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Disrupting the Dissertation: Linked-Data, Crowd-sourcing and Algorithmic Culture

Tracy, FE and Carmichael, P (2017) Disrupting the Dissertation: Linked-Data, Crowd-sourcing and Algorithmic Culture. E-Learning and Digital Media, 14 (3). pp. 164-182. ISSN 2042-7530

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This article explores how the three aspects of Striphas’ notion of algorithmic culture (information, crowds and algorithms) might influence and potentially disrupt established educational practices. We draw on our experience of introducing semantic web and linked data technologies into higher education settings, focussing on extended student writing activities such as dissertations and projects, and drawing in particular on our experiences related to undergraduate archaeology dissertations. The potential for linked data to be incorporated into electronic texts, including academic publications, has already been described, but these accounts have highlighted opportunities to enhance research integrity and interactivity, rather than considering their potential creatively to disrupt existing academic practices. We discuss how the changing relationships between subject content and practices, teachers, learners and wider publics both in this particular algorithmic culture, and more generally, offer new opportunities; but also how the unpredictability of crowds, the variable nature and quality of data, and the often hidden power of algorithms, introduce new pedagogical challenges and opportunities.

Item Type: Article
Uncontrolled Keywords: 1302 Curriculum And Pedagogy, 1303 Specialist Studies In Education
Subjects: L Education > LB Theory and practice of education > LB2300 Higher Education
Divisions: Education
Publisher: SAGE Publications
Date Deposited: 25 Jul 2017 15:00
Last Modified: 04 Sep 2021 11:20
DOI or ID number: 10.1177/2042753017731356
URI: https://researchonline.ljmu.ac.uk/id/eprint/6852
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