Embedded Responsible Computing: Mainstreaming Ethics into Computer Science Curriculum: A Case Study of Dedan Kimathi University of Technology (DeKUT)
The rapid advancement of software solutions in the industry has brought significant ethical concerns, ranging from data privacy issues to algorithmic bias and cybersecurity threats. Addressing these concerns requires software developers who are technically proficient and ethically aware. To foster such ethical awareness, embedding ethical training within the computer science (CS) curriculum has emerged as a preferred approach. This study presents a methodology for integrating ethics topics into various CS units, informed by the IMPACTCS project’s guidelines and implemented through a structured algorithm. After an initial formative assessment to gauge students’ perceptions of responsible computing, the curriculum was adapted to include relevant ethical concepts. Following the instructional period, a summative assessment was conducted to evaluate changes in students’ understanding and attitudes towards ethical issues in computing. The results indicated a significant improvement in students’ ethical awareness and their ability to apply ethical principles to real-world scenarios. These findings underscore the effectiveness of incorporating ethics education into the CS curriculum and highlight the importance of preparing future software developers to navigate the ethical challenges in the tech industry. This study contributes to the ongoing efforts to enhance responsible computing education and promote ethical practices in software development.
Authors
- George Musumba (ORCID: https://orcid.org/0000-0002-7599-1158)
- David Wachepele
- Michael Kagiri (ORCID: https://orcid.org/0000-0001-8179-839X)
- Dennis Miano (ORCID: https://orcid.org/0000-0002-0634-2293)
- Hellen Mwangi
Institutions
- Dedan Kimathi University of Technology (KE)
Publication Details
- Published
- 2024-11-18
- DOI
- https://doi.org/10.1109/ict4da62874.2024.10777260
- Citations
- 1
- Primary Topic
- Teaching and Learning Programming
- Type
- article
- Field-Weighted Citation Impact
- 0.41