Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Mining the Algorithmic Sublime: A Qualitative Analysis of Learning Analytics Discourse

Widdersheim, Michael M (2015) Mining the Algorithmic Sublime: A Qualitative Analysis of Learning Analytics Discourse. In: The 26th ICDE World Conference, 14 October 2015 - 16 October 2015, Sun City, South Africa.

Published Version
Available under License : See the attached license file.

Download (441kB)
[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


Learning analytics discourse occupies an increasingly prominent position within online distance learning literature. Learning analytics refers to the large-scale collection and analysis of student data for the purpose of providing feedback to students, instructors, and organizations. Digital, networked, and computational technologies facilitate these measurement and intervention processes. Learning analytics are highly touted by some in the education and data mining fields, and it is said that analytics will revolutionize online learning with their sophisticated predictions, modelling, and adaptive machine-learning techniques. Despite claims that learning analytics offer actionable intelligence to their users, learning analytics are not so intelligent that they can compute, predict, or recommend their own legitimacy. Instead, this paper argues that the promulgation of learning analytics depends on an ideology called the algorithmic sublime. To describe what this ideology is and how it works, this paper uses critical discourse analysis as a qualitative methodology to interrogate learning analytics discourse. This study presents four patterns of learning analytics ideology: Modal Bootstrapping, Ethicality, Epistemic Displacement, and Collect It All. These patterns are explained using examples from the literature. This study is significant because it encourages debate about an emerging issue and introduces a novel research methodology into the field.


Social Networking:
Share |


Item Type: Conference or Workshop Item (Paper)
Status: Published
CreatorsEmailPitt UsernameORCID
Widdersheim, Michael Mmmw84@pitt.eduMMW84
Date: 14 October 2015
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Event Title: The 26th ICDE World Conference
Event Dates: 14 October 2015 - 16 October 2015
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Library and Information Science
Refereed: Yes
Date Deposited: 03 Nov 2015 16:44
Last Modified: 31 Jul 2020 19:10


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item