A Gallery of Multimodal Possibilities in a Graduate Course on Learning Differences in Education
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.046 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".