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Record W2174910133 · doi:10.19030/cier.v4i12.6659

Trial by Hire: The Seven Stages of Learning to Teach in Higher Education

2011· article· en· W2174910133 on OpenAlexaffabout
Patricia A. Post

Bibliographic record

VenueContemporary Issues in Education Research (CIER) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTransformative learningPsychologyScholarshipHigher educationNarrativePedagogyScholarship of Teaching and LearningFaculty developmentMedical educationTeaching methodMathematics educationTeaching and learning centerProfessional developmentPolitical scienceMedicine

Abstract

fetched live from OpenAlex

This phenomenological study describes seven stages of learning to teach at the university level. Through the use of narratives, twelve Canadian university professors reveal their beliefs and attitudes about teaching and learning as they struggle to become better teachers within various academic settings. The purpose of the study was to develop a better understanding of self-directed and transformative learning as it relates to adults who engage in on-the-job-training. Data analysis resulted in eight themes which occurred in seven developmental stages: Warming, Forming, Informing, Storming, Performing, Reforming, and Transforming. The findings suggest that a better understanding of the stages of learning to teach in higher education could: 1) enable faculty to gain confidence in their teaching ability earlier on in their careers (Bain, 2004); 2) assist faculty developers to better meet the changing needs of faculty (Cranton, 2001); and 3) guide administrators in their efforts to promote the scholarship of teaching and learning within their academic milieu (MacKeracher, 1996).

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)0.017
metaresearch head score (Gemma)0.008
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.385
GPT teacher head0.553
Teacher spread0.168 · 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.

Study designNot applicable
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

Citations11
Published2011
Admission routes2
Has abstractyes

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