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Record W2969685073 · doi:10.3389/feduc.2019.00094

Toward a Differential and Situated View of Assessment Literacy: Studying Teachers' Responses to Classroom Assessment Scenarios

2019· article· en· W2969685073 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFrontiers in Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsQueen's University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSituatedLiteracyMathematics educationSituated learningComputer sciencePedagogyPsychologyArtificial intelligence

Abstract

fetched live from OpenAlex

Research has consistently demonstrated that teachers’ assessment actions have a significant influence on students’ learning experience and achievement. While much of the assessment research to date has investigated teachers’ understandings of assessment purposes, their developing assessment literacy, or specific classroom assessment practices, few studies have explored teachers’ differential responses to specific and common classroom assessment scenarios. Drawing on a contemporary view of assessment literacy, and providing empirical evidence for assessment literacy as a differential and situated professional competency, the purpose of this study is to explore teachers’ approaches to assessment more closely by examining their differential responses to common classroom assessment scenarios. By drawing on data from 453 beginning teachers who were asked to consider their teaching context and identify their likely actions in response to common assessment scenarios, this paper makes a case for a situated and contextualized view of assessment work, providing an empirically-informed basis for reconceptualizing assessment literacy as negotiated, situated, and differential across teachers, scenarios, and contexts. Data from survey that presents teachers with assessment scenarios are analyzed through descriptive statistics and significance testing to observe similarities and differences by scenario and by participants' teaching division (i.e., elementary and secondary). The paper concludes by considering implications for assessment literacy theory and future related 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)0.001
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 score0.057
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.370
Teacher spread0.348 · 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