Reading Strategy and Eye Movement of Japanese Students When Reading English as a Foreign Language
Bibliographic record
Abstract
This study reports on the relationship between reading strategies and eye movements observed when Japanese students attempt to comprehend English texts. Reading texts in an unfamiliar foreign language or with specialized content is generally difficult; therefore, computer support is essential. This study aims to classify and identify readers’ characteristics to customize support style. We focus on eye movements and reading strategies as readers’ characteristics, which depend on readers’ language ability and knowledge. In the experiment, we examined the reading strategies of Japanese readers of English using a questionnaire and factor analysis. We discovered two typical reading strategies: context-guessing and word-wise translation strategies. We also examined the effects of various reading strategies on eye movement and discovered significant differences in several eye movement features. We used a support vector machine to recognize the readers’ reading strategy based on the features of eye movement. The discriminator estimated the reader’s reading strategy with an F value of 0.88. Based on the results of this experiment, we expect this discriminator to help us understand readers’ reading strategies and support efficient reading comprehension strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.034 | 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".