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Record W2127042235 · doi:10.37119/ojs2012.v18i2.63

Walking Our Talk About Assessment With Preservice Teachers

2013· article· en· W2127042235 on OpenAlex
Elizabeth Munroe, Andrew Foran, Katarin MacLeod, Deborah Graham, Lisa Borden, A. Dudley Curry

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

Venuein education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsBachelorCurriculumMathematics educationPsychologyMedical educationBest practicePeer assessmentTest (biology)PedagogyMedicinePolitical science

Abstract

fetched live from OpenAlex

In this reflective study, six members of a Faculty of Education implemented or adapted research-informed assessment practices in their university Bachelor of Education teaching. These practices included aligning university course outcomes to assessment, separating achievement on university course outcomes from achievement of non-academic outcomes, collaboratively creating achievement indicators for provincial curriculum outcomes, co-constructing criteria with university students for assignments, setting up opportunities with university students for peer feedback before an assignment is submitted for marking, and administering and marking a test according to research-suggested practices. This article describes the implementation of these practices and analyzes the challenges and successes experienced as these teacher educators strove to model assessment practices that are expected of preservice teachers when they enter the profession. The primary goal of implementation was to increase congruence between teaching and practice in terms of assessment. Keywords: assessment; preservice teacher learning; self-study

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)0.000
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 score0.122
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.377
Teacher spread0.359 · 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