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Record W1480396549 · doi:10.59236/ijea15n18

A Gallery of Multimodal Possibilities in a Graduate Course on Learning Differences in Education

2014· article· en· W1480396549 on OpenAlexaff
Cynthia M. Morawski, Kimberley Hayden, Aileen Nutt, Nikolas Pasic, Angela Rogers, Violet Zawada

Bibliographic record

VenueInternational journal of education and the arts · 2014
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCourse (navigation)PedagogyMathematics educationPsychologyTeaching methodHigher educationGraduate studentsEngineering

Abstract

fetched live from OpenAlex

Pertinent research literature recognizes the importance of using multimodalities to enhance and extend ways of learning across the curriculum in such subject areas as literacy, geology, media studies, physical education, social studies and disabilities studies. As an action researcher who constantly seeks ways to improve my own classroom practice, I offered multimodal opportunities to the students in my graduate class on learning differences to enhance their capacity to participate in both in-class and out-of-class assignments. Five students representing the areas of nursing, counseling, arts education, and classroom teaching, accepted my invitation to express a major assignment--a personal narrative on learning differences in multimodal forms. With feelings and thoughts ranging from skepticism to inspiration, these five students placed themselves in the vulnerable and risky space of the unknown and represented the theoretical and practical aspects of their narratives via sculptures, beaded canvases, a book of collage art and an assemblage of popular culture. Each student created a unique work woven together from prior experiences, significant readings, and specific theoretical underpinnings. They all agreed that the use of multimodalities encouraged them to draw on various elements of personal resources, such as emotion and imagination, to reconsider learning difference as a multidimensional and fluid concept. The possibilities for multimodal learning in a graduate class allowed students to hear, see, and feel each of their positions on difference while also examining collectively their individual expressions of learning differences in education.

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)0.001
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 score0.358
Threshold uncertainty score0.171

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.061
GPT teacher head0.411
Teacher spread0.350 · 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 designObservational
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

Citations3
Published2014
Admission routes1
Has abstractyes

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