Object-oriented programming (OOP) is widely used in the software industry and university introductory courses today. Following the structure of most textbooks, such courses frequently are organised starting with the concepts of imperative and structured programming and only later introducing OOP. An alternative approach is to begin directly with OOP following the Outside-In teaching method as proposed by Meyer. Empirical results for the effects of Outside-In teaching on students and lecturers are sparse, however. We describe the conceptual design and empirical evaluation of two OOP introductory courses from different universities based on Outside-In teaching. The evaluation results are compared to those from a third course serving as the control group, which was taught OOP the "traditional" way. We evaluate the initial motivation and knowledge of the participants and the learning outcomes. In addition, we analyse results of the end term exams and qualitatively analyse the results of interviews with the lecturers and tutors. Regarding the learning outcomes, the results show no significant differences between the Outside-In and the "traditional" teaching method. In general, students found it harder to solve and implement algorithmic problems than to understand object oriented (OO) concepts. Students taught OOP by the Outside-In method, however, were less afraid that they would not pass the exam at the end of term and understood the OO paradigm more quickly. Therefore, the Outside-In method is no silver bullet for teaching OOP regarding the learning outcomes but has positive effects on motivation and interest.

The high relevance of IT skills for most job profiles today requires to teach computer science and software engineering topics to an increasing number of students from non-major computer science programs (i.e. business administration). Due to their different knowledge and motivation this is a special challenge and requires suitable didactical methods and concepts. Since the research literature on this issue is sparse, the present paper provides a first overview about these challenges and methods and presents results of a first analysis of selected methods in practice.