Online Academic Tutoring for English Language Learning: A Case Study of Receptive Skills Development in Ecuadorian Students
Bibliographic record
Abstract
This study examines the impact of online academic tutoring on Ecuadorian students of 5°, 6°, and 7° grades of Educación General Básica (EGB) on English receptive skills. Despite English's importance and integration into Ecuador's education system, language acquisition keeps facing some challenges due to resource limitations and diverse linguistic backgrounds. The research involved 52 students and 57 preservice teachers in an exploratory case study. Statistical data showed how digital education along with online academic tutoring contributed to improvements in the receptive skills of a group of English language students as well as let researchers see the most significant gains in 7th graders. Preservice teachers also developed pedagogically but encountered technical challenges. Findings underscore online tutoring's potential to address educational gaps, highlighting the need for greater investment in digital infrastructure and teacher training. Future research should examine the socio-emotional impact of online tutoring on learners' confidence and well-being.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".