The Relationship between Motivational Factors and Mandarin Performance in a Higher Education Institution
Bibliographic record
Abstract
Mastering Mandarin is an asset for international business. The purpose of this study was to ascertain therelationships between motivational factors and academic achievement. It provides a numerical estimate of howclosely or distantly these two variables are related. A quantitative analysis was used through a surveyquestionnaire among selected undergraduates learning Mandarin at Universiti Teknikal Malaysia Melaka.Besides, classroom assessments were also conducted to enrich the data. The findings showed that there was asignificant relationship between Mandarin scores and all the six motivational factors which were futureoccupation, intrinsic value and self-development, friendship, entertainment, Chinese influence and travel,requirement motivation, and Chinese culture and community. The strength of the relationship is moderate andpositive. The results are important in determining the content of Mandarin learning material which may lead toeffective and efficient learning process. Future studies should focus on more variables to enhance performance inlearning Mandarin.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".