Needs analyses for task-based curriculum design: How useful can it be for general purpose L2 courses?
Bibliographic record
Abstract
When designing a task-based language curriculum, it is essential to conduct a needs analysis (NA) to gain insight into the needs and goals of the student population (Long SLA and TBLT 6). This article illustrates the steps of the process by which an NA was designed and implemented in two university-level B2 level oral communication French as a Second Language courses to investigate students’ perceptions of the TBLT approach, students’ motivations, needs and desired outcomes in order to develop task-based syllabi. This article also addresses the challenges of responding to the needs of a diverse student population in order to determine thematic content and to design the authentic real-life tasks that would appeal to different individual students while taking into account the sociolinguistic and cultural context of the Francophone province of Quebec.The NA consisted of an analysis of the Common European Framework of Reference for Languages (CEFR), an online questionnaire given to both students (n = 48) and teachers (n = 8), and semi-structured interviews with students (n = 8). Despite the apparent heterogeneity of the participants in the two general purpose oral communication language classes, results suggest common, domain-independent goals and themes that would sufficiently cater to the needs and objectives of each individual in the group while also meeting the academic requirements of a university-level course.
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How this classification was reachedexpand
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".