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Record W1656218917 · doi:10.19173/irrodl.v10i6.765

Online and blended communities of inquiry: Exploring the developmental and perceptional differences

2009· article· en· W1656218917 on OpenAlexaffvenue
Zehra Akyol, D. Randy Garrison, M. Yaşar Özden

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCommunity of inquiryBlended learningOnline communityContext (archaeology)PsychologyMultimethodologyQualitative propertyQualitative researchCognitionPerceptionMathematics educationPedagogyEducational technologySociologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

This paper discusses findings of a mixed method approach to a study of the development of a community of inquiry in an online and a blended learning environment. A graduate course delivered online and in a blended format was the context of the study. Data were gathered from the Community of Inquiry Survey, transcript analysis of online discussions, and interviews with students and the course instructor. Using multiple qualitative and quantitative data sources, the goal was to explore the developmental differences of the three presences (social, teaching, and cognitive) in the community of inquiry framework and students’ perceptions of a community of inquiry. The results indicated that in both the online and blended course a community of inquiry developed and students could sense each presence. However, the findings revealed developmental differences in social and cognitive presence between the two course formats with higher perceptions in the blended course.

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)0.010
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.266
GPT teacher head0.479
Teacher spread0.213 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations255
Published2009
Admission routes2
Has abstractyes

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