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Towards Empirical Modelling of Knowledge Transfer in Teaching/Learning Process

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Book cover Information and Software Technologies (ICIST 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 465))

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Abstract

Educational systems are complex adaptive systems with basic properties of openness, nonlinearity, feedback and adaptivity.Modelling and assessment of a teaching/learning process is a difficult task that involves many factors at multiple dimensions (pedagogical, technological, organizational, social, etc.). Common methods used for evaluation of teaching/learning effectiveness such as surveys, questionnaires and tests are subjective and lack of statistical control and standards for comparison. In this paper, we propose an empirical knowledge transfer model for closed teacher-learner systems and its extension for open teacher-learner systems. The model is based on the theory of communication in noisy channels with additive white Gaussian noise. We describe the pedagogical interpretation of the model’s parameters and describe its application in modelling the transfer of knowledge in the teaching/learning process.

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Author information

Authors and Affiliations

  1. Software Engineering Department, Kaunas University of Technology, Studentų 50, Kaunas, Lithuania

    Robertas Damaševičius

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  1. Robertas Damaševičius
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Editor information

Editors and Affiliations

  1. Kaunas University of Technology, Studentu g. 50-409a,, LT-51368, Kaunas, Lithuania

    Giedre Dregvaite

  2. Kaunas University of Technology, Studentu g. 50-409a, LT-51368, Kaunas, Lithuania

    Robertas Damasevicius

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Damaševičius, R. (2014). Towards Empirical Modelling of Knowledge Transfer in Teaching/Learning Process. In: Dregvaite, G., Damasevicius, R. (eds) Information and Software Technologies. ICIST 2014. Communications in Computer and Information Science, vol 465. Springer, Cham. https://doi.org/10.1007/978-3-319-11958-8_29

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  • DOI: https://doi.org/10.1007/978-3-319-11958-8_29

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11957-1

  • Online ISBN: 978-3-319-11958-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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