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Record W4200302697 · doi:10.1177/0145482x211061619

Experiences Building Graphics Literacy Skills: Interviews With Teachers and Students

2021· article· en· W4200302697 on OpenAlexaff
L. Penny Rosenblum, Kim T. Zebehazy, Nicholas A. Gage, Carole R. Beal

Bibliographic record

VenueJournal of Visual Impairment & Blindness · 2021
Typearticle
Languageen
FieldMathematics
TopicCognitive and developmental aspects of mathematical skills
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGraphicsIntervention (counseling)Mathematics educationLiteracyPsychologyMedical educationPedagogyComputer scienceMedicine

Abstract

fetched live from OpenAlex

Introduction Participants’ perspectives are valuable in evaluating the effectiveness of an intervention. Methods Interviews were conducted with teachers of students with visual impairments and students who completed an intervention designed to build graphics literacy skills. Results Six themes were identified with corresponding subthemes. The intervention was reported to build students’ graphics literacy skills. Discussion Some students were able to generalize the strategies they learned to academic classes. Higher-level thinking skills challenged some students. Implications for practitioners A systematic approach beginning early can increase students’ graphics literacy skills. Teachers should provide ongoing opportunities for thinking and regulation of learning.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.028
GPT teacher head0.395
Teacher spread0.367 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations6
Published2021
Admission routes1
Has abstractyes

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