MétaCan
Menu
Back to cohort
Record W1996536206 · doi:10.1080/02568543.2013.796334

Matters of Design and Visual Literacy: One Middle Years Student's Multimodal Artifact

2013· article· en· W1996536206 on OpenAlexaff
Sylvia Pantaleo

Bibliographic record

VenueJournal of Research in Childhood Education · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsVisual literacyMultimodalitySemioticsPsychologyArtifact (error)LiteracySelection (genetic algorithm)Sign (mathematics)PedagogyMultimodal learningMeaning (existential)Visual learningMathematics educationVisual artsLinguisticsComputer scienceArtArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Meanings are created, represented, and communicated in multimodal ways in our contemporary world. The dominance of the visual in modern society requires students to be visually literate to understand, appreciate, interpret, and compose the content and the design of multimodal texts that include images. This article features the case study of Jaelyn, a Grade 6 student who participated in a classroom-based research project that explored developing student visual meaning-making skills and competencies by focusing specifically on a selection of visual elements of art and design in picturebooks and graphic novels. The semiotic analysis of Jaelyn's multimodal print text that was completed at the end of the research, as well as excerpts from her interview about her composition, revealed how her participation in the learning opportunities afforded during the explorative study influenced her sign-making. The article concludes with a discussion of pedagogical and assessment issues associated with teaching students about visual elements of art and design. Keywords: multimodaldesignvisual elementsmetalanguagecompositiontextsclassroom-based 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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.799
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.376
Teacher spread0.303 · 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

Citations21
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Research in Childhood EducationSame topicLiteracy, Media, and EducationFrench-language works237,207