Towards an Analysis of Program Complexity From a Cognitive Perspective

Duran, Rodrigo; Sorva, Juha; Leite, Sofia

doi:10.1145/3230977.3230986

Cited by 35 publications

(24 citation statements)

References 71 publications

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“…For example, Crk et al [11,12] used EEG (electroencephalography) during program comprehension, while Andrzejewska and Skawińska [2] tracked eye movements and Nourbakhsh et al [51] measured galvanic skin response and eye blinks. Duran et al [14] have proposed CL-inspired methods for analyzing the complexity of computer programs a priori for instructional-design purposes, but the work is so far unsupported by direct empirical evidence.…”

Section: Measurement In Computing Educationmentioning

confidence: 99%

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Measuring the Cognitive Load of Learning to Program: A Replication Study

Zavgorodniaia

Duran

Hellas

et al. 2020

United Kingdom &Amp; Ireland Computing Education Research Conference.

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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 twocomponent 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 twocomponent theory of CL and the sensitivity of CL self-assessments to contextual factors. CCS CONCEPTS• Social and professional topics → Computing education.

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Section: Measurement In Computing Educationmentioning

confidence: 99%

“…In computing education research (CER), CLT has been applied to example-based learning [40,60,70], course design [8,61,66], multimedia and visualizations [46,48,59], novel practice tasks [15,20], and complexity analysis [14], among other things. One review identified CLT as one of CER's more common theories [37].…”

mentioning

confidence: 99%

Measuring the Cognitive Load of Learning to Program: A Replication Study

Zavgorodniaia

Duran

Hellas

et al. 2020

United Kingdom &Amp; Ireland Computing Education Research Conference.

Self Cite

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“…While these questionnaires use metrics that show interesting correlations, richer and robust methods used in personalized learning [2] demand a deeper understanding of how prior experience translates into the comprehension of concepts present in CS1 courses. Recent work towards more reasonable and granular assessment questions [9,24] in CS1 exams points to the importance of knowing in detail the concepts learners are familiar with. Detailed information could be used to set more realistic expectations and design assessment instruments matching learner's ability (as captured by Vygotsky's zone of proximal development [28]), with the difficulty of concrete programs used in assessment instruments [9].…”

Section: Related Workmentioning

confidence: 99%

Towards a Common Instrument for Measuring Prior Programming Knowledge

Duran

Rybicki

Hellas

et al. 2019

Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education

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Computing education researchers and educators use a wide range of approaches for measuring students' prior knowledge in programming. Such measurement can help adapt the learning goals and assessment tools for groups of learners at different skills levels and backgrounds. There seems to be no consensus on if and how prior programming knowledge should be measured. Traditional background surveys are often ad-hoc or non-standard, which do not allow comparison of results between different course contexts, levels, and learner groups. Moreover, surveys may yield inaccurate information and may not be useful due to lack of detail. In contrast, tests can provide much higher detail and accuracy than surveys about student knowledge or skills, but large-scale tests are typically very time-consuming or impractical to arrange. To bridge the gap between ad-hoc surveys and standardized tests, we propose and evaluate a novel self-evaluation instrument for measuring prior programming knowledge in introductory programming courses. This instrument investigates in higher detail typical course concepts in programming education considering the different levels of proficiency. Based on a sample of two thousand introductory programming course students, our analysis shows that the instrument is internally consistent, correlates with traditional background information metrics and identifies students of varying programming backgrounds. CCS CONCEPTS• Social and professional topics → Computer science education; Model curricula; Student assessment.

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“…Podemos citar alguns outros interesses de pesquisa da EC tais como: Psicologia da EC (Duran, Sorva e Leite, 2018), mentoria profissional de graduandos de Computação (Iacob e Faily, 2020), ensino da honestidade acadêmica na Computação (Malan, Yu e Lloyd, 2020), e a influência da língua materna em erros de compilação (Reestman e Dorn, 2019). RBIE v.28 -2020 3 Informática na Educação Não é fácil encontrar definições explícitas e claras na literatura sobre o que seria a Informática na Educação (IE).…”

Section: Educação Em Computaçãounclassified

Tecnologias na Educação em Computação: Primeiros Referenciais

Bispo

Raabe

Matos

et al. 2020

RBIE

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O movimento de pesquisadores de Educação em Computação no Brasil vem promovendo vários espaços de diálogo dentro da Sociedade Brasileira de Computação com diversas áreas da Computação. Uma destas áreas é a Informática na Educação, com a qual estabelece convergências de pesquisa promissoras. Este artigo busca tecer considerações iniciais sobre as convergências entre estas duas áreas: a Educação em Computação e a Informática na Educação, estabelecendo o que chamaremos de Tecnologias na Educação em Computação.

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Towards an Analysis of Program Complexity From a Cognitive Perspective

Cited by 35 publications

References 71 publications

Measuring the Cognitive Load of Learning to Program: A Replication Study

Measuring the Cognitive Load of Learning to Program: A Replication Study

Towards a Common Instrument for Measuring Prior Programming Knowledge

Tecnologias na Educação em Computação: Primeiros Referenciais

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