Bibliographic record
Abstract
Electronic reference tools viz. dictionaries, wikis, explorers, translators etc. tender a great support to the EFL learners in understanding different aspects of the lexical, syntactical, phonological and semantic complexities. In view of the usefulness of online reference tools, it is hypothesized that extensive use of the tools in classrooms expedites the acquisition of the language. In an effort to establish the correlation between the effective use of the tools and the acquisition of English as a foreign language, it is proposed to take up a study that aims at finding out the impact of using Electronic reference tools in EFL classrooms. The study was conducted with two groups of learners of English as a foreign language who completed their yearlong English language course that is mandatory for continuing their bachelors’ course. By using purposive sampling method the participants of the study were selected and were divided into group A and group B based on the levels of success in their acquisition of English required for continuing their bachelor’s courses. The levels of success were determined based on a diagnostic test conducted at the end of their one-year English language program, and graded in light of the Interagency Language Round Table Scale (ILRS). The students who obtained ILRS +3 level and above in the test were included in group A, and the students who obtained below ILRS 3 level are included in group B. The final sample of the students in both the groups were provided with a questionnaire of Likert scale that is followed by face-to-face interviews. By employing mixed method model of research, the correlation between their use of online reference tools and their level of success in learning the language were established. The results show a positive correlation that confirms the use of online and electronic reference tools is an essential learning strategy both within and out of the classroom learning as well as for expediting the learning process.
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 | 0.000 | 0.067 |
| 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 | 0.001 | 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".