DescriptionComplex societal issues usually ask for socio-technological solutions. Examples are e-health, surveillance, care robots, mobility, climate-problems, disaster management, and smart environments. The design and development of such socio-technological solutions involve inter-, multi- and/or transdisciplinary scientific research in both social and engineering sciences. This complexity puts forward particular challenges for the education of engineering students. How should they be prepared for these kinds of tasks? Based on an extensive review of literature on how interdisciplinary problem-solving is taught in engineering education we have concluded that clarity on crucial epistemological challenges of the uses of science in interdisciplinary problem-solving is lacking, let alone, on how to teach the necessary (meta-)cognitive and methodological skills needed for interdisciplinary research and design.
This paper aims to address these educational challenges for engineering programs by drawing on three different sources: literature on science and engineering education, studies in the philosophy of science, and our own course in model-based reasoning (MBR) that aims to mitigate intellectual and epistemological challenges of teaching interdisciplinary problem-solving.
Didactic models such as problem-based learning (PBL) have been widely adopted in engineering education programs to promote students’ ability to solve ‘real-world’ problems and to recognize societal issues, as well as to attain social and professional skills. However, education in methodologies and so-called metacognitive skills for dealing with the intellectual and epistemological challenges of effectively employing science in interdisciplinary problem-solving is virtually absent. Indeed, although the literature on interdisciplinarity is massive (e.g., on its characterization and on its institutional aspects), studies aiming at an epistemology of interdisciplinarity are scarce. The issue requires better (philosophical) understanding of (1) how scientific knowledge for specific applications is constructed, (2) why scientific disciplines take different approaches and have difficulties to understand each other, and (3) possibilities and constraints for effectively combining discipline-specific epistemic resources (knowledge, methods, technological and mathematical instruments, …). Philosophers of science have argued that in actual research practices model-based reasoning (MBR) plays an essential role in the coordination and integration of different scientific fields. Accordingly, we propose an epistemology that puts models and modeling (rather than theories and laws) at the center.
Based on these insights, we have developed a course in MBR, which aims at methodological and (meta-)cognitive skills needed for interdisciplinary research and problem-solving. MBR, in short, is the activity of reasoning by means of models and modelling. The locus of this course is a university college (ATLAS UC) that aims to education T-shaped engineers. Our general claim is that scientific education aiming at graduates capable of interdisciplinary research towards problem-solving should take MBR as one of the central skills to support in learning effective approaches in: problem-analysis, reading scientific articles, translating problems into possible solutions, crafting design-concepts for problem-solving, translating design-ideas into research-project, and ultimately, also understanding of so-called cognitive and heuristic strategies that scientists use in generating scientific knowledge.
|Period||15 Jun 2016|
|Event title||20th International Conference of the Society for Philosophy of Technology 2017: The Grammar of Things|
|Degree of Recognition||International|