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Smart STEM-Driven Computer Science Education - Theory, Methodology and Robot-based Practices (Hardcover, 1st ed. 2018)
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Smart STEM-Driven Computer Science Education - Theory, Methodology and Robot-based Practices (Hardcover, 1st ed. 2018)
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At the centre of the methodology used in this book is STEM learning
variability space that includes STEM pedagogical variability,
learners' social variability, technological variability, CS content
variability and interaction variability. To design smart
components, firstly, the STEM learning variability space is defined
for each component separately, and then model-driven approaches are
applied. The theoretical basis includes feature-based modelling and
model transformations at the top specification level and
heterogeneous meta-programming techniques at the implementation
level. Practice includes multiple case studies oriented for solving
the task prototypes, taken from the real world, by educational
robots. These case studies illustrate the process of gaining
interdisciplinary knowledge pieces identified as S-knowledge,
T-knowledge, E-knowledge, M-knowledge or integrated STEM knowledge
and evaluate smart components from the pedagogical and
technological perspectives based on data gathered from one real
teaching setting. Smart STEM-Driven Computer Science Education:
Theory, Methodology and Robot-based Practices outlines the overall
capabilities of the proposed approach and also points out the
drawbacks from the viewpoint of different actors, i.e. researchers,
designers, teachers and learners.
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