Teachers’ and Students’ Perception on Acquiring English Vocabulary for Young Learners Using Mobile Apps in EFL Context
Bibliographic record
Abstract
This study investigated the teachers’ and students’ perceptions on language acquisition for young learners using Mobile App in EFL context. Many ways have been found to assist young learners in acquiring English as a Foreign Language. This study applied survey where the teachers’ perceptions were obtained from the observation, while the students’ perceptions were taken from the observation questionnaire. The respondent and participants were taken from six elementary schools in which there were twelve English teachers and 569 students of grade 4th in Indonesia. The result showed that teachers thought most students were anxious and didn’t have self-esteem and a good motivation while learning English. The teachers’ perceptions don’t always match the students’ ones or vice-versa in learning English in EFL context. It is expected that the mismatches of teachers’ and students’ perception are not greater than the match ones.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".