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ERIC Number: EJ833969
Record Type: Journal
Publication Date: 2005-Dec
Pages: 19
Abstractor: As Provided
Reference Count: 22
ISBN: N/A
ISSN: ISSN-0899-3408
Knowing What I Know: An Investigation of Undergraduate Knowledge and Self-Knowledge of Data Structures
Tenenberg, Josh; Murphy, Laurie
Computer Science Education, v15 n4 p297-315 Dec 2005
This paper describes an empirical study that investigated the knowledge that Computer Science students have about the extent of their own previous learning. The study compared self-generated estimates of performance with actual performance on a data structures quiz taken by undergraduate students in courses requiring data structures as a prerequisite. The study was 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, as well as in the credence that instructors give to student self-reports. Our results indicated that Computer Science student self-estimates are highly correlated with performance, more so for estimates provided after the performance than before. This high level of calibration, however, was likely the result of a number of conditions that do not always hold: that the students already had domain expertise, that the quiz had unambiguous and verifiable answers, and that students expected their estimates to be validated. When these conditions are not met, it becomes more important for students to have direct feedback about their performance so as to uncover those areas where their intuitions might mislead them. Students also had weak knowledge about their standing relative to their peers, particularly those in the lower performance quartiles, exhibiting the well known "better-than-average" heuristic. There was, additionally, no correlation between calibration ability and degree of liking or difficulty with the data structures material, suggesting that instructors and researchers should not treat liking or difficulty as reliable indicators of the learning that has occurred. (Contains 1 note, 4 tables and 4 figures.)
Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Washington