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Record W2120445341 · doi:10.19173/irrodl.v11i1.763

An investigation of distance education in North American research literature using co-word analysis

2010· article· en· W2120445341 on OpenAlexvenueno aff
Albert D. Ritzhaupt, Michelle Stewart, Patryce Smith, Ann E. Barron

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
FundersUniversity of North Florida
KeywordsDistance educationWorld Wide WebSociologyLibrary scienceComputer sciencePedagogy

Abstract

fetched live from OpenAlex

The field of distance education is composed of a multiplicity of topics leading to a vast array of research literature. However, the research does not provide a chronological picture of the topics it addresses, making it difficult to develop an overview of the evolution and trends in the literature. To address this issue, a co-word analysis was performed on the abstracts of research articles found in two prominent North American research journals (<em>N</em> = 517), the <em> American Journal of Distance Education</em> and the <em>Journal of Distance Education</em>, between 1987 and 2005. The analysis yielded underlying trends and themes for three different periods (pre-Web, emerging Web, and maturing Web). Additionally, similarity index analyses were conducted across time periods. The pre-Web era was characterized by the need for quality and development. The emerging Web era was characterized by the development of theory. The maturing Web era was characterized by interaction and the use of tools for communication. The results demonstrate that the North American distance education research literature is characterized by having few consistent and focused lines of inquiry. Conclusions are provided.

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 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)0.014
metaresearch head score (Gemma)0.003
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 score0.055
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.081
GPT teacher head0.529
Teacher spread0.448 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations50
Published2010
Admission routes1
Has abstractyes

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