Bridging knowledge gaps: impact of remedial classes on first-year medical students in biochemistry – a cross-sectional study

Table 8 Logistic regression analysis showing the effect of different remediation tools on summative performance in students

Remediation tool	p value	Odds ratio	95% CI
Remediation tool	p value	Odds ratio	Lower	Upper
Mind map	0.831	1.107	0.436	2.814
Role play	0.905	0.921	0.238	3.568
Seminar	0.089	0.396	0.136	1.153
Quiz	0.172	1.952	0.748	5.093
Viva	0.700	0.838	0.342	2.054
SGD	0.595	0.778	0.308	1.965
Weekly test	0.188	0.415	0.112	1.538
Quick revision	0.568	1.519	0.362	2.312
Assignments	0.789	1.106	0.528	2.320
Grade incentives in FA	0.025*	6.186	0.431	13.609

Notes CI is confidence interval. ‘*’ represents statistically significant values. Student performance was categorized into two groups: ‘good’ and ‘average.’ Based on their marks, 28 students (54.9%) were classified as ‘good,’ and 23 students (45.1%) were classified as ‘average’ in their SA. These performance groups served as the dependent variable in the binary logistic regression analysis, with various remediation methods as the independent variables

ISSN: 1472-6920