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Record W2181769305 · doi:10.19173/irrodl.v16i6.2154

Comparing MOOC Adoption Strategies in Europe: Results from the HOME Project Survey

2015· article· en· W2181769305 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 · 2015
Typearticle
Languageen
FieldComputer Science
TopicOnline Learning and Analytics
Canadian institutionsnot available
FundersEuropean Commission
KeywordsStyle (visual arts)Context (archaeology)FontSpan (engineering)Political sciencePsychologySociologyGeographyArtEngineeringLiterature

Abstract

fetched live from OpenAlex

<p style="margin: 0cm 0cm 12pt 36pt; text-align: justify; line-height: 15pt;"><span style="font-family: 'Georgia','serif'; mso-bidi-font-size: 10.0pt; mso-bidi-font-family: Georgia;" lang="EN-US"><span style="font-size: small;">Much of the literature and the academic discussion about the impact of Massive Open Online Courses (MOOC) in institutional strategic planning has been centred on the US context. However, data shows that although the US are responsible for the largest MOOC platforms and the most successful course provision, it is the European region which accounts for the highest percentage of global MOOC participation. Differently from the US Higher Education system framework, however, in Europe public policy and in particular the European Commission is now driving MOOC institutional uptake.</span></span></p><p style="margin: 0cm 0cm 12pt 36pt; text-align: justify; line-height: 15pt;"><span style="font-family: 'Georgia','serif'; mso-bidi-font-size: 10.0pt; mso-bidi-font-family: Georgia;" lang="EN-US"><span style="font-size: small;">Given the very different institutional, political and cultural contexts, it is interesting to analyse how in these two different regions Higher Education institutions are responding to the challenges of the MOOC phenomena and are integrating it in their own strategic planning.</span></span></p><p style="margin: 0cm 0cm 12pt 36pt; text-align: justify; line-height: 15pt;"><span style="font-family: 'Georgia','serif'; mso-bidi-font-size: 10.0pt; mso-bidi-font-family: Georgia;" lang="EN-US"><span style="font-size: small;">The current research presents the first attempt to conduct a benchmarking study of institutional MOOC strategies in Europe and the US. It's based on a survey launched by the EU-funded project HOME and compares results with a similar survey launched in the US. Results show that are significant differences in how US and European institutions understand the impact of massive forms of open education and also how they perceive the efficiency of digital education and online learning.</span></span></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)0.015
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.268
GPT teacher head0.467
Teacher spread0.198 · 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