Online technologies self-efficacy, self-directed learning readiness, and locus of control of learners in a graduate-level web-based distance education program

The purpose of this study was to describe the strength and direction of the relationship between online technologies self-efficacy, self-directed learning readiness, internal locus of control, and student success as measured by academic performance and student satisfaction.; A correlational research design was utilized to study the relationships between the three predictor variables and two criterion variables to test the hypotheses that, within a single group, these variables were statistically significantly related to one another. The participants in this study were drawn from a convenience sample of 191 graduate-level students enrolled in an online Master of Education in Educational Technology (M.Ed.) degree program at The University of Texas at Brownsville and Texas Southmost College from January 2003 to May 2003. Ninety-eight students from the convenience sample volunteered to participate in this study by responding to the surveys. These students comprised the study sample.; Data for the participants' online technologies self-efficacy, self-directed learning readiness, and locus of control orientation were elicited though three self-report instruments. In addition, the participants were asked to fill out a demographic questionnaire and a student satisfaction survey. The data were analyzed using the following analyses: (1) bivariate analyses using the Pearson product-moment correlation technique to determine the strength and direction of the relationship between each of the three predictor variables and the two criterion variables; and (2) multivariate analysis using multiple linear regression to determine the strength of the relationship between the combination of predictor variables and the criterion variables.; To test the first research hypothesis, a Pearson product-moment correlation technique was used to estimate the relationship between the three predictor variables and student satisfaction. It yielded: a correlation coefficient of r = +.63 for online technologies self-efficacy that was statistically significant (p < .001); a correlation coefficient of r = +.37 for self-directed learning readiness that was statistically significant (p < .001); and a correlation coefficient of r = −.54 for locus of control that was statistically significant (p < .001). The multivariate analysis using multiple linear regression yielded a multiple correlation coefficient (R = .70), a coefficient of determination (R 2 = .49), and an F ratio of 30.49, which was statistically significant (p < .001) for the predictor variables in combination. Inasmuch as 49 percent of the variance of the criterion variable was accounted for by the combination of predictor variables, this is viewed as a moderate to strong relationship.; To test the second research hypothesis, a Pearson product-moment correlation technique was used to estimate the relationship between the three predictor variables and academic performance. It yielded: a correlation coefficient of r = +.51 for online technologies self-efficacy which was statistically significant (p < .001); a correlation coefficient of r = +.52 for self directed learning readiness that was statistically significant (p < .001); and a correlation coefficient of r = −.69 for locus of control that was statistically significant (p < .001). The multivariate analysis using multiple linear regression yielded a multiple correlation coefficient (R = .74), a coefficient of determination (R 2 = .55), and an F ratio of 38.68, which was statistically significant (p < .001) for the predictor variables in combination...