Analysis of Extracurricular Programs That Affect College Students' Writing and Speaking Skills
Bibliographic record
Abstract
Communication skills such as writing and speaking contribute to learners' satisfaction with school life, academic achievement, and improvement of adaptability. In particular, the extracurricular activities experienced during college affect the acquisition of key qualities necessary for social life. The purpose of this study is to identify the extracurricular programs that affect the writing and speaking ability of college students. To confirm the purpose of this study, data were collected through an online survey conducted from April to May 2022 for current students at 4-year E-University located in Gyeonggi-do. The measurement tool is the Korea-National Survey of Student Engagement (K-NSSE). The Undergraduate Education Satisfaction Survey is a diagnostic tool that can obtain objective information on the quality and performance of undergraduate education by diagnosing undergraduate students' learning participation, learner psychology, high-efficiency program participation, and student performance. For the analysis method, frequency analysis and descriptive statistical analysis were performed. In addition, correlation analysis was performed to examine the validity between variables and to confirm multicollinearity. Finally, multiple regression analysis was performed to verify the influence of the non-examination program on the writing and speaking ability of college students. Results showed that the extracurricular program on the writing ability of college students had an influence in the order of learning mentoring, freshman orientation, professor's research project, and learning community activity. Moreover, the extracurricular program that affected the speaking ability of college students had an influence in the order of learning mentoring, professor's research project, freshman orientation, and learning community activity.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".