قبول عوامل آموزش الکترونیکی موثر بر اثربخشی آموزش

The development of information technologies has contributed to the growth in online training as an important education method. E-learning provides trainees with education opportunities in diverse ways. It has led to a range of innovative services offering one-stop educational solutions within the e-business sector. The online training environment enables trainees to undertake customized training at any time and any place. Moreover, information technology allows both the trainers and trainees to be decoupled in terms of time, place, and space. The purposes of this research are twofold: (1) To discover the determinants of effective online training and; (2) To reveal how those variables affect learning performance and transfer performance, two important aspects of training effectiveness in the workplace. This paper demonstrates, through empirical data, a positive relationship between individual, organizational and online training design constructs and training effectiveness constructs (learning and transfer performance).

Today, organizations are making great efforts to properly adjust to the changing business environment to enhance their competitiveness. In step with the development of information technology and the Internet, many businesses are replacing traditional vocational training with e-learning to better manage their workforce. However, it is questionable whether training programs actually change employee behavior after implementation. In the case of US companies, only 10–15% of training is applied to work (Sevilla & Wells, 1988). As off-line learning concepts have been evolved into e-learning concepts along with the development of information and communication technology, e-learning have become an important field of study and a number of research papers have reported on this. (1) Recently, many MIS researchers have published e-learning studies in IT or MIS journals (Ijab & Anwar, 2004; Neville, Heavin, & Walsh, 2005; Ong, Lai, & Wang, 2004; Piccoli, Ahmad, & Ives, 2001; Wild, Griggs, & Downing, 2002; Zhang & Zhou, 2003). Specifically, study on e-learning effectiveness becomes one of popular themes and many studies are found since 2004 (Cappel & Hayen, 2004; Dougla & Van Der Vyver, 2004; Zhang, Zhou, Briggs, & Nunamaker, 2006). Under the e-learning context, these studies focus on the specific variables that have been developed through the past e-learning research trend. Our study differentiates from existing literatures by including variables found to be important in off-line training program and other conditional variables as well as e-learning specific variables. (2) For the theoretical background, our study refers to previous studies on the connection between learning and technologies (Chau & Wang, 2000; Parikh & Verma, 2002) and distance learning as a form of e-learning (Kodama, 2001; Theakston, 1999) published in International Journal of Information Management. This study seeks to demonstrate the factors of a training system that enhance efficacy of corporate e-training. By reviewing design factors that affect traditional offline training, and defining factors affecting online training, we seek to identify their effects on learning performance and transfer performance.

The purpose of this paper is to explore online training program design factors to improve learning performance and transfer performance. To do this, we constructed hypotheses based on a literature review and then tested the hypotheses by surveying subjects from a large group of trainees, who had participated in task-related online training. The research results are as follows. First, the higher online learning trainees’ learning motivation, the better learning performance and transfer performance based on the analysis. Specifically, trainees’ learning motivation has the largest magnitude among endogenous constructs. That is, trainees’ motivation is a relatively important variable in learning performance (learning motivation→learning performance: γ11=0.5098γ11=0.5098, and transfer performance (learning motivation→transfer performance: γ12=0.4279γ12=0.4279). This result means that, like traditional offline education, trainees’ volition of education is the most important factor in online educational training. Second, the higher the trainees’ computer self-efficacy, the higher the learning performance. This result is in accordance with Compeau and Higgins (1995) study. In order to undertake online learning, some computer proficiency is needed. Thus, attitude and self-efficacy toward computers seem to positively affect online learning success. However, in this study, trainees’ computer self-efficacy is not statistically significant with transfer performance. This result means that the transfer performance is channeled through learning performance, thus demonstrating the mediating role of learning performance with online learning, which is consistent with Lee, Choi, and Lee (2004). Third, task-related content increases transfer performance as Alliger et al. (1997) insisted, and this study has shown. Moreover, task-related content directly affects trainees’ learning performance. The ultimate goal of introducing a training program is to increase task-ability with advanced trainees’ knowledge, technology, and attitude. Fourth, when an online site is designed, face-to-face meetings between trainer and trainees, and the site's ease of use should be considered important factors. There is no reason to exclude face-to-face meetings between trainers and trainees even in an online learning situation. Powley (1994) claim that offline regular meetings and telephone feedback increase learning performance. This study supports their findings. However, unlike Liedner and Jarvenpaa's research (1995), this research does not attest to the effect of communication through email on learning performance. Hence, we suggest additional study about email communication is needed. Fifth, the idea regarding organization environment for effectiveness is partially supported. Interestingly, unlike other constructs, support from supervisors and a consistent learning environment do not affect learning performance, but rather they influence transfer performance. These results differ from Baldwin and Ford (1988) in that supervisors’ support directly affects trainees’ learning performance. In this study, we defined supervisor support as the degree of support in helping trainees’ learn to apply the current task. We may infer that supervisor support directly relates to transfer performance. By contrast, maintaining a consistent learning environment is not significant with transfer performance, but rather with learning performance. That is, when the organization environment emphasizes innovation, and the organization rewards trainees’ self-development efforts, trainees learning performance will be higher. Finally, from the perspective of online and traditional education, the traditional education factor is still important in online education. Trainees’ motivation, face-to-face meetings and training contents directly affect learning performance. Specifically, motivation directly affects transfer performance, even though face-to-face meetings and training contents indirectly influence transfer performance. Ultimately, this study shows that effective virtual education or e-education needs ease of interaction, computer self-efficacy, and efficient communication in the virtual perspective as well as institutional factors such as support of seniors and continuous learning culture.