Emerging from the Deep: Complexity, Emergent Pedagogy and Deep Learning

As indicated in the title – emerging from the deep – this paper proposes that an ability to face and deal with complexity can emerge from deep learning that is facilitated by pedagogies designed to ensure this outcome, especially an emergent pedagogy that instills deep education. Educators would vie...

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Main Author: Sue L. T. McGregor
Format: Article
Language:English
Published: Binghamton University Library 2020-12-01
Series:Northeast Journal of Complex Systems
Subjects:
Online Access:https://orb.binghamton.edu/nejcs/vol2/iss1/2
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author Sue L. T. McGregor
author_facet Sue L. T. McGregor
author_sort Sue L. T. McGregor
collection DOAJ
description As indicated in the title – emerging from the deep – this paper proposes that an ability to face and deal with complexity can emerge from deep learning that is facilitated by pedagogies designed to ensure this outcome, especially an emergent pedagogy that instills deep education. Educators would view the classroom as a complex adaptive system (CAS) capable of self-organizing and operating at the edge of chaos where order emerges, just not predictably. Self-directed students would experience a learning environment that is appreciative of nonequilibrium, unpredictability, shifting and emerging patterns and co-evolution. Teachers would be coaches, activators and facilitators. Students would take part in learning encounters that ensure intellectual networking and conceptual connections. The knowledge and insight that develop would be interwoven and interdependent (complex), which is appropriate because complexity is needed to address complex problems.
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spelling doaj.art-dffbbf1f4bc34f0dabb28891b73319a12023-11-13T20:11:35ZengBinghamton University LibraryNortheast Journal of Complex Systems2577-84392020-12-012110.22191/nejcs/vol2/iss1/2Emerging from the Deep: Complexity, Emergent Pedagogy and Deep LearningSue L. T. McGregor0https://orcid.org/0000-0002-4392-9608Mount Saint Vincent UniversityAs indicated in the title – emerging from the deep – this paper proposes that an ability to face and deal with complexity can emerge from deep learning that is facilitated by pedagogies designed to ensure this outcome, especially an emergent pedagogy that instills deep education. Educators would view the classroom as a complex adaptive system (CAS) capable of self-organizing and operating at the edge of chaos where order emerges, just not predictably. Self-directed students would experience a learning environment that is appreciative of nonequilibrium, unpredictability, shifting and emerging patterns and co-evolution. Teachers would be coaches, activators and facilitators. Students would take part in learning encounters that ensure intellectual networking and conceptual connections. The knowledge and insight that develop would be interwoven and interdependent (complex), which is appropriate because complexity is needed to address complex problems.https://orb.binghamton.edu/nejcs/vol2/iss1/2chaoscomplexitycomplex adaptative systemsdeep educationdeep learningemergent pedagogy
spellingShingle Sue L. T. McGregor
Emerging from the Deep: Complexity, Emergent Pedagogy and Deep Learning
Northeast Journal of Complex Systems
chaos
complexity
complex adaptative systems
deep education
deep learning
emergent pedagogy
title Emerging from the Deep: Complexity, Emergent Pedagogy and Deep Learning
title_full Emerging from the Deep: Complexity, Emergent Pedagogy and Deep Learning
title_fullStr Emerging from the Deep: Complexity, Emergent Pedagogy and Deep Learning
title_full_unstemmed Emerging from the Deep: Complexity, Emergent Pedagogy and Deep Learning
title_short Emerging from the Deep: Complexity, Emergent Pedagogy and Deep Learning
title_sort emerging from the deep complexity emergent pedagogy and deep learning
topic chaos
complexity
complex adaptative systems
deep education
deep learning
emergent pedagogy
url https://orb.binghamton.edu/nejcs/vol2/iss1/2
work_keys_str_mv AT sueltmcgregor emergingfromthedeepcomplexityemergentpedagogyanddeeplearning