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Record W4289531011 · doi:10.1558/wap.21124

Illuminative evaluation of an intercultural-competence-focused first-year writing curriculum

2022· article· en· W4289531011 on OpenAlex

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

VenueWriting & Pedagogy · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCurriculumCompetence (human resources)PedagogyIntercultural competenceContext (archaeology)Mathematics educationPsychologySociologyGeography

Abstract

fetched live from OpenAlex

This article explores illuminative evaluation as a method to reflectively assess a pilot implementation of an intercultural-competence-focused first-year writing curriculum at a US large public university. The goal of this curriculum is to promote integration of diverse student populations on our university campus, while developing all students’ intercultural competence and writing skills. In this article, we present practitioner reflections on classroom experiences and collaborative design of our approach to data analysis. These reflections show how an illuminative, context-rich approach to an early phase of a writing pedagogy research project shapes a holistic curricular evaluation. Illuminative evaluation drew our attention to the interaction between teaching and curriculum evaluation as well as to how this approach promotes an invitational and exploratory approach to teacher research.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.159
GPT teacher head0.446
Teacher spread0.287 · 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