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Record W3005729729 · doi:10.22158/grhe.v3n1p1

Strategic Approaches to SoEL Inquiry Within and Across Disciplines: Twenty-year Impact of an International Faculty Development Program in Diverse University Contexts

2020· article· en· W3005729729 on OpenAlexaff
Andrea S. Webb, Harry Hubball, Anthony Clarke, Simon Ellis

Bibliographic record

VenueGlobal Research in Higher Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsScholarshipTransformational leadershipContext (archaeology)Educational leadershipVariety (cybernetics)Professional developmentSociologySituatedPedagogyFaculty developmentFace (sociological concept)Scholarship of Teaching and LearningStrategic planningHigher educationEngineering ethicsPolitical sciencePublic relationsManagementTeaching methodSocial scienceEngineering

Abstract

fetched live from OpenAlex

Educational leaders on university campuses around the world are increasingly required to account for the effectiveness, efficiency and quality of their undergraduate and graduate degree programs. The S Scholarship of Educational Leadership (SoEL) in higher education is a distinctive form of strategic inquiry for educational leaders with an explicit transformational agenda of educational practices within and across the disciplines in diverse university contexts. This paper examines complex institutional challenges and strategic approaches to SoEL inquiry. In an international faculty development context, data suggests that educational leaders from a variety of disciplines face significant challenges when undertaking SoEL inquiry. Strategic institutional supports and customised professional development are key to facilitating SoEL inquiry in higher education. Further, SoEL is inherently situated, socially mediated, and responsive to the professional learning needs and circumstances of educational leaders within and across the disciplines in diverse university contexts.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.514
GPT teacher head0.537
Teacher spread0.023 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2020
Admission routes1
Has abstractyes

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