Translingual approach in assessing academic writing for emerging multilingual writers in EMI higher education
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
• Standardized tests bring harmful, negative consequences for first-year multilingual writers. • Academic writing is not a set of independent linguistic competences. • Academic writing involves communities of practice including three agents, such as students, teachers, and tutors. • Our RWS framework proposes a holistic alternative to standardized testing for assessing multilingual academic writing. • We emphasize assessing students’ linguistic repertoire, including their context knowledge, skill development and language proficiency together. Drawing from the first author's teaching experience in a first-year disciplinary writing course and observations, this article develops a theory to address the limitations of standardized language tests in assessing multilingual writers’ skills. These tests emphasize formulaic tasks that do not align with the complexities of university writing activities, such as reflection, or argumentation. The first author's observation of 25 first-year writers engaging with institutional writing support services reveal that academic writing is a complex process, rarely captured by standardized tests. We propose the Reflective Writing Space (RWS) model, a paradigm-shifting framework that reconceptualizes writing assessment through three interconnected dimensions: content & context, skill development, and language use and proficiency. This model advocates for a more inclusive and interactive approach that actively engages students, tutors, and instructors in teaching writing. We conclude with practical recommendations for implementing the RWS framework to better support multilingual writers’ academic writing development.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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