MétaCan
Menu
Back to cohort
Record W2117912030 · doi:10.1080/0144341032000160146

Teacher motivation to implement an educational innovation: factors differentiating users and non-users of cooperative learning

2004· article· en· W2117912030 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.

Bibliographic record

VenueEducational Psychology · 2004
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsConcordia University
Fundersnot available
KeywordsExpectancy theoryPsychologyContext (archaeology)Variance (accounting)Adaptation (eye)Value (mathematics)Resistance (ecology)Cooperative learningMathematics educationKnowledge managementTeaching methodSocial psychologyComputer science

Abstract

fetched live from OpenAlex

This study applied expectancy theory to integrate the numerous and disparate explanations that researchers and educators have proposed to account for teacher resistance to implementing cooperative learning as an educational innovation. The cooperative learning implementation questionnaire (CLIQ) contained 48 items grouped under three broad motivational categories: perceived value of the innovation, expectancy of success, and perceived cost. These items accounted for 42.3% of the total variance in self-reported use of cooperative learning among 933 teachers. Expectancy of success issues were most important in differentiating users and non-users, suggesting that increased emphasis on professional development should be used to enhance teachers' beliefs that they can succeed in implementing an innovation in their own context. This may require both follow-up support and adaptation of the innovation.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.457
Teacher spread0.373 · 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