Search for Causal Predictors of Distance Education Achievement Using Path Analysis
Dr. Maria Ana T. Quimbo
SEAMEO-UNESCO Education Congress held on 27-29 May 2004 at Bangkok , Thailand
*Abstract only
The study was conducted to find out how factors that comprise distance learning system explain achievement of distance learners. It was aimed to develop a predictive model of achievement in distance education. To address this objective, a path analysis of pertinent variables in a causal model of DE achievement was determined.
The research participants were students enrolled in the teacher education programs of a state-owned Distance Learning Institution. Two types of research instruments were developed and used in the study. These were the Evaluation Questionnaire for Distance Education (EQDE) and the Distance Education Achievement Test for Teachers (DEATT). Both EQDE and DEATT were subjected to validity and reliability procedures to ensure their merit and worth as measuring instruments.
Specifically, the EQDE was used to collect respondents' perceptions on the dimensions of distance education. Scores of students in an achievement test, using DEATT, were used as the first measure of achievement of distance learners. Student's GWA was also considered as another measure of achievement in the causal model.
In the causal model, nine dimensions of distance learning system are the independent, exogenous variables, a chievement test score is the endogenous variable and used in the causal model both as a dependent and an independent variable in different regression functions, and GWA is the endogenous dependent variable.
Results of path analysis showed that of the nine dimensions of distance education, social & work integration , learner-material interaction , workload requirement, and tutor support were significant predictors of achievement test score . On the other hand, metacognition, social & work integration, teaching effectiveness, learner-material interaction, workload requirement, learner-learner interaction, and test score were significant predictors of GWA .
