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Record W2604135653 · doi:10.19173/irrodl.v18i2.2806

Review and Content Analysis of the International Review of Research in Open and Distance/Distributed Learning (2000–2015)

2017· article· en· W2604135653 on OpenAlexvenueno aff
Olaf Zawacki‐Richter, Uthman Alturki, Ahmed Aldraiweesh

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2017
Typearticle
Languageen
FieldComputer Science
TopicOnline Learning and Analytics
Canadian institutionsnot available
FundersKing Saud University
KeywordsDistance educationOpen educational resourcesOpen educationLibrary scienceContent analysisEducational technologyOpen learningComputer scienceWorld Wide WebSociologySocial sciencePedagogyTeaching method

Abstract

fetched live from OpenAlex

This paper presents a review of distance education literature published in the International Review of Research in Open and Distance/Distributed Learning (IRRODL) to describe the status thereof and to identify gaps and priority areas in distance education research based on a validated classification of research areas. All articles (N = 580) published between 2000 and 2015 were reviewed for this study. An analysis of abstracts using the text-mining tool Leximancer over three 5-year periods reveals the following broad themes over the three periods: the establishment of online learning and distance education institutions (2000–2005), widening access to education and online learning support (2006–2010), and the emergence of Massive Open Online Courses (MOOCs) and Open Educational Resources (OER) (2011–2015). The analysis auf publication and authorship patterns revealed that IRRODL is a very international journal with a high impact in terms of citations.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.943
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0570.052
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.198
GPT teacher head0.505
Teacher spread0.308 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations54
Published2017
Admission routes1
Has abstractyes

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