Reaction Time
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Reich, Justin; Tingley, Dustin; Leder-Luis, Jetson; Roberts, Margaret E.; Stewart, Brandon M. – Journal of Learning Analytics, 2015
Dealing with the vast quantities of text that students generate in Massive Open Online Courses (MOOCs) and other large-scale online learning environments is a daunting challenge. Computational tools are needed to help instructional teams uncover themes and patterns as students write in forums, assignments, and surveys. This paper introduces to the…
Descriptors: Large Group Instruction, Online Courses, Data Collection, Data Analysis
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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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Knight, Simon; Littleton, Karen – Journal of Learning Analytics, 2015
There is an increasing interest in developing learning analytic techniques for the analysis, and support of, high-quality learning discourse. This paper maps the terrain of discourse-centric learning analytics (DCLA), outlining the distinctive contribution of DCLA and outlining a definition for the field moving forwards. It is our claim that DCLA…
Descriptors: Discourse Analysis, Outcomes of Education, Data Analysis, Language Usage
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Sonnenberg, Christoph; Bannert, Maria – Journal of Learning Analytics, 2015
According to research examining self-regulated learning (SRL), we regard individual regulation as a specific sequence of regulatory activities. Ideally, students perform various learning activities, such as analyzing, monitoring, and evaluating cognitive and motivational aspects during learning. Metacognitive prompts can foster SRL by inducing…
Descriptors: Metacognition, Cues, Control Groups, Outcomes of Education
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