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Scott, John; Nichols, T. Philip – Research in Education, 2017
Recently, the possibilities for leveraging "big data" in research and pedagogy have given rise to the growing field of "learning analytics" in online education. While much of this work has focused on quantitative metrics, some have called for critical perspectives that interrogate such data as an interplay between technical…
Descriptors: Learning, Data Analysis, Electronic Learning, Online Courses
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Veerasamy, Ashok Kumar; D'Souza, Daryl; Laakso, Mikko-Jussi – Journal of Educational Technology Systems, 2016
This article presents a study aimed at examining the novice student answers in an introductory programming final e-exam to identify misconceptions and types of errors. Our study used the Delphi concept inventory to identify student misconceptions and skill, rule, and knowledge-based errors approach to identify the types of errors made by novices…
Descriptors: Computer Science Education, Programming, Novices, Misconceptions
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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
Wilson, Sharise Mavis – ProQuest LLC, 2010
The purpose of this project was to explore the decision-making approach and types of data that school psychologists use in determining special education classification. There were three research objectives: (a) to investigate the types of conditions and measures needed to test the use of the representativeness heuristic and assessment data, (b) to…
Descriptors: Research Design, School Psychologists, Heuristics, Difficulty Level