Measuring the cognitive load of learning to program: A replication study

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

6 Sitaatiot (Scopus)
138 Lataukset (Pure)


Cognitive load (CL) on a learner's working memory has emerged as an influential concept in computing education and beyond. CL is commonly divided in at least two components, intrinsic load (IL) and extraneous load (EL). We seek progress on two questions: (1) How can CL components be measured in the programming domain? (2) How should CL measurement deal with the "third component"of germane load (GL)? We replicate two studies: Morrison and colleagues' [49] evaluation of a questionnaire for self-assessing CL in programming, which is an adaptation of a generic instrument; and Jiang and Kalyuga's [24] study, which found support for a two-component measure of CL in language learning, with GL redundant. We crowd-sourced CL data using Morrison's questions at the end of a video tutorial on programming for beginners. A confirmatory factor analysis found strong support for a three-factor model, with factors matching the items intended to capture IL, EL, and GL, respectively. A two-factor model with IL-targeting and GL-targeting items combined gave a poorer fit. Our findings strengthen the claims of discriminant validity and internal reliability for Morrison's CL questionnaire for programming; construct validity for GL remains open, however. We affirm the need for further research on the two-component theory of CL and the sensitivity of CL self-assessments to contextual factors.

OtsikkoUKICER 2020 - Proceedings of the 2020 Conference on United Kingdom and Ireland Computing Education Research
ISBN (elektroninen)9781450388498
DOI - pysyväislinkit
TilaJulkaistu - 3 syysk. 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaUnited Kingdom and Ireland Computing Education Research Conference - Online, Glasgow, Iso-Britannia
Kesto: 3 syysk. 20204 syysk. 2020


ConferenceUnited Kingdom and Ireland Computing Education Research Conference


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