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Record W1530185735 · doi:10.19173/irrodl.v15i5.1856

Making ‘MOOCs’: The construction of a new digital higher education within news media discourse

2014· article· en· W1530185735 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2014
Typearticle
Languageen
FieldComputer Science
TopicOnline Learning and Analytics
Canadian institutionsnot available
Fundersnot available
KeywordsMainstreamPublic relationsSociologySocial mediaUnderpinningDigital mediaPolitical scienceMedia studiesEngineering

Abstract

fetched live from OpenAlex

<p>One notable ‘disruptive’ impact of massive open online courses (MOOCs) has been an increased public discussion of online education. While much debate over the potential and challenges of MOOCs has taken place online confined largely to niche communities of practitioners and advocates, the rise of corporate ‘xMOOC’ ventures such as Coursera, edX and Udacity has prompted popular mass media interest at levels not seen with previous educational innovations. This article addresses this important societal outcome of the recent emergence of MOOCs as an educational form by examining the popular discursive construction of MOOCs over the past 24 months within mainstream news media sources in United States, Australia and the UK. In particular, we provide a critical account of what has been an important phase in the history of educational technology—detailing a period when popular discussion of MOOCs has far outweighed actual use/participation. We argue that a critical analysis of MOOC discourse throughout the past two years highlights broader societal struggles over education and digital technology—capturing a significant moment before these debates subside with the anticipated normalization and assimilation of MOOCs into educational practice. This analysis also sheds light on the influences underpinning how many people perceive MOOCs thereby leading to a better understanding of acceptance/adoption and rejection/resistance amongst various professional and popular publics.</p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.844
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.098
GPT teacher head0.459
Teacher spread0.361 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it