Locus of control and self-efficacy as predictors of academic achievement among form three students in Nyamaiya division, Nyamira county, Kenya.

Abstract

A study will be conducted to determine whether academic performance could be predicted on the bases of the constructs; locus of control and academic selfefficacy. Five objectives will guide the study: to establish relationship between student's academic achievement and locus of control and academic self-efficacy, establish gender differences in locus of control and academic self-efficacy and determine the interaction effect of locus of control and academic self-efficacy in predicting student academic achievement. Two theories will guide this study: attribution theory and social cognitive theory (self-efficacy theory). The study will adopt a correlation research design and both descriptive and inferential statistics will be employed to analyze the data. The findings of this study may enable teachers and parents to assist students develop a positive self believe that they can achieve academic success. Three schools will be sampled using stratified random sampling. The school sample will have a total of 3 schools i.e. 1 boy school, 1 girl school and 1 mixed school. Using simple random sampling, 150 students will be sampled from the three schools from Nyamaiya Division, Nyamira County, Kenya. Two research instruments-an Academic Self-Efficacy Scale (ASES) and a modified Crandall's Intellectual Achievement Responsibility (IAR) questionnaire will be used in data collection. IARQ will be used to measure participants' locus of control and the ASES to measure self-efficacy. Scores on academic performance will be obtained through document analysis by computing mean scores from three consecutive end-of-term examinations results English, Kiswahili and Mathematics. The relationship between two independent variables (self-efficacy and locus of control) and dependent variable (academic achievement) will be tested using Pearson Product Moment Correlation coefficient. However, relationship among the three variables will be determined using the multiple regression and F- test analysis at 0.05 alpha levels. The results of the data analysis were presented in frequency tables.