Business English Proficiency Acquisition Facilitated by Technology: Evaluations and Implications
Bibliographic record
Abstract
Online learning prospered in recent years, so did the research in this area. The COVID-19 pandemic has made it the default option of education. The design, implementation and evaluation of a completely online education model are of universal urgency. The learning purposes of Business English encompass the mastery of business knowledge and language abilities. This paper reviews the online teaching and learning of this course and tries to assess its effectiveness in equipping students with business related language competence. Students’ performances were measured in score comparisons; their levels of participation and activeness were captured in statistics across learning platforms; their perceptions on the advantages and disadvantages of this teaching model were collected in a survey and in-depth interviews. Research results show significant progresses have been achieved in students’ reading proficiency; language production in terms of speaking and writing was perceived to have been improved; the level of engagement was high. Challenges of this model have also been summarized and corresponding modifications would be proposed, to facilitate proficiency acquisition more efficiently.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".