Exploring EFL Views about the Value of Test Preparation Exam for TOEFL
Bibliographic record
Abstract
Test preparation for high-stakes English language tests has attracted growing research attention in the language assessment scope. However, little is known about what aspects of test preparation learners attend to and value. While theoretical and empirical research has focused on test-takers' attitudes toward test preparation and test-taking strategies, adequate attention to broader socio-political and ethical issues remains insufficient. Additionally, there exists a gap between achieving required test scores and actual academic communication abilities. Objective: This study aims to investigate EFL learners' views about the value of TOEFL test preparation courses based on Scriven's (1998, 2007) model that conceptualizes value as merit (intrinsic qualities), worth (contextual cost-effectiveness), and significance (assigned importance). Method: This descriptive study involved in 40 EFL learners enrolled in various academic programs at a University in Canada. The research subjects were students who had successfully gained admission to educational institutions after completing TOEFL preparation and achieving required scores. Results: Findings revealed that quality (merit) was linked to instructor characteristics and teaching methods, benefit (worth) was evaluated through effectiveness and adaptation to TOEFL and English skill development, while importance (significance) included participation in learning communities and motivation to study. Conclusion and Implications: This research provides educational insights for EAP program instructors at a University in Canada to understand students' experiences and perceptions of appropriate and effective English language learning support. The findings are also important given the increasing number of international students who require additional language competencies for academic success.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".