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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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Wenyi Lu; Joseph Griffin; Troy D. Sadler; James Laffey; Sean P. Goggins – Journal of Learning Analytics, 2025
Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…
Descriptors: Game Based Learning, Predictor Variables, Evaluation Methods, Educational Games
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Wise, Alyssa Friend; Shaffer, David Williamson – Journal of Learning Analytics, 2015
It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…
Descriptors: Learning Theories, Predictor Variables, Data, Data Analysis
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Khosravi, Hassan; Shabaninejad, Shiva; Bakharia, Aneesha; Sadiq, Shazia; Indulska, Marta; Gasevic, Dragan – Journal of Learning Analytics, 2021
Learning analytics dashboards commonly visualize data about students with the aim of helping students and educators understand and make informed decisions about the learning process. To assist with making sense of complex and multidimensional data, many learning analytics systems and dashboards have relied strongly on AI algorithms based on…
Descriptors: Learning Analytics, Visual Aids, Artificial Intelligence, Information Retrieval
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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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Ye, Cheng; Biswas, Gautam – Journal of Learning Analytics, 2014
Our project is motivated by the early dropout and low completion rate problem in MOOCs. We have extended traditional features for MOOC analysis with richer and higher granularity information to make more accurate predictions of dropout and performance. The results show that finer-grained temporal information increases the predictive power in the…
Descriptors: Large Group Instruction, Online Courses, Educational Technology, Technology Uses in Education
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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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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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Colthorpe, Kay; Zimbardi, Kirsten; Ainscough, Louise; Anderson, Stephen – Journal of Learning Analytics, 2015
It is well established that a student's capacity to regulate his or her own learning is a key determinant of academic success, suggesting that interventions targeting improvements in self-regulation will have a positive impact on academic performance. However, to evaluate the success of such interventions, the self-regulatory characteristics of…
Descriptors: Data Analysis, Data Collection, Educational Research, Self Control
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Papamitsiou, Zacharoula; Economides, Anastasios A. – Journal of Learning Analytics, 2014
Accurate and early predictions of student performance could significantly affect interventions during teaching and assessment, which gradually could lead to improved learning outcomes. In our research, we seek to identify and formalize temporal parameters as predictors of performance ("temporal learning analytics" or TLA) and examine…
Descriptors: Time Factors (Learning), Predictor Variables, Student Behavior, Academic Achievement