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Neurocomputational Methods: From Models of Brain and Cognition to Artificial Intelligence in Education

Thomas, M; Porayska-Pomsta, K; (2022) Neurocomputational Methods: From Models of Brain and Cognition to Artificial Intelligence in Education. In: Houdé, O and Bosrt, G, (eds.) The Cambridge Handbook of Cognitive Development. (pp. 662-687). Cambridge University Press: Cambridge, UK.

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Abstract

In this chapter, we consider computational approaches to understanding learning and teaching. We consider the utility of computational methods in two senses, which we address in separate sections. In Section 32.1, we consider the use of computers to build models of cognition, focusing on the one hand on how they allow us to understand the developmental origins of behaviour and the role of experience in shaping behaviour, and on the other hand on how a particular type of model – artificial neural networks – can uncover the way in which the constraints of brain function likely shape the properties of our cognitive systems. In Section 32.2, we consider the use of computers as tools to aid teaching, in particular in the use of artificial intelligence in education.

Type: Book chapter
Title: Neurocomputational Methods: From Models of Brain and Cognition to Artificial Intelligence in Education
DOI: 10.1017/9781108399838.037
Publisher version: https://doi.org/10.1017/9781108399838.037
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media
URI: https://discovery.ucl.ac.uk/id/eprint/10088032
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