Predicting students’ final grades for regulating the supervision of academic activities: A model of continuous assessment practices, teaching effectiveness and students’ personal studies

Abstract

The study was conducted to determine the predictive strength of a model of continuous assessment practices, teaching effectiveness and students’ personal studies for predicting students’ final grades. Thus the study investigated the influence of continuous assessment practices, teaching effectiveness, and students’ personal studies on the test scores of some selected junior secondary school students in Health and Physical Education in Egor Local Government Area of Edo State. Three null hypotheses were formulated to guide the study. The hypotheses were tested at 0.05 level of significance. The population of the study was 4,042 while the sample size was 200 randomly selected from JSS III in Egor LGA of Edo State. The instrument used for data collection was the questionnaire with reliability co-efficient of 0.89. Data collected were analyzed using the Pearson Product Moment Correlation Statistics and the multiple regression statistics. The major findings of this study were are as follows: The multiple regression coefficient of prediction of students’ final grade with ratings of continuous assessment practices, teaching effectiveness and students’ personal studies is significant (R = 0.65, p ≤ 0.00). The net regression coefficient of prediction of students examination grades with ratings of continuous assessment practices is positive and significant (B = 0.54, p ≤ 0.00). The net regression coefficient of prediction of students final grades with ratings of students personal studies is positive and significant (B = 0.31, P ≤ 0.00). The net regression coefficient of prediction of students’ final grades with ratings of teaching effectiveness is positive and significant at 0.05 alpha level (B = 0.46, p ≤ 0.00). It was, therefore, recommended that the ministry of education and school administrators adopt the use of this scientific model to predict students’ final grades, for regulating the supervision of teaching and learning process for optimization of students’ academic achievement.