The Impact of Open Discussion Sessions on Enhancing the Oral Communicative Abilities of Saudi English Language Majors at Buraydah Community College
Bibliographic record
Abstract
The importance of developing the communicative needs of English language majors has been found a fundamental concern of Buraydah Community college in Qassim University, Saudi Arabia. The aim of this study has been to identify English language speaking skill needs of English language majors and investigate the impact of using Open Discussion Sessions, as extracurricular speaking activities, on developing students’ oral communicative abilities. Thirty-five students and eleven English language teachers participated in the study. Data were collected quantitatively and qualitatively by means of survey questionnaires, semi-structured interviews and pre-post speaking test. Both descriptive and inferential statistics were employed in analyzing the raw data collected. The results of the study exposed a perceived need for developing Saudi EFL students’ speaking skill in English as their oral communicative abilities dramatically increased for their needs and interests were clearly identified and the methods for fulfilling those needs were more innovative. Post-test speaking results revealed significant development in students’ speaking abilities due to the use of Open Discussion Sessions that provided a relaxed learning environment void of worry and enhanced learners’ self-confidence through active involvement with real communicative situations with other students as well as with the instructors. Finally this study provided a framework with techniques and procedures that helped teachers to teach speaking skill more efficiently. Suggestions focused on incorporating Social Network Sites and visual cues to enhance students’ interactivity and participation outside the college borders.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".