Comparative analysis of academic performance in business management education: foundation year vs. non-foundation students in UAE higher education
Bibliographic record
Abstract
This paper reviews the performance of students who graduated from the foundation year programme in business studies and compares their performance with non-foundation students at the higher national diploma equivalent to the foundation degree in the business programme. The study is conducted to understand how foundation students perform at the same level as their peers who have completed their schooling from the traditional school system in UAE. Data collected was secondary from the institution’s archive files of both the groups of students and their academic performance over fifteen modules. Descriptive statistical techniques were used to analyse the data. The results from the analysis found that the foundation students performed equally better as non-foundation students in most modules while in a few cores mandatory modules, students performed better than non-foundation students. The foundation programme students were not found to underperform in any module. In specialisation modules the data varied, however these modules were in marketing/finance/business in which the results were no longer comparable due to differences in specialisation, the field of study, and the type of assessments varied. Foundation students exhibited greater variability in their grades. This study contributes to scarce literature and research work in the area of foundation education in the UAE higher education teaching and learning and guides the future direction of studies based on the findings.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".