Examining the Linkage of Academic Performance and Attention by Uddin's Numeral Finding and Typo Revealing Tests: A Cross-Sectional Pilot Study in Undergraduate Students of Bangladesh
Bibliographic record
Abstract
Background: Attention is the state of applying the concentration to something and it's strongly linked to academic performance. The drive of this study was to analyze the academic performance and attention of undergraduate students. Methods: The study was implemented on 139 undergraduate students of Bangladesh selected from 9 universities from April to August 2018. In this study to investigate the attention of the students, the Uddin’s Numeral Finding (NF) and Typo Revealing (TR) tests were used. Results: In the NF test male students with last semester cumulative grade point average (CGPA) of 3.47 (highest) exerted the maximum 40% attention but female students exerted only 33.3% attention and their last semester CGPA was 3. Students with age > 22 years exerted maximum, 70.55%, and 35.2% attention in NF and TR tests respectively with last semester CGPA of 3.56 (maximum). In the NF and TR tests, highest, 89.73%, and 50.33% attention respectively were reported by 1st-year students with last semester CGPA of only 3.70. High-socioeconomic status students with last semester CGPA of 3.43 (lowest) exerted maximum 75.30% attention in NF test. There were no significant associations between variables. Conclusion: Attention is a very rudimentary function that often is a forerunner to cognitive functions. Individual differences in academic performance have been linked to differences in attention and intelligence.
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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 | 0.000 |
| 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 | 0.000 |
| 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".