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Record W1947335013 · doi:10.21432/t25s3m

Breaking the ice: Supporting collaboration and the development of community online

2006· article· en· W1947335013 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDistance educationPsychologyTransactional analysisPoint (geometry)Computer-mediated communicationOnline learningTransactional leadershipOnline communityCollaborative learningEducational technologyPedagogySocial psychologyComputer scienceThe InternetMultimediaWorld Wide Web

Abstract

fetched live from OpenAlex

This study explores the concept of transactional distance, a term coined by Moore (1993), which relates to the distance that exists in all learning relationships and can be more evident and potentially problematic in online learning environments. Reducing this psychologically perceived distance to help learners develop social presence in support of collaborative relationships and the development of community in online learning environments is the purpose of this research. Icebreakers are fun activities that help people get to know each other. These activities can potentially ameliorate the perceived distance in online learning environments. Two author-developed icebreakers were used in a preliminary study involving university undergraduates and instructors in online environments. Respondents took part in an icebreaker at the start of a semester and at the mid-point after which they completed a questionnaire about perceived value of icebreakers. Early results were positive and have led to recommendations for practice.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.011
GPT teacher head0.299
Teacher spread0.288 · 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