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Article: Modelling programming performance: Beyond the influence of learner characteristics

TitleModelling programming performance: Beyond the influence of learner characteristics
Authors
KeywordsImproving classroom teaching
Pedagogical issues
Programming and programming languages
Secondary education
Teaching/learning strategies
Issue Date2011
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/compedu
Citation
Computers And Education, 2011, v. 57 n. 1, p. 1202-1213 How to Cite?
AbstractIn the 21st century, the ubiquitous nature of technology today is evident and to a large extent, most of us benefit from the modern convenience brought about by technology. Yet to be technology literate, it is argued that learning to program still plays an important role. One area of research in programming concerns the identification of predictors of programming success. Previous studies have identified a number of predictors. This study examined the effect of a combination of predictors (gender, learning styles, mental models, prior composite academic ability, and medium of instruction) on programming performance. Data were collected anonymously through a website from 131 secondary school students in Hong Kong who opted for computer programming in the Computer and Information Technology curriculum. Partial Least Squares (PLS) modelling was used to test a hypothesized theoretical structural model. All of the five aforementioned variables were either direct or indirect predictors of programming performance and the antecedents accounted for 43.6% of the variance in programming performance. While this study shows the influence of learner characteristics such as gender, learning styles, and mental models on programming performance, it highlights the effect that prior composite academic ability and medium of instruction exert on learning outcomes, which is uncommon among studies of similar purpose. These findings have significant implications for policy makers and educators alike. © 2011 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/137585
ISSN
2015 Impact Factor: 2.881
2015 SCImago Journal Rankings: 3.143
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorLau, WWFen_HK
dc.contributor.authorYuen, AHKen_HK
dc.date.accessioned2011-08-26T14:28:15Z-
dc.date.available2011-08-26T14:28:15Z-
dc.date.issued2011en_HK
dc.identifier.citationComputers And Education, 2011, v. 57 n. 1, p. 1202-1213en_HK
dc.identifier.issn0360-1315en_HK
dc.identifier.urihttp://hdl.handle.net/10722/137585-
dc.description.abstractIn the 21st century, the ubiquitous nature of technology today is evident and to a large extent, most of us benefit from the modern convenience brought about by technology. Yet to be technology literate, it is argued that learning to program still plays an important role. One area of research in programming concerns the identification of predictors of programming success. Previous studies have identified a number of predictors. This study examined the effect of a combination of predictors (gender, learning styles, mental models, prior composite academic ability, and medium of instruction) on programming performance. Data were collected anonymously through a website from 131 secondary school students in Hong Kong who opted for computer programming in the Computer and Information Technology curriculum. Partial Least Squares (PLS) modelling was used to test a hypothesized theoretical structural model. All of the five aforementioned variables were either direct or indirect predictors of programming performance and the antecedents accounted for 43.6% of the variance in programming performance. While this study shows the influence of learner characteristics such as gender, learning styles, and mental models on programming performance, it highlights the effect that prior composite academic ability and medium of instruction exert on learning outcomes, which is uncommon among studies of similar purpose. These findings have significant implications for policy makers and educators alike. © 2011 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_US
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/compeduen_HK
dc.relation.ispartofComputers and Educationen_HK
dc.subjectImproving classroom teachingen_HK
dc.subjectPedagogical issuesen_HK
dc.subjectProgramming and programming languagesen_HK
dc.subjectSecondary educationen_HK
dc.subjectTeaching/learning strategiesen_HK
dc.titleModelling programming performance: Beyond the influence of learner characteristicsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0360-1315&volume=57&issue=1&spage=1202&epage=1213&date=2011&atitle=Modelling+programming+performance:+beyond+the+influence+of+learner+characteristicsen_US
dc.identifier.emailLau, WWF: wwflau@hku.hken_HK
dc.identifier.emailYuen, AHK: hkyuen@hku.hken_HK
dc.identifier.authorityLau, WWF=rp01723en_HK
dc.identifier.authorityYuen, AHK=rp00983en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.compedu.2011.01.002en_HK
dc.identifier.scopuseid_2-s2.0-79251623914en_HK
dc.identifier.hkuros189898en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79251623914&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume57en_HK
dc.identifier.issue1en_HK
dc.identifier.spage1202en_HK
dc.identifier.epage1213en_HK
dc.identifier.isiWOS:000289396000012-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridLau, WWF=26648932200en_HK
dc.identifier.scopusauthoridYuen, AHK=8983762600en_HK
dc.identifier.citeulike8611586-

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