Towards a Competency Model for Teaching Computer Science

Bender, Elena; Hubwieser, Peter; Schaper, Niclas; Margaritis, Melanie; Berges, Marc; Ohrndorf, Laura; Magenheim, Johannes; Schubert, Sigrid

doi:10.1080/0161956x.2015.1068082

Cited by 22 publications

(7 citation statements)

References 23 publications

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“…This initiative received approximately €7 million in funding. 12 Initial findings of KoKoHs and ASCOT were published in 2014 and 2015. Both programmes were treated as the first sections of a far-reaching research project, and were exclusively devoted to test development.…”

Section: Procedures For Ensuring Content Validitymentioning

confidence: 99%

Ensuring content validity of psychological and educational tests – the role of experts

Beck

2020

FLR

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Many test developers try to ensure the content validity of their tests by having external experts review the items, e.g. in terms of relevance, difficulty, or clarity. Although this approach is widely accepted, a closer look reveals several pitfalls need to be avoided if experts' advice is to be truly helpful. The purpose of this paper is to exemplarily describe and critically analyse widespread practices of involving experts to ensure the content validity of tests. First, I offer a classification of tasks that experts are given by test developers, as reported on in the respective literature. Second, taking an exploratory approach by means of a qualitative meta-analysis, I review a sample of reports on test development (N = 72) to identify the common current procedures for selecting and consulting experts. Results indicate that often the choice of experts seems to be somewhat arbitrary, the questions posed to experts lack precision, and the methods used to evaluate experts' feedback are questionable. Third, given these findings I explore in more depth what prerequisites are necessary for their contributions to be useful in ensuring the content validity of tests. Main results are (i) that test developers, contrary to some practice, should not ask for information that they can reliably ascertain themselves ("truth-apt statements"). (ii) Average values from the answers of the experts which are often calculated rarely provide reliable information about the quality of test items or a test. (iii) Making judgements about some aspects of the quality of test items (e.g. comprehensibility, plausibility of distractors) could lead experts to unreliable speculations. (iv)When several experts respond by giving incompatible or even contradictory answers, there is almost always no criterion enabling a decision between them. In conclusion, explicit guidelines on this matter need to be elaborated and standardised (above all, by the AERA, APA, and NCME "Standards").

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Section: Procedures For Ensuring Content Validitymentioning

confidence: 99%

Ensuring content validity of psychological and educational tests – the role of experts

Beck

2020

FLR

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“…They describe empirical validation of their competency model using qualitative text analysis. Bender et al [18] discuss the development of a similar model and discuss issues relating to validating the model. Asghar and Luxton-Reilly [16] report a case study of the design of a curriculum informed by a competency based framework proposed by a recent ITiCSE working group on Cybersecurity education [44].…”

Section: Curriculum Validationmentioning

confidence: 99%

Designing Dissemination and Validation of a Framework for Teaching Cloud Fundamentals

Paterson

Adams

White

et al. 2021

Proceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education

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Three previous Working Groups (WGs) met at ITiCSE conferences to explore ways to help educators incorporate cloud computing into their courses and curricula by mapping industry job skills to knowledge areas (KAs). These WGs identified, organized, and grouped together student learning objectives (LOs) and developed these KAs and LOs in a repository of learning materials and course exemplars. * Leader Approaches to validating that a cloud computing course designed around the KAs and LOs can meet the needs of industry have been outlined with further iterations being considered. A research plan has been designed for a study to be implemented over the coming year in order to perform this validation.

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“…(2015) proposed a five-dimension competency model of CS PCK which included subject and curriculum related issues, teaching methods and use of media, learner-related issues, teacher-related issues, and issues of the educational system. Although the model provides a framework for evaluating CS teachers’ PCK, concrete measurement instruments and empirical studies are needed to validate it (Bender et al., 2015).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Their results indicated that there is limited understanding about the knowledge teachers should have to teach programming and suggested that more research is needed. In another paper, Bender et al (2015) proposed a five-dimension competency model of CS PCK which included subject and curriculum related issues, teaching methods and use of media, learner-related issues, teacher-related issues, and issues of the educational system. Although the model provides a framework for evaluating CS teachers' PCK, concrete measurement instruments and empirical studies are needed to validate it (Bender et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Teachers’ Perceptions of Student Misconceptions in Introductory Programming

Qian

Hambrusch

Yadav

et al. 2019

Journal of Educational Computing Research

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A quality computer science (CS) teacher needs to understand students’ common misconceptions in learning CS. This study explored one aspect of CS teachers’ understanding of student misconceptions: their perceptions of student misconceptions related to introductory programming. Perceptions in this study included three parts: teachers’ perceived frequency of a student misconception, teachers’ perceived importance of a misconception in learning, and teachers’ confidence in addressing a misconception. Teachers in our study taught a Python-based CS course for high schools students. A survey was designed and administered to assess teachers’ perceptions of students’ misconceptions. Our results indicated that teachers’ confidence of addressing misconceptions and the teaching context may affect their perceptions of student misconceptions. We also found that some latent misconceptions are likely to lead to a perception of low frequency as they can be more difficult to detect. Moreover, our study found that teachers’ degrees and additional computing training showed positive relationships with their confidence of addressing student misconceptions and that additional computing training also showed a positive relationship with teachers’ perceived importance of student misconceptions. Implications of the findings for future research and practice of CS education are discussed.

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Towards a Competency Model for Teaching Computer Science

Cited by 22 publications

References 23 publications

Ensuring content validity of psychological and educational tests – the role of experts

Ensuring content validity of psychological and educational tests – the role of experts

Designing Dissemination and Validation of a Framework for Teaching Cloud Fundamentals

Teachers’ Perceptions of Student Misconceptions in Introductory Programming

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