PREDICTIVE MODELLING OF STUDENTS' ENROLMENT AND CHOICE PATTERNS IN PAINTING AND GRAPHICS PROGRAM OF LAUTECH ART SCHOOL, NIGERIA

Abstract

Predictive modelling of students’ enrolment is a robust methodological approach for evaluating the present and future of academic programme. This study analysed the enrolment trends in Painting and Graphics specialization in LAUTECH Art School. It explained the factors influencing enrolment trend. It also examined relationship between Painting and Graphics and predicted from the model generated for enrolments. Secondary data used were obtained from the Departmental records on enrolment and specialization status of students’ for a period of 19 years. Primary data were obtained through questionnaires administered to randomly selected students from the departmental matriculation list using a Table of Random Numbers. Both Descriptive and Inferential techniques were used to analyze data. Descriptive statistics used were frequency and percentage to summarize findings, while inferential techniques used included Least-Square method, Exponential smoothing, Correlation and Analysis of Variance (ANOVA). Least Square results revealed that students’ enrolment in both Painting and Graphics experienced an upward trend at a very slow speed, but a faster speed in Graphics than in Painting. This was influenced by positive values of the regression (b = 114) and correlation coefficient (r = + 0.4862) of Graphics against (b = 0.2241) and (r = + 0.333) of Painting. There were variations in reasons given by students’ across Painting and Graphics as factors influencing their enrolment for a particular specialized area. Student’s personal interest was the main factor as 24.24% and 33.33% of Painting and Graphics students respectively indicated such. There were also moderate positive correlation between students’ enrolment in Painting and Graphics. The study therefore predicted that enrolment in Graphics will triple enrolment in Painting in five years’ time using models Y = 5.1474 + 0.2241x and Y = 4.807 + 1.114x generated for Painting and Graphics respectively as X is 23 in 2026/2027 academic session. The study therefore concluded that enrolment in Graphics is experiencing exponential growth. It is therefore suggested at this time that a concerted and intensified effort be ensured not only to teach students’ intellectually, but also to give them all round education that will make them have prowess both theoretically and in practical advancement in their specialized area of study. 

Keywords: Enrolment, Painting, Graphics, Modelling, Prediction, LAUTECH.