Book Gold Open Access 2023

Modeling Programming Competency: A Qualitative Analysis

Modeling Programming Competency: a Qualitative Analysis
Journal · pp. 1-195
Abstract

This book covers a qualitative study on the programming competencies of novice learners in higher education. To be precise, the book investigates the expected programming competencies within basic programming education at universities and the extent to which the Computer Science curricula fail to provide transparent, observable learning outcomes and assessable competencies. The study analyzes empirical data on 35 exemplary universities' curricula and interviews with experts in the field. The book covers research desiderata, research design and methodology, an in-depth data analysis, and a presentation and discussion of results in the context of programming education. Addressing programming competency in such great detail is essential due to the increasing relevance of computing in today’s society and the need for competent programmers who will help shape our future. Although programming is a core tier of computing and many related disciplines, learning how to program can be challenging in higher education, and many students fail in introductory programming. The book aims to understand what programming means, what programming competency encompasses, and what teachers expect of novice learners. In addition, it illustrates the cognitive complexity of programming as an advanced competency, including knowledge, skills, and dispositions in context. So, the purpose is to communicate the breadth and depth of programming competency to educators and learners of programming, including institutions, curriculum designers, and accreditation bodies. Moreover, the book’s goal is to represent how a qualitative research methodology can be applied in the context of computing education research, as the qualitative research paradigm is still an exception in computing education research. The book provides new insights into programming competency. It outlines the components of programming competencies in terms of knowledge, skills, and dispositions and their cognitive complexity according to the CC2020 computing curricula and the Anderson-Krathwohl taxonomy of the cognitive domain. These insights are essential as programming constitutes one of the most relevant competencies in all computing study programs. In addition, being able to program describes the capability of solving problems, which is also a core competency in today’s increasingly digitalized society. In particular, the book reveals the great relevance of dispositions and other competency components in programming education, which curricula currently fail to recognize and specify. In addition, the book outlines the resulting implications for higher education institutions, educators, and student expectations. Yet another result of interest to graduate students is the multi-method study design that allows for the triangulation of data and results. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

Author Keywords

Computer science Computing education Competency Competency-based education Qualitative content analysis Programming education introductory programming programming competency dispositions Basic programming education Competency Modeling Curricula Analysis Curricula Design Guided Interviews Learning objectives Learning Programming Novice programmer University curricula

Index Keywords

Teaching Curricula Engineering education Competency Education computing Students Curricula design Computing education competency-based education Content analysis Accreditation Computer programming Information systems Disposition Programming education Competency model Learning objectives Data handling Basic programming education Curriculum analyze Guided interview Introductory programming Learning programming Novice programmer Programming competency Qualitative content analyze University curricula
Author Affiliations
Frankfurt am Main, Frankfurt am Main, Hessen, Germany
Funding & Acknowledgements
No funding information
References 10 References
1 A Taxonomy for Learning Teaching and Assessing A Revision of Bloom S Taxonomy of Educational Objectives, (2001)
2 Taxonomie Von Unterrichtsmethoden Ein Pladoyer Fur Didaktische Vielfalt, (2011)
3 Biggs, John B., Enhancing teaching through constructive alignment, Higher Education, 32, 3, pp. 347-364, (1996)
4 Teaching for Quality Learning at University, (1999)
5 Handbook I the Cognitive Domain, (1956)
6 Kompetenzmodellierung Und Instrumente Der Kompetenzerfassung Im Hochschulsektor, (2020)
7 Keycit 2014 Key Competencies Informatics ICT, (2015)
8 Computing Curricula 2020 Paradigms for Global Computing Education, (2020)
9 Danielsiek, Holger, Competency-based design recommendations for Computer Science tutor training courses, Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI), 275, pp. 241-254, (2017)
10 Journal of Educational Computing Research, (1986)
Quick Actions
Full Text via DOI
Citation Metrics
10
Times Cited (Scopus)

References 10
Document Identifiers