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Pardos, Zachary A.; Horodyskyj, Lev – Journal of Learning Analytics, 2019
We introduce a novel approach to visualizing temporal clickstream behaviour in the context of a degree-satisfying online course, "Habitable Worlds," offered through Arizona State University. The current practice for visualizing behaviour within a digital learning environment is to generate plots based on hand-engineered or coded features…
Descriptors: Visualization, Online Courses, Course Descriptions, Data Analysis
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Gardner, Josh; Brooks, Christopher – Journal of Learning Analytics, 2018
Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…
Descriptors: Prediction, Models, Evaluation, Evaluation Methods
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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
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Méndez, Gonzalo; Ochoa, Xavier; Chiluiza, Katherine; de Wever, Bram – Journal of Learning Analytics, 2014
Learning analytics has been as used a tool to improve the learning process mainly at the micro-level (courses and activities). However, another of the key promises of learning analytics research is to create tools that could help educational institutions at the meso- and macro-level to gain better insight into the inner workings of their programs…
Descriptors: Data Analysis, Data Collection, Educational Research, Curriculum Design