Arousing the College Students’ Motivation in Speaking English through Role-Play
Bibliographic record
Abstract
English as a tool of communication has been playing an important part in acquiring cultural, scientific and technical knowledge, for collecting worldwide information and carrying out international exchange and cooperation. Improving college students’ oral English level has become more and more important. Based on Richard E. Mayer’s theory of motivation and the advantages of role-play on the aspect of arousing the motivation of learning, this paper not only explores some of the theories of communicative teaching methods, but also proves the importance of the motivation of learning. Two kinds of English teaching activities for oral English class were designed which are oral English tests and role-play activity. The objective of this research is to arouse the college students’ motivation in speaking English. And the project hypothesis is that using the activity of role-play is more effective in arousing the college students’ motivation in speaking English than using oral English tests. The researcher divides the students who are the freshmen of Beijing City University into two groups - Target group and the Control group. And the researcher does the research by using observation notes, the questionnaire and the interview data collection methods. Through the four weeks research, it is proved that the students in the Target Group which use role-play activity become more interested in speaking English than the students in the Control Group which use oral English tests. So from the result of this research, we know that in our Chinese university, the teachers can use some communicative classroom activities such as role-play to arouse the students’ motivation of English speaking. There are also some limitations of this research for example, because the sample size was small, the results might not be typical; and the time of the research was too short, so maybe there were some unstable data.
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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 | 0.000 | 0.001 |
| 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".