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Record W1985525340 · doi:10.5539/ass.v7n11p13

Teaching Induction Program: Framework, Design and Delivery

2011· article· en· W1985525340 on OpenAlexvenueno aff
Elaine Huber, Susan Hoadley, Leigh Wood

Bibliographic record

VenueAsian Social Science · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Quality (philosophy)Professional developmentMedical educationProgram Design LanguageTeaching and learning centerTeaching methodFaculty developmentKey (lock)Computer sciencePsychologyMathematics educationPedagogyMedicine

Abstract

fetched live from OpenAlex

Professional development is a key factor in ensuring teaching staff are confident in the delivery of quality teaching. Professional development is especially relevant for staff who are new to teaching and are required to teach in the context of the large and increasingly diverse student cohorts, prevalent in the Faculty of Business and Economics. The Teaching Induction Program (TIP) addresses this need by modelling best practice in tertiary learning and teaching, delivered in a blended mode. The foundation of TIP is a series of videos, using the student voice, and this feedback is the lens through which knowledge and skills in learning and teaching are developed. During the program, participants build community around their experiences of implementing the teaching skills they have developed, and thereby reflect upon their efficacy for students’ learning. Participant feedback is used to inform the development of following iterations of TIP and this has led to two additional programs being planned, using the voices of new teachers or tutors as well as experienced teachers.

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)0.007
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.860
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.002
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.214
GPT teacher head0.441
Teacher spread0.228 · 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 designOther design
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

Citations6
Published2011
Admission routes1
Has abstractyes

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