PRELIMINARY DEVELOPMENT OF LEARNER SUPPORT PREDICTION MODEL FOR E-LEARNING BASED ON SELF-REGULATED LEARNING FACTORS

The purpose of this research is to develop learner support prediction model for e-learning courses based on self-regulated learning (SRL) factors. The model aims to predict learners' needs and typical behaviour to determine learner types at the forethought phase of Zimmerman's three-phase model (1998) to help them complete e-learning courses. This report consists of two main parts: (1) exploration of factors of SRL for e-Learning and (2) development of preliminary model of the Factors on e-learning course completion. The standardized questionnaire for SRL skills developed by Wolter, Pintrich, & Karabenic (2003) were modified and shorten based on the pilot study results with exploratory and confirmatory factor analysis. The final inventory consists of 40 questions with high reliability (Overall Chronbach alpha = .931). 857 college students' data were analyzed and there found four SRL factors including (1) affective, (2) cognitive, (3) help-seek, and (4) self-directed factors. Then, a preliminary model to determine learner types at the forethought phase of Zimmerman's three-phase model (1998) students e-learning classes without any face-to-face instruction. In order to develop a preliminary learner support model with the four SRL factors to predict learners' e-learning course completion, 224 students' data were examined with path analysis. The model showed an excellent fit (chi(2)((4)) = 2.725, p=.605, RMSEA=.000, GFI=.995, AGFI=.982). The significance of this research is to provide information on learners' needs priori to a semester, which helps instructors and mentors to plan learner support and estimate necessary efforts to help students complete a course.