Pass or Failure of Students in The “WASSCE” Mathematics Mock Examination: The Binary Logistic Regression Model (Published)
This study predicts students’ pass or failure in the WASSCE mathematics mock examination. Three hundred (300) Senior High School (SHS) students, comprising one hundred and fifty-nine (159) males and one hundred and forty-one (141) females from selected Senior High Schools in the Cape Coast Municipal District of the Central Region, participated in the study. The binary logistic regression model comprising continuous and categorical predictor variables was adopted. The results indicated that the raw score coefficients for Math self-concept, Math attitude, Instructional strategies and methods, Teacher competency in math, and Gender, were positive and significant (P < .05), while that of High Socio-Economic Status (SES) was negative and significant (P < .05). The adjusted odds ratio for gender was 2.24, with a C. I of .45 -11.02. The adjusted odds ratio for mathematics self-concept was 7.40, with a C. I of 2.32 – 23.60, while, the adjusted odds ratio for Instructional strategies and methods was 31.67, with a C.I of .97 -15.40. An implication of this study is that mathematics teachers should not downplay the role these significant predictors play in the teaching and learning of the subject. Mathematics teachers must create a conducive atmosphere in the classroom to support active learning among students. The study concludes that to increase the probability of students passing the examination, the value of the exponential term in the computation of the probability must reduce considerably. This can be realised through an effective combination of the predictor variables.
Citation: Charles Kojo Assuah, Rufai Sabtiwu, Robert Benjamin Armah, Grace Abedu, & Fusheini Awulo(2022) Pass or Failure of Students in The “WASSCE” Mathematics Mock Examination: The Binary Logistic Regression Model, International Journal of Education, Learning and Development, Vol. 10, No.4, pp.38-56
Students’ Mathematics And English Language Mock Examination As Predictors To School Certificate Performance In Physics. (Published)
This study was an ex-post-facto survey, which investigated students’ mathematics and English language (mock) achievement as predictors to school certificate performance in Physics, using two hundred and fifty (250) students randomly selected from public secondary schools in Rivers State. The data was analyzed using the Pearson Product Moment Correlation Coefficient and t-test inferential statistics. In order to predict the performance of students on physics based on their performances in Mock examinations on mathematics and English language, the multiple regression analysis (R2) was used. Results showed that there was a significant relationship between the performance of students in English language Mock examination and their performance in physics. There was also a significant relationship between students’ performance in mathematics mock examination and their performance in physics (SSCE). Although there exist positive dependence of performance of physics (SSCE) on their collective performances in. mock examinations on mathematics and English language, the predictor variable Y1=38. 79 EM+0.17Mm where the partial multiple regression coefficients are 38.79 and 0.17 respectively. Based on these findings, it was recommended that learners of physics should be involved in acquisition of knowledge in mathematics and English language, if their performance in physics should improve.