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Record W7086598898

Good Teachers, Scholarly Teachers and Teachers Engaged in Scholarship of Teaching and Learning: A Case Study from McMaster University, Hamilton, Canada

2011· article· en· W7086598898 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipScholarship of Teaching and LearningTeaching and learning centerTeaching methodHigher educationValue (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

This paper defines and operationalizes definitions of good teaching, scholarly teaching and the scholarship of teaching and learning in order to measure characteristics of these definitions amongst undergraduate instructors at McMaster University. A total of 2496 instructors, including all part-time instructors, were surveyed in 2007. A total of 339 surveys were returned. Indices of good teaching, scholarly teaching and scholarship of teaching and learning were developed. The data illustrated a strong correlation between good teaching and scholarly teaching and between scholarly teaching and scholarship of teaching and learning. The perceived value placed upon teaching varied across the different Faculties. New instructors and those engaged in scholarly teaching and scholarship of teaching and learning perceived teaching to be more valued than their peers.\nLe présent article définit et opérationnalise les définitions d’enseignement efficace[1], d’enseignement érudit[2] et de la publication sur l'enseignement supérieur[3] afin de mesurer les caractéristiques de ces définitions chez les enseignants de premier cycle de l’Université McMaster. Au total, 2 496 enseignants, y compris tous ceux qui travaillent à temps partiel, ont été sondés en 2007 et 339 questionnaires ont été retournés. Les chercheurs ont élaboré des indices d’un bon enseignement, d’un très bon enseignement et d’un excellent enseignement. Les données illustrent une forte corrélation entre un bon enseignement et un très bon enseignement, de même qu’entre un très bon enseignement et un excellent enseignement. La valeur perçue accordée à l’enseignement variait selon les différentes facultés. Les nouveaux enseignants pratiquant un très bon enseignement et un excellent enseignement trouvaient l’enseignement plus utile que leurs pairs.\n[1] good teaching, [2] scholarly teaching, [3] scholarship of teaching and learning

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)0.013
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0010.008
Open science0.0010.001
Research integrity0.0000.007
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 head0.229
GPT teacher head0.368
Teacher spread0.139 · 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 designObservational
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

Citations0
Published2011
Admission routes1
Has abstractyes

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