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Record W2318674301 · doi:10.1177/1541344614540335

Developing a Survey of Transformative Learning Outcomes and Processes Based on Theoretical Principles

2013· article· en· W2318674301 on OpenAlexaff
Heather L. Stuckey, Edward W. Taylor, Patricia Cranton

Bibliographic record

VenueJournal of Transformative Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTransformative learningPsychologyCronbach's alphaScale (ratio)Learning theorySurvey data collectionPedagogyMathematics educationDevelopmental psychologyPsychometricsMathematics

Abstract

fetched live from OpenAlex

The purpose of this research was to develop an inclusive evaluation of “transformative learning theory” that encompassed varied perspectives of transformative learning. We constructed a validated quantitative survey to assess the potential outcomes and processes of how transformative learning may be experienced by college-educated adults. Based on a review of the rational/cognitive, extrarational, and social/emancipatory perspectives of transformation learning theory, the survey reflects the assumptions underlying these perspectives through survey items and allows the survey to be used in multiple contexts both inside and outside the formal classroom. Survey development included a comprehensive review of the literature, external review by experts in adult education, focus groups for clarification of the items, the calculation of interitem correlations for each scale and cross-scale correlations, and the calculation of Cronbach’s α reliability coefficients. This survey has the potential to advance the study of transformative learning by being inclusive of several existing theoretical perspectives that have common outcomes.

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)0.038
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.064
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.344
Teacher spread0.310 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations103
Published2013
Admission routes1
Has abstractyes

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