Programming Pluralism: Using Learning Analytics to Detect Patterns in the Learning of Computer Programming

New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful...

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Bibliographic Details
Published in:	The Journal of the learning sciences Vol. 23; no. 4; pp. 561 - 599
Main Authors:	Blikstein, Paulo, Worsley, Marcelo, Piech, Chris, Sahami, Mehran, Cooper, Steven, Koller, Daphne
Format:	Journal Article
Language:	English
Published:	Philadelphia Routledge 02.10.2014 Taylor & Francis Group Taylor & Francis Ltd
Subjects:	Academic Achievement Achievement Rating Algorithms Artificial intelligence Assignments Automation Behavior Change Cluster Grouping Coding Cognitive Style Cohort Analysis Computation Computer programming Computer Science Education Computers Correlation Data Analysis Data Collection Educational evaluation Educational Experiments Graduate Students Introductory Courses Learning Learning Analytics Learning Processes Pattern Recognition Predictive Measurement Predictive Validity Programming Protocol Analysis Regression (Statistics) Student Behavior Student Centered Learning Technology education Undergraduate Students
ISSN:	1050-8406, 1532-7809
Online Access:	Get full text
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