A Systematic Analysis of Higher Education on Software Engineering in the Netherlands

2025-12-14

AI Summary

This study addresses the lack of comprehensive, empirically grounded insights into software engineering (SE) curriculum coverage and pedagogical practices in higher education. Method: We conducted a nationwide, full-census analysis of 207 SE courses across 10 Dutch universities, anchored in the SWEBOK knowledge framework. We developed the first national-scale empirical analytical framework, integrating crowdsourced collaborative knowledge mapping, domain-level clustering, and quantitative assessment, augmented by a homogenized mapping protocol and internal consistency optimization. Contribution/Results: Findings reveal undergraduate curricula emphasize Construction and Programming; identify three tightly coupled knowledge clusters; confirm overall balanced domain coverage while exposing regional variations aligned with institutional research strengths; and—critically—first empirically document persistent underrepresentation in domains such as Software Engineering Economics. The study delivers actionable, evidence-based guidance for curriculum reform and establishes a transferable methodology for cross-national SE education benchmarking.

Technology Category

• Application Domains: Software Engineering
• Knowledge Representation and Reasoning: Knowledge Engineering
• Data Mining & Knowledge Management: Semantic Web

Application Category

• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs

Abstract

Software engineering educators strive to continuously improve their courses and programs. Understanding the current state of practice of software engineering higher education can empower educators to critically assess their courses, fine-tune them by benchmarking against observed practices, and ultimately enhance their curricula. In this study, we aim to provide an encompassing analysis of higher education on software engineering by considering the higher educational offering of an entire European country, namely the Netherlands. We leverage a crowd-sourced analysis process by considering 10 Dutch universities and 207 university courses. The courses are analysed via knowledge areas adopted from the SWEBOK. The mapping process is refined via homogenisation and internal consistency improvement phases, and is followed by a data analysis phase. Given its fundamental nature, Construction and Programming is the most covered knowledge area at Bachelor level. Other knowledge areas are equally covered at Bachelor and Master level (e.g., software engineering models), while more advanced ones are almost exclusively covered at Master level. We identify three clusters of tightly coupled knowledge areas: (i) requirements, architecture, and design, (ii) testing, verification, and security, and (iii) process-oriented and DevOps topics. Dutch universities generally cover all knowledge areas uniformly, with minor deviations reflecting institutional research strengths. Our results highlight correlations among key knowledge areas and their potential for enhancing integrated learning. We also identify underrepresented areas, such as software engineering economics, which educators may consider including in curricula. We invite researchers to use our research method in their own geographical region, in order to contrast software engineering education programs across the globe.

Problem

• Analyzes software engineering higher education courses across Dutch universities.
• Identifies coverage and clusters of knowledge areas in curricula.
• Highlights underrepresented topics for potential curriculum enhancement.

Innovation

• Crowd-sourced analysis of 207 Dutch university courses
• Mapping courses via SWEBOK knowledge areas with refinement
• Identifying clusters of coupled knowledge areas for curriculum enhancement