In programming education for non-computer science students, high diversity exists among our students, including gender, culture, age, educational background, and work experience. Introductory programming courses traditionally face high drop-out rates and poor performance, and students often perceive learning to program as difficult. Current research on diversity in programming education has primarily focused on gender differences, thus neglecting the influence of other diversity dimensions on students' performance. The project Diversity in Programming Education (DIPE) aims to fill this gap by identifying how heterogeneous groups of students can be best supported. Based on our findings, we develop a didactic concept with accompanying teaching and learning material to support different diversity dimensions actively in programming education. The concept includes competence models for measuring competences and individual learning paths. To support a flat learning curve further in university programming courses in the future, we closely work with schools and educational centres for teachers to integrate algorithmic thinking into school curricula. We empirically evaluate our concept using a mixed methods approach. In particular, we will explore the effects of our concept in our programming course and will investigate the value of these effects as perceived by lecturers and students.

Despite great effort in research and teaching as well as in raising women's quotas in the public sector and in enterprises, a gender gap in computer science can still be observed. The reasons are manifold, including the lack of interest of girls because of existing stereotypes of male nerds, misconceptions in the field of computer science, and concrete differences in students' self-concept and performance. Girls do not choose schools or studies in the field of computer science because working on computers or coding is unattractive to them. Research shows poorer performance, missing interest, and lower self-concept for girls in secondary computing education as well as a high dropout rate of female students in computer science courses at the bachelor's level. Software development exams contribute to those high dropout rates, and women often choose a different subject or even stop their university education altogether. This leads to fewer female employees in the field of computer science, and this situation calls for special measures at several levels. The current paper provides an overview of the initiatives of our university that aim to address several aspects of the gender gap. The programs offered aim to (1) increase interest in computer science and recruit (highly) gifted girls for our talent programs, (2) recruit and support female bachelor's and master's students in computer science, and (3) redesign programming courses and teaching materials to reduce the gender gap in performance and support, especially for female students. This study also describes a "cyber tutoring" program in which highly gifted girls between 13 and 16 years collaborate with and are supervised by female role models in higher positions in STEM. The evaluation results gained in the first year of this case study are promising and suggest that the extension and further development of the program would be advantageous.