Young Learners’ Perceptions on the Implementation of Online English Proficiency Test
Bibliographic record
Abstract
The present study made use of Cambridge Online English Test for Children and Young Learner to explore how young learners perceived the implementation of an online test and to what extent the ICT backgrounds and English exposures correlated to their online English test achievement. Three data collection strategies were used to gather the data that involved second to sixth-grade elementary school students as the participants. The instruments were: 1) Online English Proficiency Test for Young Learners; 2) observation field notes; and (3) interviews. The findings revealed that students’ test scores diverse as their grade levels were also various. The mean score was 10.53 which could be categorized into Movers level which was in the middle level. It was also found that the three-quarter of the participants declared that they preferred having an online test as it gave them new experiences and comfortable feeling with taking a test on laptop or smartphones. From further investigation to the randomly selected six students, it was revealed three factors were majorly influential for young learners in benefitting the digital technology use. They were: 1) family socio-economic background; 2) parental involvement in children’s digital media use; and 3) learners’ personal motivation in using the digital media.
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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 | 0.002 | 0.006 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".