Language learners’ drawings and textual commentaries as a way to envision goals and aspirations for future language use
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Written and spoken language are not the only ways to illustrate thinking. Incorporating arts-informed and multimodal ways to communicate can offer new insights for higher education language teaching and learning practices. This study investigates how Finnish as a second language students’ drawings as visualizations support an arts-informed approach to knowledge production in the initial years of language learning and proficiency in higher education in Canada. Further, it explores how students of Finnish represent their aspirations and objectives for their future language use and study through these embodied visualizations. The article focuses on how students visualize their aspirations to learn and use language without having to look for support from English. Grounded in reflective arts-informed language pedagogy, this study employs multisemiotic content analysis to examine a selection of students’ drawings. Through drawing, students visualize their imagined potential selves as future language users in different situations, activities and tasks and with different people. While language learners traditionally express their thoughts through oral and written language, and commonly in English, this study shows that drawings offer an alternative and artistic avenue for knowledge transmission and communication in the early stages of the language learning trajectory. Through reflective research practice, his study also addresses some implications of integrating arts-informed teaching and learning practice into second language pedagogy, encouraging instructors to adapt arts-informed teaching methodologies to align with students’ individual learning trajectories.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it