Smart STEM-Driven Computer Science Education - Theory, Methodology and Robot-based Practices (Paperback, Softcover reprint of the original 1st ed. 2018)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	February 2019
First published:	2018
Authors:	Vytautas Stuikys • Renata Burbaite
Dimensions:	235 x 155 x 20mm (L x W x T)
Format:	Paperback
Pages:	368
Edition:	Softcover reprint of the original 1st ed. 2018
ISBN-13:	978-3-03-008710-4
Categories:	Books > Social sciences > Education > Educational resources & technology > General Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems Promotions
LSN:	3-03-008710-7
Barcode:	9783030087104

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