| Summary: | The development of knowledge following contemporary activities in science, technology, engineering and mathematics (STEM) involves epistemologies and cognition frames associated with modelling processes that balance different elements from theory, experimentation and scientific computation. In addition, many such processes increasingly require advanced mathematical physics models and methods of scientific computation. It then follows that STEM educational curricula, methodologies and teaching-learning environments should envision the development of meaningful learning paths going through balanced interactive explorations of all the different phases of the modelling cycle, namely, qualitative contextual description, definition, exploration, interpretation and validation of mathematical models, communication of results and generalizations. Furthermore, and always taking into account specific area dependent contexts, it is fundamental to achieve an early balanced integration of computational modelling, and to bring up a strong integrated background in physics, mathematics and scientific computation. However, in spite of the increasing amount of scientific evidence accumulated over the years, the majority of current practices in STEM education courses are still not able to reflect such balanced STEM epistemological and cognitive characteristics. Moreover, these are courses that often have many students with fragmented knowledge states, deteriorating expectations and low exam success rates
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