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A fundamental problem in deciding between mutually exclusive options is that the decision needs to be categorical although the properties of the options often differ but in grade. We developed an experimental handle to study this aspect of behavior organization. Larval Drosophila were trained such that in one set of animals odor A was rewarded, but odor B was not (A+/B), whereas a second set of animals was trained reciprocally (A/B+). We then measured the preference of the larvae either for A, or for B, or for “morphed” mixtures of A and B, that is for mixtures differing in the ratio of the two components. As expected, the larvae showed higher preference when only the previously rewarded odor was presented than when only the previously unrewarded odor was presented. For mixtures of A and B that differed in the ratio of the two components, the major component dominated preference behavior—but it dominated less than expected from a linear relationship between mixture ratio and preference behavior. This suggests that a minor component can have an enhanced impact in a mixture, relative to such a linear expectation. The current paradigm may prove useful in understanding how nervous systems generate discrete outputs in the face of inputs that differ only gradually.
Providing adaptive, independence-preserving and theory-guided support to students in dealing with real-world problems in mathematics lessons is a major challenge for teachers in their professional practice. This paper examines this challenge in the context of simulations and mathematical modelling with digital tools: in addition to mathematical difficulties when autonomously working out individual solutions, students may also experience challenges when using digital tools. These challenges need to be closely examined and diagnosed, and might – if necessary – have to be overcome by intervention in such a way that the students can subsequently continue working independently. Thus, if a difficulty arises in the working process, two knowledge dimensions are necessary in order to provide adapted support to students. For teaching simulations and mathematical modelling with digital tools, more specifically, these knowledge dimensions are: pedagogical content knowledge about simulation and modelling processes supported by digital tools (this includes knowledge about phases and difficulties in the working process) and pedagogical content knowledge about interventions during the mentioned processes (focussing on characteristics of suitable interventions as well as their implementation and effects on the students’ working process). The two knowledge dimensions represent cognitive dispositions as the basis for the conceptualisation and operationalisation of a so-called adaptive intervention competence for teaching simulations and mathematical modelling with digital tools. In our article, we present a domain-specific process model and distinguish different types of teacher interventions. Then we describe the design and content of a university course at two German universities aiming to promote this domain-specific professional adaptive intervention competence, among others. In a study using a quasi-experimental pre-post design (N = 146), we confirm that the structure of cognitive dispositions of adaptive intervention competence for teaching simulations and mathematical modelling with digital tools can be described empirically by a two-dimensional model. In addition, the effectiveness of the course is examined and confirmed quantitatively. Finally, the results are discussed, especially against the background of the sample and the research design, and conclusions are derived for possibilities of promoting professional adaptive intervention competence in university courses.