In this paper we review some problems with traditional approaches for acquiring and representing knowledge in the context of developing user interfaces. Methodological implications for knowledge engineering and for human-computer interaction are studied. It turns out that in order to achieve the goal of developing human-oriented (in contrast to technology-oriented) human-computer interfaces developers have to develop sound knowledge of the structure and the representational dynamics of the cognitive system which is interacting with the computer. //We show that in a first step it is necessary to study and investigate the different levels and forms of representation that are involved in the interaction processes between computers and human cognitive systems. Only if designers have achieved some understanding about these representational mechanisms, user interfaces enabling individual experiences and skill development can be designed. In this paper we review mechanisms and processes for knowledge representation on a conceptual, epistemological, and methodological level, and sketch some ways out of the identified dilemmas for cognitive modeling in the domain of human-computer interaction.

Key words: cognitive modeling, cognitive systems, human-computer interaction knowledge engineering, knowledge representation, knowledge-based user interfaces.

Context: Cognitive science, as an interdisciplinary research endeavour, poses challenges for teaching and learning insofar as the integration of various participating disciplines requires a reflective approach, considering and making explicit different epistemological attitudes and hidden assumptions and premises. Only few curricula in cognitive science face this integrative challenge. Problem: The lack of integrative activities might result from different challenges for people involved in truly interdisciplinary efforts, such as discussing issues on a conceptual level, negotiating colliding frameworks or sets of premises, asking profound questions challenging one’s own paradigm, and differences in terminologies, as well as from the “personal” challenge of realising one’s own limits of knowledge and, hence, the need to trust in another person’s expertise. This implies that the proposed curriculum structure provides an “epistemic laboratory”: a space for experiencing and negotiating, as well as constructing different viewpoints in a trustful setting. Approach: A newly-designed interdisciplinary cognitive science curriculum is presented that is based on a constructivist epistemology. We suggest that a careful construction of the learning space is a necessary requirement. The MEi:CogSci curriculum is designed and structured in such a way that enables didactical measures that allow for collaborative construction of meaning by discussing concepts, methods and terminologies and also hidden assumptions. Findings: The experience with four cohorts of students has shown that a truly interdisciplinary approach to cognitive science demands a different attitude towards knowledge as well as towards teaching and learning on both sides: the teacher and the student. The research orientation promotes an understanding of knowledge as something that is actively constructed, rendering the role of the teacher that of a co-learner rather than a transmitter of knowledge, thereby also changing the responsibility of students.

Key words: learning space, interdisciplinarity, cognitive science, curriculum design, epistemological reflection, teacher, constructivist pedagogy