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Record W2773430719

Re-imagining A Learning Program For New Faculty: An Opportunity To Enhance Institutional Capacity

2017· article· en· W2773430719 on OpenAlexaboutno aff
Carol A Appleby

Bibliographic record

VenueScholarship@Western (Western University) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsnot available
Fundersnot available
KeywordsCapacity developmentCapacity buildingBusinessPublic relationsPolitical scienceEconomicsEnvironmental resource managementEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

This case study of one Ontario, mid-sized community college explores collaborative leadership processes and practices to shift the structure and conceptualization of a learning program for newly hired faculty members from a prescribed, linear model to a self-directed, multi-modal program. Examining organizational structure, institutional culture, adult learning theory, and systems thinking, the question, how can a professional development program best support new faculty in their teaching practice and new role, is addressed. The Change Path Model, grassroots and relational leadership practices are strategies utilized to guide the process for change. A distributed leadership approach is advocated to share decision making, embrace a new approach to an existing program and build institutional capacity. Democratic principles of inclusion, equity and empowerment underpin a dialogic approach to shifting mindsets to enact change. Building on the literature supporting socially constructed knowledge, communities of practice and inquiry, principles of andragogy, and universal design for learning, are proposed as mechanisms to reimagine the current program while simultaneously build institutional capacity and community. This organizational improvement plan proposes a reimagined vision to an existing program, that gives new faculty agency over their learning, while managing growth, meeting institutional obligations, and remaining accountable.

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)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0020.008
Open science0.0020.000
Research integrity0.0000.001
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 head0.490
GPT teacher head0.518
Teacher spread0.029 · 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
Published2017
Admission routes1
Has abstractyes

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