## 1 Introduction  
From 2016 to now, the Ministry of Education (MOE) of Taiwan conducted a digital application promotion plan in rural schools to improve digital skills, enrich digital competency (e-commerce and e-marketing), and promote enjoyment of mobile services as well as applications. The MOE e-learning partner program was one part of the plan [1]. Based on companionship, learning, and improving the motivation and interest of rural students, undergraduates used the internet to overcome barriers between urban and rural areas. The purpose was to promote equal learning opportunities for elementary and secondary students everywhere. In addition, the core values of this program included life accompanying life and living teaching living. There are two main targets: one is the learning of the children and the other is the teaching of the undergraduates. There was a total of ten weeks in one semester, with classes twice a week and two lessons each time (Chinese, English, or Mathematics). Each lesson lasted for 45 min with one-on-one online interaction. Regarding the partners, there were five primary and secondary schools that cooperated with the case university from 2017 until now. Many studies reported good performance of the e-learning partner program [2; 3; 4; 5]. In the case university, the e-learning partner program has been promoted for four semesters. However, the outcome report of this program stated that the retention rate of the undergraduates was below 30% over three semesters [6]. At the beginning of each new semester, the program hosts had to invite lecturers to announce and impart the same knowledge and skills as those of the e-leaning partner program. The problem, as per program hosts, was considered an economic loss for the universities and talent loss for the team members of the program. This present study aims to collect specific data of the undergraduates' inner characteristics and the outer environmental support to examine the significant factors that influence the persistence of the program. A sound and complete model can predict the user performance with technology by the analysis of personal learning behavior [7]. We use an advanced procedure to set up the predictive model of undergraduates' self-evaluation in an online e-learning partner program to improve the high talent turnover problem and decrease the cost of human-resource training. The evaluation of self-efficacy will directly affect a person's motivation for the job. [PERSON] et al. concluded that teacher self-efficacy, academic self-efficacy, and computer self-efficacy are important predictors of prospective teachers' attitudes toward applying computer-supported education [8]. Also, personalization features can match the user's attitude and behavior; therefore, they could enhance the user's performance and persistency with technology [9]. Some studies reported that there was a positive relationship between self-efficacy and positive attitude and predicted the attitude [10; 11; 12]. The variables of teaching efficacy and teaching satisfaction were also discussed [13; 14]. In order to explore the results of the undergraduates' retention during one semester in the case university, collecting data on teaching, counseling, administration, and equipment evaluation was necessary. Furthermore, the retention factor and designing of a questionnaire and its implementation during the mid-term and the end of the semester were important. For this reason, it is essential to detect which variables affect prospective undergraduates' attitudes toward applying for the e-learning partner program and to devise a predictive model in this program. In the e-learning partner program, there were 94 teaching undergraduates who completed the survey at the case university. When using a small sample, the partial least squares structural equation modeling (PLS-SEM) can be used to estimate the relationships between latent variables with several indicators [15; 16].