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Record W6943820592 · doi:10.17608/k6.auckland.5547631

Drawings of Feedback: Students in NZ

2017· dataset· en· W6943820592 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Auckland Data Repository · 2017
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsFrequently asked questionsLine drawingsQualitative researchData collection

Abstract

fetched live from OpenAlex

There are 193 drawings made by New Zealand primary, middle, and high school students when asked to draw a picture of feedback. This study builds on previous studies in which we asked students to draw pictures of assessment. <br>These files were analysed and described in a published article:Harris, L. R., Brown, G. T. L., &amp; Harnett, J. (2014). Understanding classroom feedback practices: A study of New Zealand student experiences, perceptions, and emotional responses. <i>Educational Assessment, Evaluation and Accountability, 26</i>(2), 107-133. doi:10.1007/s11092-013-9187-5<br><br>An earlier version was presented as:Harris, L. R., Brown, G. T. L., &amp; Harnett, J. (2012, April). <i>Student pictures of feedback: Feedback is for learning and from teachers.</i> Paper presented at the 2012 AERA Annual Meeting of the American Educational Research Association, Vancouver, BC.<br>

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 categoriesMeta-epidemiology (narrow), Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0080.005
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 head0.023
GPT teacher head0.283
Teacher spread0.261 · 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.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2017
Admission routes1
Has abstractyes

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