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Download full textSavi, Alexander O.; Deonovic, Benjamin E.; Bolsinova, Maria; van der Maas, Han L. J.; Maris, Gunter K. J. – Journal of Educational Data Mining, 2021
In learning, errors are ubiquitous and inevitable. As these errors may signal otherwise latent cognitive processes, tutors--and students alike--can greatly benefit from the information they provide. In this paper, we introduce and evaluate the Systematic Error Tracing (SET) model that identifies the possible causes of systematically observed…
Descriptors: Learning Processes, Cognitive Processes, Error Patterns, Models
Berens, Johannes; Schneider, Kerstin; Gortz, Simon; Oster, Simon; Burghoff, Julian – Journal of Educational Data Mining, 2019
To successfully reduce student attrition, it is imperative to understand what the underlying determinants of attrition are and which students are at risk of dropping out. We develop an early detection system (EDS) using administrative student data from a state and private university to predict student dropout as a basis for a targeted…
Descriptors: Risk Management, At Risk Students, Dropout Prevention, College Students
Sonnenberg, Christoph; Bannert, Maria – Journal of Educational Data Mining, 2016
In computer-supported learning environments, the deployment of self-regulatory skills represents an essential prerequisite for successful learning. Metacognitive prompts are a promising type of instructional support to activate students' strategic learning activities. However, despite positive effects in previous studies, there are still a large…
Descriptors: Data Analysis, Metacognition, Prompting, Cues
Zimmermann, Judith; Brodersen, Kay H.; Heinimann, Hans R.; Buhmann, Joachim M. – Journal of Educational Data Mining, 2015
The graduate admissions process is crucial for controlling the quality of higher education, yet, rules-of-thumb and domain-specific experiences often dominate evidence-based approaches. The goal of the present study is to dissect the predictive power of undergraduate performance indicators and their aggregates. We analyze 81 variables in 171…
Descriptors: Undergraduate Students, Graduate Students, Academic Achievement, Prediction
Rebolledo-Mendez, Genaro; Du Boulay, Benedict; Luckin, Rosemary; Benitez-Guerrero, Edgard Ivan – Journal of Educational Data Mining, 2013
Tutoring systems are a common tool for delivering educational content and recent advances in this field include the detection of and reaction to learners' motivation. A data set derived from interactions in a tutoring system and its motivationally-aware variant provided opportunities to discover patterns of behavior in connection with motivational…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Student Motivation, Interaction
Gupta, Naman K.; Penstein Rosé, Carolyn – Journal of Educational Data Mining, 2010
As the wealth of information available on the Web increases, Web-based information seeking becomes a more and more important skill for supporting both formal education and lifelong learning. However, Web-based information access poses hurdles that must be overcome by certain student populations, such as low English competency users, low literacy…
Descriptors: Information Seeking, Internet, Mixed Methods Research, Data Analysis
