Effects of Task-based Language Teaching (TBLT) Approach and Language Assessment on Students’ Competences in Intensive Reading Course
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
Task-based language teaching on the purpose of enhancing students’ communicative skills and involving them actively in the authentic context has long been highlighted in recent years in tertiary English language teaching. This paper proposes a framework of task-based teaching approach and language assessment in intensive reading class based on the researcher’s own teaching practice to explore positive impacts on students’ competences. This is done in the context of both oral presentation and written reports of first undergraduate English major students. The research method consists of semi-structured interviews and a questionnaire with 18 questions pointing to different aspects in the learning and teaching processes, aiming to explore what impacts it has on students’ competence in both second language acquisition and at cognitive level. In this empirical study, all the findings indicate that TBLT applied in Chinese English teaching class is very effective and beneficial for the enhancement of Chinese English learners.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| 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