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.
Author(s): Natalie Keisler
Publisher: Springer
Year: 2023
Language: English
Pages: 291
Foreword
Preface
Acknowledgments
Contents
Acronyms
Part I Background and Context
1 Introduction
1.1 Background and Motivation
1.2 Goal and Research Questions
1.3 Contextualization of This Research
1.4 Structure of the Book
References
2 Approaching the Concept of Competency
2.1 Competency Definition
2.1.1 Psychological Perspective on Competency
2.1.2 Historical Perspective on Competency
2.1.3 Recent Perspectives and Discussions
2.2 Taxonomies and Competency Models for Computing
2.2.1 Bloom's and Anderson-Krathwohl's Taxonomy
2.2.2 Competency Model of the German Informatics Society
2.3 Competency-Based Curricula Recommendations in Computing
2.3.1 Information Technology 2017
2.3.2 Computing Curricula 2020
2.3.3 National Curricula Recommendations
2.4 Related Research in Computing Education
References
3 Research Design
3.1 Summary of Research Desiderata
3.2 Research Goals
3.3 Research Questions
3.4 Study Design
References
Part II Data Gathering and Analysis of University Curricula
4 Data Gathering of University Curricula
4.1 Goals of Gathering and Analyzing University Curricula
4.2 Relevance of Gathering and Analyzing University Curricula
4.3 Expectations and Limitations
4.4 Sampling and Data Gathering
4.4.1 Selection of Bachelor Degree Programs
4.4.2 Selection of Content Area
4.4.3 Selection of Institutions and Study Programs
4.4.4 Selection of Modules
References
5 Data Analysis of University Curricula
5.1 Methodology of the Data Analysis
5.2 Pre-processing of Data
5.2.1 Linguistic Smoothing of Competency Goals
5.2.2 Basic Coding Guidelines
5.2.3 Computer-Assisted Analysis
5.3 Data Analysis
5.3.1 Deductive Category Development
5.3.2 Inductive Category Development
5.3.3 Deductive-Inductive Category Development
5.4 Application of Quality Criteria
References
Part III Data Gathering and Analysis of Expert Interviews
6 Data Gathering of Guided Expert Interviews
6.1 Goals of Conducting and Analyzing Guided Expert Interviews
6.2 Relevance of Conducting and Analyzing Guided Expert Interviews
6.3 Expectations and Limitations
6.4 Developing an Interview Guide and Questions
6.5 Data Gathering and Sampling
6.5.1 Selecting and Contacting Experts
6.5.2 Conducting the Interviews
6.5.3 Recording the Interviews
References
7 Data Analysis of Guided Expert Interviews
7.1 Pre-processing of Data
7.1.1 Transcription Guidelines
7.1.2 Transcription System
7.1.3 Transcription Process
7.2 Data Analysis
7.3 Application of Quality Criteria
References
Part IV Results
8 Results of University Curricula Analysis
8.1 Cognitive Competencies
8.1.1 Cognitive Process Dimension Remembering
8.1.2 Cognitive Process Dimension Understanding
8.1.3 Cognitive Process Dimension Applying
8.1.4 Cognitive Process Dimension Analyzing
8.1.5 Cognitive Process Dimension Evaluating
8.1.6 Cognitive Process Dimension Creating
8.1.7 Knowledge Dimensions
8.2 Other Competencies
8.3 Reliability
8.4 Discussion of Results
References
9 Results of Guided Expert Interviews
9.1 Cognitive Competencies
9.2 Other Competencies
9.3 Factors Preventing Programming Competency
9.4 Factors Contributing to Programming Competency
9.5 Reliability
9.6 Discussion of Results
References
10 Summarizing and Reviewing the Components of Programming Competency
10.1 Summary of Cognitive Programming Competencies
10.2 Summary of Other Programming Competency Components
10.3 Review of the Anderson Krathwohl Taxonomy
References
Part V Wrap Up
11 Conclusion
11.1 Brief Summary of Results
11.1.1 Competencies Expected from Novice Programmers
11.1.2 Adequacy of the Anderson Krathwohl Taxonomy for Programming Education
11.1.3 Factors Influencing Students' CompetencyDevelopment
11.2 Conclusions
11.3 Future Work
References
