title: Identifying student profiles and their impact on academic performance in a Brazilian undergraduate student sample.
abstract: The recognition of the student profile provides strategic information for planning educational policies in the university environment. The aims of this study were to identify natural segmentation of freshman undergraduate dental students based on demographic, socioeconomic and educational variables, and to subsequently investigate their impact on academic performance of Brazilian undergraduate students. Cluster analysis (two-step algorithm) was used to segment students who entered dental school in the time period from 1999 to 2001 (n=158) into groups based on responses to a questionnaire completed by students at the time of the admission examination. Clustering analysis revealed three natural groups. Age, the parents' level of education, and performance on the first admission test were the most important variables for cluster segmentation. Cluster 1 (n=42; 26.6%) was characterized by female students with higher socioeconomic status and better previous educational indicators. Cluster 2 (n=62; 39.2%) represented disadvantaged socioeconomic profiles, with a predominance of females and older students. Cluster 3 (n=54; 34.2%) showed similar socioeconomic characteristics to cluster 1, except for male prevalence, higher age, and experiencing difficulty in the admission test. Clusters' academic performance was satisfactory in both overall course and course groups (grade point average of at least 7.0), with average ranging from 7.89 (SD=0.44) to 8.13 (SD=0.31) and 7.37 (SD=0.75) to 8.31(SD=0.26), respectively. Our findings provide encouraging evidence for the current context of equality of access to education and reveal the importance of financial support to maximize successful educational experiences of socioeconomically disadvantaged dental students.
authors.affiliation: School of Dentistry, Federal University of Goias, Goiania, Goias, Brazil.
authors.forename: E T
authors.initials: ET
authors.lastname: da Silva
authors.forename: M
authors.initials: M
authors.lastname: de Fátima Nunes
authors.forename: L B
authors.initials: LB
authors.lastname: Santos
authors.forename: M G
authors.initials: MG
authors.lastname: Queiroz
authors.forename: C R
authors.initials: CR
authors.lastname: Leles
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D003479:Curriculum; D003710:Demography; D004521:Educational Measurement; D005260:Female; D006801:Humans; D008297:Male; D012189:Retrospective Studies; D012575:Schools, Dental / Q000458:organization & administration; D012959:Socioeconomic Factors; D013335:Students, Dental / Q000706:statistics & numerical data*; D055815:Young Adult