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Learning and expertise with scientific external representations: an embodied and extended cognition model

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Abstract

This paper takes an embodied and extended cognition perspective to ER integration – a cognitive process through which a learner integrates external representations (ERs) in a domain, with her internal (mental) model, as she interacts with, uses, understands and transforms between those ERs. In the paper, I argue for a theoretical as well as empirical shift in future investigations of ER integration, by proposing a model of cognitive mechanisms underlying the process, based on recent advances in extended and embodied cognition. I present this new model in contrast to the still dominant classical cognitivist (information processing) approaches to ER integration, and the educational technology intervention designs such approaches inspire. I then exemplify this distinction between the information processing model and the new model through a case of arithmetic problem solving. Corroborative neuroscience evidence presented in relation to this case provides empirical support for the new model by showing how bodily actions (sensorimotor mechanisms) are critical to ER integration and learning. Finally, as educational implications of the new model, I demonstrate the need for: (i) re-viewing the development of ER integration and expertise as fine-tuning of the learner's action or sensorimotor system, and (ii) a shift of focus in new-media intervention design principles based on this newer understanding of ER integration in science, technology, engineering and mathematics.

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Notes

  1. The action-perception-expertise loop is not new in cognitive science (e.g. see Glenberg et al. 2013 for a detailed review largely in the context of language reading and comprehension). However, reviews reveal that it is yet to percolate in STEM education, specifically in the context of ER integration and conceptual learning. This paper is an attempt to adoptively revise the models of ER integration in STEM.

  2. Extended cognition is different in focus from distributed cognition, which is more of a systemic perspective examining cognition as emerging out of complex interactions between various components of a distributed system such as socio-material-technical ecologies (e.g. airplanes, ships; Hutchins 1995).

  3. Common coding is different from the more radical anti-representationalist embodied cognition perspectives such as enactivism and dynamical systems theories (see Noë 2004; Riva 2006; Thelen and Smith 1994; Van Gelder and Port 1995).

  4. For instance, to perform an action as simple as picking up an object, the sensorimotor system integrates: the current state or posture of the body, spatial relations between the body and the object, previous experiences of the object, expected feedback or ‘consequences’ of touching the object or the action of picking it up, control and regulation of the body movement, through the information coming from the skin, muscles and joints, vestibular system, the motor plan of the action, anticipatory adjustments of the posture and body parts and movements in relation to the motor plan and the position of the object (see Machado et al. 2010).

  5. That said, it is still not clear, from a phenomenological stance, as to how the sensorimotor neural basis of ER-related expertise is linked to experiencing instances of that expertise in tasks (Noë 2004). Also uncertain are if and how the phenomenological and neural processes are looped together. It would also perhaps be interesting for future interdisciplinary and multi-faceted domain-expertise research to investigate how language in a domain (e.g. ‘scientific’ language, ‘language of mathematics’; Tall 2013), social and peer interaction dynamics in STEM domains, among other coexisting and interacting dimensions in the STEM learning and practice world affect ER integration and expertise.

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Acknowledgements

I am grateful to Dr. Sanjay Chandrasekharan for his guidance in developing this theoretical work and Dr. Renae Acton for her valuable feedback on the manuscript.

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  1. Department of People and Technology, Roskilde University, Universitetsvej 1, 4000, Roskilde, Denmark

    Prajakt Pande

  2. Centre for Virtual Learning Technologies , Roskilde University , Universitetsvej 1, 4000, Roskilde, Denmark

    Prajakt Pande

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Pande, P. Learning and expertise with scientific external representations: an embodied and extended cognition model. Phenom Cogn Sci 20, 463–482 (2021). https://doi.org/10.1007/s11097-020-09686-y

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