The Roles of L1 and Lexical Aspect in the Acquisition of Tense-Aspect by Thai Learners of English
Bibliographic record
Abstract
Investigating the L2 temporality, most previous studies within the Aspect Hypothesis framework focused on the basic meanings or prototypical uses of past morphology. The present study, however, including other less prototypical uses of past morphology, addresses 2 questions: (i) how the uses of simple past and past progressive morphology change as learners become more proficient in their target language; (ii) to what extent lexical aspectual class and L1 influence the uses of simple past and past progressive morphology. Using a cloze test as an elicitation task, this study analyzes data from 5 groups of Thai EFL learners at different proficiency levels. Results show that learners use past morphology more accurately as their L2 proficiency levels increase. The tense-aspect marking was, however, affected by lexical aspectual class. Learners first use simple past form on telic verbs, eventually extending its use to atelic verbs. The progressive form, on other hand, begins with atelic verbs and then extends to telic verbs. All learner groups, however, exhibit a higher rate of appropriate use of past morphology in the more prototypical uses than in the less prototypical uses. Additionally, L1 plays an important role in the tense-aspect marking. Learners at different proficiency levels, however, use different L1-influenced forms, suggesting that L1 influence is constrained by L2 development. Contributing to the body of research on L2 tense-aspect, this study shed light on the nature of difficulty learners experience in developing L2 tense-aspect system.
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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 | 0.000 | 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) | 0.001 | 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".