Using open-source software and interdisciplinary teaching to increase digital forensics accessibility, and inclusivity, with sustainable development and learning in higher education

• Six years of student attainment data of the UG “Forensic Image Processing” module. • Accessibility benefits using open-source software focusing on processing principles. • Interdisciplinary team delivers material to provide an equal footing for students. • No ethnic minority attainment gap is present. • Benefit industry by training when automated software wrongly processes an image. Ensuring rigorous forensic image processing means not only adhering to the relevant industry standards but also a solid foundation of teaching the principles behind the skills. This study examines six years of a level 5 undergraduate “Forensic Image Processing” module and focuses on using open-source software and interdisciplinary teaching to provide a competence based active learning environment, to improve professional development. A discussion of the importance of understanding how an image is processed is included, especially when applying automated processes. The results of this approach show a benefit of education for cultural diversity. Within the module the computing workshops have a negligible award gap, while the exam shows a 6% gap in favour of ethnic minority students. The major factor affecting student outcomes in the module is the year it was delivered partly with online learning via remote workshops with a drop of average attainment for all students.