Correlates of performance of engineering freshman students in basic mathematics courses

This study was conducted to determine whether the intellective factors such as entrance examination results, fourth year high school average and intelligence quotient and non-intellective factors such as age, gender, major in the College of Engineering, home supervision and choice of course applied for in college have any effect on the classroom performance of students and if any or all of these factors can effectively predict the classroom performance of the students as reflected in the final grade in Engineering Algebra (Engalge) and Trigonometry and Solid Geometry (Trigsol). The subjects of this study were students enrolled during the first term of SY 2000-2001 and 2001-2002 in the College of Engineering of DLSU-Manila who were randomly selected. Data were obtained through questionnaires designed for this study by the researcher and records from the Admission Office of the university. Mean, standard deviation, analysis of variance and regression were used in the statistical analysis of the data. The following were the findings of the study : 1. The over-all means of the intellective factors are 41.25 for language, 17.32 for reading, and 23.45 for mathematics. The mean of their HSGPA is 84.12 and the mean of their IQ is 55.95. Most of the students who participated in the survey are male in both school years 2000 and 2001 with male to female ratio of about 3 to 1. Based on the major, Electronics and Communication (ECE) majors comprised 40.30% of the total respondents for the two school years, Civil (CIV) majors comprised 19.30%, Industrial (IE) students comprised 13.8% Manufacturing engineering and management (MEM) students were 13.20% of the respondents, Chemical (CHE) students were 6.9% and Mechanical (MEE) students are 6.30% of the total respondents. In the home supervision category, 78% of the students are staying with their parents, 14.26% are staying in dormitories and 7.74% are staying with their relatives. The distribution according to choice shows most of the students who participated were accepted based on their first choice in the two school years. 2. Mathematics, HSGPA and IQ correlates significantly with both Engalge and Trigsol for both school years. Aside from these three factors there is a weak correlation between Engalge and reading, between Trigsol and reading and also with language. Among the other parameters or factors age has a weak correlation with language and a strong correlation between language and reading. 3. Mathematics, HSGPA, language and IQ can predict the classroom performance in Engalge and that mathematics, HSGPA, and major can predict the classroom performance in Trigsol. Regression equations were formulated based on the data