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dc.contributor.authorAguayo, Cen_NZ
dc.date.accessioned2020-03-10T01:56:35Z
dc.date.available2020-03-10T01:56:35Z
dc.date.copyright2019en_NZ
dc.identifier.citationIn The 2018 Conference on Artificial Life: A Hybrid of the European Conference on Artificial Life (ECAL) and the International Conference on the Synthesis and Simulation of Living Systems (ALIFE) (pp. 495-496). One Rogers Street, Cambridge, MA 02142-1209 USA journals-info@ mit. edu: MIT Press.
dc.identifier.isbn9780262358446en_NZ
dc.identifier.urihttp://hdl.handle.net/10292/13197
dc.description.abstractToday’s mobile and smart technologies have a key role to play in the transformative potential of educational practice. However, technology-enhanced learning processes are embedded within an inherent and unpredictable complexity, not only in the design and development of educational experiences, but also within the socio-cultural and technological contexts where users and learners reside. This represents a limitation with current mainstream digital educational practice, as digital experiences tend to be designed and developed as ‘one solution fits all’ products, and/or as ‘one-off’ events, failing to address ongoing socio-technological complexity, therefore tending to decay in meaningfulness and effectiveness over time. One ambitious solution is to confer the processes associated with the design and development of digital learning experiences with similar autopoietic properties found within living systems, in particular adaptability and self-organisation. The underpinning rationale is that, by conferring such properties to digital learning experiences, intelligent digital interventions responding to unpredictable and ever-changing socio-cultural conditions can be created, promoting meaningful learning over-time. Such an epistemological view of digital learning aims to ultimately promote a more efficient type of design and development of digital learning experiences in education.
dc.publisherMIT Pressen_NZ
dc.relation.urihttps://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00210
dc.rights© 2019 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license
dc.titleAutopoiesis in Digital Learning Design: Theoretical Implications in Educationen_NZ
dc.typeConference Contribution
dc.rights.accessrightsOpenAccessen_NZ
dc.identifier.doi10.1162/isal_a_00210en_NZ
pubs.elements-id372106
aut.relation.conferenceThe 2019 Conference on Artificial Lifeen_NZ


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