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Education for Problems of Sustainable Development
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ABSTRACT
The Cynefin framework for decision‐making categorizes problem environments into simple (known knowns), complicated (known unknowns), complex (unknown unknowns), and chaotic (unknowables). Simple and complicated problem environments enable best and good solutions, but complex and chaotic problem environments require emergent and novel solutions. Arguing that sustainability problems are complex and chaotic, this study applies the Cynefin framework of decision‐making in complex and chaotic problem environments as a lens for sensemaking and reframing of sustainability competencies, resulting in proposing a suite of sustainability competencies to address complex and chaotic problems. Five competencies are proposed and defined, including: reflective action, critical systems thinking, boundary spanning, active empathy, and pathfinding. These are the first suite of sustainability competencies that are problem‐based, processual, and integrated in nature, involving a sequential relationship between the competencies grounded on the Cynefin problem‐solving steps. This enables systematic learning of these competencies in a single instructional project, hence facilitating deep relational learning. Furthermore, the study proposes an instructional design that situates learning of these competencies in human cognitive architecture to reduce extraneous cognitive load on the limited working memory and encourage long‐term memory construction. The study hypothesizes that each competence is best learned through a tailored set of the nine human intelligences identified by the theory of multiple intelligences. For example, the competence of critical systems thinking, defined as the ability to account for known, unknown, and unknowable relationships in a problem context, is best learned through logical‐mathematical intelligence and spatial intelligence—which help analyze known problem relationships, naturalistic intelligence—which helps reflect on unknown problem relationships, and existential intelligence which helps consider unknowable problem relationships.
Title: Education for Problems of Sustainable Development
Description:
ABSTRACT
The Cynefin framework for decision‐making categorizes problem environments into simple (known knowns), complicated (known unknowns), complex (unknown unknowns), and chaotic (unknowables).
Simple and complicated problem environments enable best and good solutions, but complex and chaotic problem environments require emergent and novel solutions.
Arguing that sustainability problems are complex and chaotic, this study applies the Cynefin framework of decision‐making in complex and chaotic problem environments as a lens for sensemaking and reframing of sustainability competencies, resulting in proposing a suite of sustainability competencies to address complex and chaotic problems.
Five competencies are proposed and defined, including: reflective action, critical systems thinking, boundary spanning, active empathy, and pathfinding.
These are the first suite of sustainability competencies that are problem‐based, processual, and integrated in nature, involving a sequential relationship between the competencies grounded on the Cynefin problem‐solving steps.
This enables systematic learning of these competencies in a single instructional project, hence facilitating deep relational learning.
Furthermore, the study proposes an instructional design that situates learning of these competencies in human cognitive architecture to reduce extraneous cognitive load on the limited working memory and encourage long‐term memory construction.
The study hypothesizes that each competence is best learned through a tailored set of the nine human intelligences identified by the theory of multiple intelligences.
For example, the competence of critical systems thinking, defined as the ability to account for known, unknown, and unknowable relationships in a problem context, is best learned through logical‐mathematical intelligence and spatial intelligence—which help analyze known problem relationships, naturalistic intelligence—which helps reflect on unknown problem relationships, and existential intelligence which helps consider unknowable problem relationships.
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