Can score databanks help teaching?
BACKGROUND
Basic courses in most medical schools assess students' performance by conferring scores. The objective of this work is to use a large score databank for the early identification of students with low performance and to identify course trends based on the mean of students' grades.


RESULTS
We studied scores from 2,398 medical students registered in courses over a period of 10 years. Students in the first semester were grouped into those whose ratings remained in the lower quartile in two or more courses (low-performance) and students who had up to one course in the lower quartile (high-performance). ROC curves were built, aimed at the identification of a cut-off average score in the first semesters that would be able to predict low performances in future semesters. Moreover, to follow the long-term pattern of each course, the mean of all scores conferred in a semester was compared to the overall course mean obtained by averaging 10 years of data. Individuals in the low-performance group had a higher risk of being in the lower quartile of at least one course in the second semester (relative risk 3.907; 95% CI: 3.378-4.519) and in the eighth semester (relative risk 2.873; 95% CI: 2.495-3.308). The prediction analysis revealed that an average score of 7.188 in the first semester could identify students that presented scores below the lower quartiles in both the second and eighth semesters (p<0.0001 for both AUC). When scores conferred by single courses were compared over time, three time-trend patterns emerged: low variation, upward trend and erratic pattern.


CONCLUSIONS
An early identification of students with low performance may be useful in promoting pedagogical strategies for these individuals. Evaluation of the time trend of scores conferred by courses may help departments monitoring changes in personnel and methodology that may affect a student's performance.
Faculdade de Medicina, Universidade Federal da Bahia, Salvador, Bahia, Brazil.
Vitor Rosa Ramos
VR
de Mendonça
Bruno Bezerril
BB
Andrade
Alessandro
A
Almeida
Manoel
M
Barral-Netto
D016208:Databases, Factual; D004521:Educational Measurement / Q000379:methods*; D012577:Schools, Medical / Q000592:standards / Q000639:trends; D013337:Students, Medical; D013663:Teaching / Q000379:methods*
Acad Med. 1989 Aug;64(8):482-4
2751790
Acad Med. 1992 Sep;67(9):583-4
1520412
Med Educ. 2007 Oct;41(10):982-9
17908116
Acad Med. 2000 Oct;75(10 Suppl):S71-3
11031179
Med Educ. 1989 Sep;23(5):416-21
2796796
BMJ. 1999 Aug 28;319(7209):542-6
10463892
Acad Med. 2005 Oct;80(10):910-7
16186610
S Afr Med J. 1999 May;89(5):550-4
10416460
Med J Aust. 2008 Mar 17;188(6):349-54
18341459
Med Educ. 2004 Apr;38(4):425-34
15025644
Teach Learn Med. 2007 Summer;19(3):216-20
17594215
Am J Med Sci. 1996 Nov;312(5):214-8
8900383
Med Educ. 2001 Apr;35(4):374-80
11319002
Am J Surg. 1998 Jul;176(1):62-6
9683136
BMJ. 2002 Apr 20;324(7343):952-7
11964342
Adv Physiol Educ. 2009 Sep;33(3):139-43
19745038
BMC Med Educ. 2009 Jul 13;9:42
19594918
Acad Med. 1995 Aug;70(8):715-22
7646748
BMJ. 1998 Jan 31;316(7128):345-50
9487168
Acad Med. 1996 Oct;71(10 Suppl):S83-5
8940943