Enhancing Public Speaking Confidence: A Program for Higher Education Students with Fear of Public Speaking
Bibliographic record
Abstract
This study developed a structured intervention program based on Transformative Learning, Experiential Learning, and Humanistic Education principles to enhance public speaking confidence among university students experiencing public speaking anxiety, a common barrier to academic and professional success. The research had two objectives: (1) to examine the effects of the program on students’ public speaking confidence and anxiety levels, and (2) to identify the factors influencing the program’s success. A mixed-methods approach was employed. Quantitatively, a one-group pretest-posttest design measured changes in self-reported public speaking confidence and anxiety using standardized scales. Qualitatively, participant reflections and interviews were analyzed to uncover supportive factors. The results showed a significant improvement in students’ self-confidence for public speaking and a corresponding reduction in anxiety after completing the program. Participants reported feeling more comfortable and less fearful when speaking in front of an audience. Key factors contributing to the program’s effectiveness included gradual exposure to public speaking tasks, a safe and supportive learning environment, peer feedback, and guided self-reflection. The discussion connects these findings to the theoretical frameworks, explaining how experiential practice, transformative reflection, and humanistic support combined to foster greater confidence. This study offers practical implications for educators seeking to help students overcome public speaking fear, suggesting that incorporating structured practice and supportive pedagogies into the curriculum can substantially improve students’ public speaking skills and confidence. The article concludes with recommendations for implementing similar programs in higher education and directions for future research.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".