A Study on Teaching Business Communication/English in Indian Classroom
Bibliographic record
Abstract
The aim of this article is to discuss on teaching Business Communication in classroom to Business Administration degree programme students. Indeed, teaching Business Communication in classroom was different experience when compared with Technical English for B.Tech students. The syllabus for Business Communication (English) was also peculiar whereas Business Communication taught in other institutions. Usually in Business Communication we will have components of letter writing (Business letters), writing memos, agendas, circulars, advertisements, Business report writing and Business vocabulary, but in our university we had even Linguistic elements in syllabus such as Phonetics, Word stress, and Sentence stress. In addition to, other portions are Linguistic communication? Barriers to communication, Dyadic communication, Idioms and Phrases, Proverbs, Listening skills, Movie talk and Reading skills. The only thing what any one can find on students with this type of curriculum is that they cultivated more interest to read theory part (Linguistic communication, Barriers to communication, Dyadic communication) than technical matters (Phonetics, Word stress, Sentence stress). Yet they enjoyed Phonemic symbols while spelling their sounds. Perhaps the result point of view allowed them to be inspired with theory content rather than linguistics. Hence, might be learners earned enough experience in having command over English language. Concerned with learning materials it was difficult to search for Linguistic communication. The students felt happy with the academic syllabus due to teaching methodology than the given syllabus. The adopted teaching methodology was communicative language teaching with usual lecturing method. Lecture was lectured with the help of the technical tool power point presentation. The downloaded materials with pictures (power point lessons with pictures) attracted young minds. It is wonder that Business administration students reading Linguistic aspects and sitting for final written exam. Therefore, this paper exposes teaching-learning process of the teacher and student in teaching Business Communication to them.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".