Impact of English Language Teaching and Learning through Language Laboratory in Engineering in Nepal
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The present article discusses the importance of language, in general, and English, in particular, in the context of engineering education in Nepal. It mainly discusses the importance and application of language laboratory for the enhancement of skills and proficiency of English language in the learners of Bachelor's level in engineering in Nepal. The main objective of the present article is to highlight the importance of teaching and learning of English language in the B.E. level in engineering by using language laboratory. In course of the present study, literature available in different accessible sources was reviewed for collecting necessary data and designing theoretical framework for the same. From the study, it has been found that language laboratory is tremendously helpful in creating favourable atmoshphere for language learning and helping the learners to acquire necessary language skills useful to them in sharpening their study at present and streamlining their research and innovative activities in their further studies in the future. English language is now the language of worldwide communication, and therefore, it is very essential for the students of engineering to be proficient in communication through English not only for grabbing job opportunities open at present but also to furthering their future research and innovative endeavors and publishing their reports and research articles based on them. Language Laboratory is highly instrumental for attaining ample proficiency in English language, the means of global communication.DOI: http://dx.doi.org/10.3126/jie.v10i1.10882Journal of the Institute of Engineering, Vol. 10, No. 1, 2014, pp. 94–103
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.
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 | 0.002 |
| 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) | 0.000 | 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 it