Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/21941
Appears in Collections:Faculty of Social Sciences Journal Articles
Peer Review Status: Refereed
Title: Political computational thinking: policy networks, digital governance and ‘learning to code’
Author(s): Williamson, Ben
Contact Email: ben.williamson@stir.ac.uk
Keywords: computing curriculum
computational thinking
learning to code
governance
policy networks
policy labs
Issue Date: 2016
Date Deposited: 3-Jul-2015
Citation: Williamson B (2016) Political computational thinking: policy networks, digital governance and ‘learning to code’. Critical Policy Studies, 10 (1), pp. 39-58. https://doi.org/10.1080/19460171.2015.1052003
Abstract: Reflecting political shifts toward both ‘network governance' and ‘digital governance', the idea of ‘learning to code' has become part of a major reform agenda in education policy in England. This article provides a ‘policy network analysis' tracing the governmental, business and civil society actors now operating in policy networks to project learning to code into the reformed programs of study for computing in the National Curriculum in England. The insertion of learning to code into the curriculum provides evidence of how the education policy process is being displaced to cross-sector ‘boundary organizations' such as ‘policy labs' that act as connecting nodes to broker networks across public and private sector borderlines. It also examines how the pedagogies of learning to code are intended to inculcate young people into the material practices and systems of thought associated with computer coding, and to contribute to new forms of ‘digital governance'. These developments are evidence of a ‘reluctant state' deconcentrating its responsibilities, and also of a computational style of political thinking that assumes policy problems can be addressed using the right code. Learning to code is seen as a way of shaping governable citizens that can participate in the dynamics of digital governance.
DOI Link: 10.1080/19460171.2015.1052003
Rights: © 2015 The Author(s). Published by Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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