research-article

Towards a Competence Model for the Novice Programmer Using Bloom's Revised Taxonomy - An Empirical Approach

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Natalie KieslerAuthors Info & Claims

ITiCSE '20: Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education

Pages 459 - 465

https://doi.org/10.1145/3341525.3387419

Published: 15 June 2020 Publication History

Abstract

This work addresses the demand of an empirically developed competence model for programming as challenging core tier of computer science curricula. The presented paper investigates the application of Bloom's revised taxonomy for learning, teaching and assessing by Anderson and Krathwohl for the specification of currently used learning objectives in programming education. Accordingly, 129 module descriptions of beginner level programming courses from 35 German universities constitute the sample. Learning goals are evaluated using Mayring's qualitative content analysis. In addition, seven guided interviews with computer science professors as experts are categorized according to Mayring's qualitative analysis method. As a result, a model comprised of deductively-inductively built cognitive categories is proposed, proving the adequacy of Bloom's revised taxonomy for computer science and programming in particular. The categories depict current operationalized learning objectives and cognitive competencies of novice programmers, as well as additional non-cognitive competencies. Thus, the results can help classify competency levels and support the didactic design of introductory programming classes and assessment. This research also constitutes a basis for the development of a measuring instrument of programming competence in the future.

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Cited By

Gao ZCui CYan HLiu JSun XFeng JStone JYuen TShoop LRebelsky SPrather J(2025)Towards a Quantitative Competency Model for CS1 via Five-Channel Learning SequencesProceedings of the 56th ACM Technical Symposium on Computer Science Education V. 110.1145/3641554.3701837(367-373)Online publication date: 12-Feb-2025
https://dl.acm.org/doi/10.1145/3641554.3701837
Kiesler NOpel SThorbrügge CMonga MLonati VBarendsen ESheard JPaterson J(2024)With Great Power Comes Great Responsibility - Integrating Data Ethics into Computing EducationProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653637(471-477)Online publication date: 3-Jul-2024
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Azaiz IKiesler NStrickroth SMonga MLonati VBarendsen ESheard JPaterson J(2024)Feedback-Generation for Programming Exercises With GPT-4Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653594(31-37)Online publication date: 3-Jul-2024
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Index Terms

Towards a Competence Model for the Novice Programmer Using Bloom's Revised Taxonomy - An Empirical Approach
1. General and reference
  1. Cross-computing tools and techniques
    1. Empirical studies
2. Social and professional topics
  1. Professional topics
    1. Computing education

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ITiCSE '20: Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education

June 2020

615 pages

ISBN:9781450368742

DOI:10.1145/3341525

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NTNU, Norway
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NTNU, Norway

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Cited By

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https://dl.acm.org/doi/10.1145/3641554.3701837
Kiesler NOpel SThorbrügge CMonga MLonati VBarendsen ESheard JPaterson J(2024)With Great Power Comes Great Responsibility - Integrating Data Ethics into Computing EducationProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653637(471-477)Online publication date: 3-Jul-2024
https://dl.acm.org/doi/10.1145/3649217.3653637
Azaiz IKiesler NStrickroth SMonga MLonati VBarendsen ESheard JPaterson J(2024)Feedback-Generation for Programming Exercises With GPT-4Proceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653594(31-37)Online publication date: 3-Jul-2024
https://dl.acm.org/doi/10.1145/3649217.3653594
Lohr DKiesler NKeuning HJeuring JMonga MLonati VBarendsen ESheard JPaterson J(2024)"Let Them Try to Figure It Out First" - Reasons Why Experts (Do Not) Provide Feedback to Novice ProgrammersProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653530(38-44)Online publication date: 3-Jul-2024
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Prather JDenny PLeinonen JBecker BAlbluwi ICraig MKeuning HKiesler NKohn TLuxton-Reilly AMacNeil SPetersen APettit RReeves BSavelka JLaakso MMonga MSimon Sheard J(2023)The Robots Are Here: Navigating the Generative AI Revolution in Computing EducationProceedings of the 2023 Working Group Reports on Innovation and Technology in Computer Science Education10.1145/3623762.3633499(108-159)Online publication date: 22-Dec-2023
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Kiesler NThorbrügge CLaakso MMonga MSimon Sheard J(2023)Socially Responsible Programming in Computing Education and Expectations in the ProfessionProceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 110.1145/3587102.3588839(443-449)Online publication date: 29-Jun-2023
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Kiesler N(2023)Investigating the Use and Effects of Feedback in CodingBat Exercises: An Exploratory Thinking Aloud Study2023 Future of Educational Innovation-Workshop Series Data in Action10.1109/IEEECONF56852.2023.10104622(1-12)Online publication date: 16-Jan-2023
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