Bibliographic record
Abstract
Project-based instruction has gained some popularity in general education and in second-language (L2) education. However, a review of the literature shows discrepancies between teachers' and students' evaluations of this activity. For example, general education teachers and students find that project-based instruction creates opportunities for in-depth learning of subject-matter content, which fosters student independence and problem-solving skills. However, English as a Second Language (ESL) teachers' and students' evaluations show mixed results. Although some anecdotal reports and one systematic research study show ESL teachers endorsing project-based instruction because it provides opportunities for comprehensible output and integrated language teaching, there is evidence that ESL students and at least one ESL teacher are frustrated by this form of instruction. These students felt that project-based instruction prevented them from learning from the teacher and textbooks and from focusing on language skills. The ESL teacher felt a loss of student respect and noted a drop in student attendance. These discrepancies are discussed from philosophical, cultural, and linguistic perspectives. Recommendations for research and pedagogy are proposed. For example, it is suggested that a framework be developed to aid ESL teachers in assisting their multicultural students to understand the benefits of project-based instruction in L2 learning.
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.
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 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".