Implicit Theories of Programming Aptitude as a Barrier to Learning to Code: Are They Distinct from Intelligence?

Scott, Michael ORCID: https://orcid.org/0000-0002-6803-1490 and Ghinea, Gheorghita (2013) Implicit Theories of Programming Aptitude as a Barrier to Learning to Code: Are They Distinct from Intelligence? In: Proceedings of the 18th ACM Conference on Innovation and Technology in Computer Science Education, July 1-3, 2013, Canterbury, UK.

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Abstract / Summary

Contemporary psychology has shown that self-theories can have a profound influence on affect and behavior. Entity-theorists, believing their traits are fixed, adopt maladaptive learning strategies in the face of difficulty. In contrast,incremental-theorists, believing their qualities can change, often adopt mastery-orientated strategies. However, can this concept be domain-specific? This poster presentation challenges the notion of a single dominant mindset. People can nurture a variety of beliefs about different traits, so in the minds of learners, programming aptitude may not be the same as intelligence. The results from a confirmatory factor analysis of 94 responses to an undergraduate programming experience survey indicate that beliefs towards aptitude are empirically distinct from those towards intelligence, suggesting that alternate self-traits should be considered when extending self-theories into specific domains.

Item Type:	Conference or Workshop Item (Poster)
Subjects:	Computer Science, Information & General Works Education
Courses by Department:	The Games Academy > Computing for Games
Depositing User:	Michael Scott
Date Deposited:	06 Oct 2015 15:06
Last Modified:	11 Nov 2022 16:33
URI:	https://falmouth-test.eprints-hosting.org/id/eprint/1649

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