Promoting Discussions About Diversity in the Language Classroom: Digital Storytelling as an Exploratory Case Study
Bibliographic record
Abstract
Digital storytelling is a narrative technique that combines audio, video and animation elements. It can be used to provide opportunities for the promotion of cultural understanding in the university language classroom. In this study, pedagogy that combines digital storytelling techniques and computational technologies are explored, as part of language studies that can allow instructors to create an intercultural experience. The outcomes of an undergraduate learning exercise have been evaluated, along with this researcher’s experience as an instructor who used digital storytelling in a French-as-a-second-language classroom, and includes these students’ solicited feedback. In this case study, a group of students conducted internet research to explore the online cultural diversity and cultural differences of Francophone culture. They then created digital stories to represent this diversity. The findings have been analysed to evaluate the potential place of inclusivity and diversity tools in French-as-a-second-language learning, and to share the potential of this practical pedagogy approach for other university educators.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".