Analogy as a Tool for the Acquisition of English Verb Tenses among Low Proficiency L2 Learners
Bibliographic record
Abstract
The teaching of English grammar to second language learners is usually a tedious, stressful and time consuming activity and even after all the effort, students have generally found these lessons boring and confusing. As such, innovative language instructors have been trying different approaches to the teaching of grammar in their classrooms. Using analogy as a tool for teaching is nothing new especially in science subjects such as Physics. In this comparative study however, analogy is used to teach English verb tenses to low proficiency L2 learners of English. The aim is to investigate the effects of using analogy as a tool for teaching English verb tenses. If using analogy is found to be effective, then it would be interesting to investigate to what extent it can be implemented in the low proficiency classroom. The analogy used has been creatively thought out and incorporated in the lesson with the help of innovative visual aids. A hundred and seventy-two pre-diploma students with low profiency levels of English were selected for this experiment. They were given a pre and post-test task before and after the lesson on verb tenses in order to determine whether the use of analogy implemented during the lesson had a favourable impact to learning. The test scores of the pre and post tests were then compared to verify the feasibility of using analogy in the lesson.
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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 | 0.006 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".