Speaking Anxiety during MUET-CEFR Aligned Oral Presentations among ESL Learners in Perak
Bibliographic record
Abstract
The newly enforced MUET-CEFR aligned format is one of the government’s efforts to upscale Malaysian learners’ English proficiency level to be at par with international standards. However, the learners are reported to have high anxiety levels resulting in poor performance, especially in the speaking component. Hence, this study is conducted to investigate the learner’s anxiety levels, factors causing anxiety, and strategies to overcome speaking anxiety during oral presentations among MUET-CEFR ESL learners in Perak. The survey research design is employed for this study where a total of 130 participants took part by answering a three-section questionnaire on their background information, McCroskey’s Personal Report of Public Speaking Anxiety (PRSPA), and Nakatani’s Oral Communication Strategy Inventory (OCSI). Descriptive statistics are used to analyze the data and an independent sample t-test was conducted to investigate the differences in the learners’ strategy use based on their course types. A follow-up interview session and classroom observation were also conducted for data triangulation. The findings indicated many of the participants possess moderately high and high anxiety levels based on PRPSA scores. Meanwhile, the responses to OCSI implied that message reduction and alteration are the most used strategies to cope with their speaking anxiety during oral presentations. The findings also showed a statistically significant difference between Diploma and Form 6 students in the use of social affective, fluency-oriented, negotiation for meaning while speaking, accuracy-oriented, message reduction and alteration, and non-verbal strategies while speaking. The findings from this study suggest that teachers should scaffold students' oral presentation skills and manage their speaking anxiety for better performance in the MUET-CEFR aligned speaking examination.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".