5. Cybersocial learning occurs in the play of the material (artifacts, machines, texts) and the ideal (the figuring they require). With ubiquitous computing devices, both formal and informal learning are increasingly mediated by these devices and their peculiar affordances (Cope & Kalantzis, 2015, 2017, 2022a).
5.1. In the era of networked computers, previously impracticable sociabilities are created. These span time and space in unprecedented ways, so also offering unparalleled opportunities to learn for persons, social groups and organizations. However, these openings are also frequently accompanied by new vectors for anti-social control – the algorithmic manipulations of social media platforms, for instance, or the knowledge transmission and control mechanisms of learning management systems.
5.2. Now that we have binary computing devices ubiquitously at hand, serving as extensions of our sensorimotor systems and minds, we no longer need to focus formal education on a separated domain of cognition and the memorization of facts and procedures. We need to learn ‘how’ more than ‘what’ because we can rely on the machines can do the ‘what’ for us.
5.3. Computer-mediated, cybersocial learning connects people (who give meaning to things) with computers (which represent these things via transpositions of calculation). Such learning strives to be:
5.3.1. Agentive: placing a premium on awareness of self-states, self-regulation, and self-efficacy within the parameters of social or knowledge systems that are themselves self-organizing (contrasted with transmission pedagogies of received knowledge).
5.3.2. Transpositional: creating a lively traffic between the sensorimotor and the cognitive, the world and its conceptual representation, human intelligence and computer intelligence, the ideal and the material (contrasted with the cognitivist biases of education, assessment, and some strands of artificial intelligence).
5.3.3. Multilinear: traversing social networks and knowledge graphs (contrasted with linear, transmission models of standardized knowledge: teacher/text > student > one-shot test; and lock-step models knowledge progression).
5.3.4. Reflexive: offering small, rapid cycles of actionable human-human and human machine feedback (contrasted with the long, practically non-actionable cycles of traditional assessment) (Cope & Kalantzis, 2019).
5.3.5. Modulated: between periods of homeostasis, practicing at one level of learning, and self-transformation, moving towards a new level (contrasted with continuous delivery models).
5.3.6. Collaborative: leveraging the social distribution of meanings, in knowledge architectures and ontologies or group knowledge work (contrasted with individualized, ‘mentalist’ pedagogies).
5.3.7. Heterarchical: making virtue of the diversity of learners, applying this to dialogue, interpretation, and problematizing knowledge (contrasted with hierarchical, one-size-fits-all transmission of received knowledge).
5.3.8. Non-scalar: nesting small scale for example peer-peer, one-to-one instruction, within an indefinitely scalable learning ecology (contrasted with the fixed scale of physical learning architectures and educational labor processes).
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COPE, Bill and KALANTZIS, Mary, 2022. The cybernetics of learning. Educational Philosophy and Theory. 6 December 2022. Vol. 54, no. 14, p. 2352–2388. DOI 10.1080/00131857.2022.2033213, p. 2384–2385. pdf 