Addison Wesley's Review for the Computer Science AP Exam in C++
Addison Wesley's Review for the Computer Science AP Exam in C++
How to Prepare for the AP Computer Science Exam
How to Prepare for the AP Computer Science Exam
From Limen to Lumen: computing students in liminal spaces
Proceedings of the third international workshop on Computing education research
Empirical evidence for the existence and uses of metacognition in computer science problem solving
Proceedings of the 41st ACM technical symposium on Computer science education
Peerwise: replication study of a student-collaborative self-testing web service in a u.s. setting
Proceedings of the 41st ACM technical symposium on Computer science education
Motivating online collaborative learning
Proceedings of the fifteenth annual conference on Innovation and technology in computer science education
ITiCSE 2010 working group report motivating our top students
Proceedings of the 2010 ITiCSE working group reports
PeerWise: exploring conflicting efficacy studies
Proceedings of the seventh international workshop on Computing education research
Gaps between industry expectations and the abilities of graduates
Proceeding of the 44th ACM technical symposium on Computer science education
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This paper describes an empirical study that investigates the knowledge that Computer Science students have about the extent of their own previous learning. The study compares self-generated estimates of performance with actual performance on a data structures quiz taken by undergraduate students in courses requiring data structures as a pre-requisite. The study is contextualized and grounded within a research paradigm in Psychology called calibration of knowledge that suggests that self-knowledge across a range of disciplines is highly unreliable. Such self-knowledge is important because of its role in meta-cognition, particularly in cognitive self-regulation and monitoring. It is also important because of the credence that faculty give to student self-reports. Our results indicate that Computer Science student self-estimates correlate moderately with their performance on a quiz, more so for estimates provided after they have taken the quiz than before. The pedagogical implications are that students should be provided with regular opportunities for empirical validation of their knowledge as well as being taught the metacognitive skills of regular self-testing in order to overcome validation bias.