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Record W4282838049 · doi:10.1108/qae-01-2022-0023

Forming an academic program review learning community: description of a conceptual model

2022· article· en· W4282838049 on OpenAlex
Alana Hoare, Catharine Dishke Hondzel, Shannon L. Wagner

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQuality Assurance in Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsConceptual modelOriginalityConceptual frameworkCoachingKnowledge managementHigher educationQuality (philosophy)Public relationsComputer scienceSociologyPsychologyPolitical science

Abstract

fetched live from OpenAlex

Purpose Higher education institutions are required to evaluate program quality through cyclical program review processes. Despite often being considered the “gold standard” of academic review, there persists dissatisfaction with the lack of integration of program review findings into other planning processes, such as budgeting, assessment and strategic planning. As a result, the notion of program review action plans “collecting dust on the shelf” is so ubiquitous that the concept is normalized as an expected outcome. The purpose of this paper is to describe a conceptual model whereby teams of faculty members receive education and training from quality assurance practitioners and educational developers, access to institutional resources, opportunities for cross-departmental collaborations and collective advocacy to increase the capacity of faculty members to implement improvement goals resulting from program reviews. Design/methodology/approach The authors theorize that a professional learning community is a meaningful approach to program review and present a conceptual model – the Academic Program Review Learning Community (PRLC) – as an antidote to hierarchical, fragmented, compliance-oriented processes. The authors suggest that the PRLC offers a reliable institutional framework for learning through formalized structures and nested support services, including peer learning and external coaching, which can enhance the catalytic capacity of reviews. Findings The authors argue that postsecondary institutions should create formal structures for incorporating learning communities because, without a reliable infrastructure for collective learning, decision-making may be fragmented oridiosyncratic because of shifting demands, priorities or disconnected faculty. Originality/value A learning community model for program review fits well with a new way to think about program review because faculty are most engaged when they feel ownership over the process. Furthermore, few models exist for conducting program review; as a result, chairs and academics often struggle to conduct reviews without a coherent framework to draw upon.

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.

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)0.022
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.416
GPT teacher head0.564
Teacher spread0.148 · 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