Elearning: Implications of Training Theory & Research

Many organizations both in the military and in private industry are using distributed learning (i.e., structured learning that takes place without the physical presence of an instructor) to train personnel. While distributed learning methods vary (e.g., computer based, video tele-training, correspondence courses), this paper will focus on "E-learning" (i.e., electronic courses delivered via CD-ROM or the internet). E-learning offers many potential benefits including the ability to train large numbers of people at the same time and reduced travel costs.

While some E-learning implementation success has been achieved, many challenges remain. For example, one concern is the student drop-out rate (Carr, 2000). Identifying the reasons for the dropout rate and developing methods to improve course completion is not easy. Fortunately, the science of learning literature may help. Recently, Colquitt, LePine, and Noe (2000) performed a meta-analysis of 20 years of training research and developed a model of training motivation. The model has a number of implications for the design and implementation of E-learning programs. This includes the influence of characteristics of the individual learners and the organization in which the learner works on how much is actually learned during training.

This paper examines E-learning in light of the Colquitt et al. (2000) model. The paper discusses the influence of self-efficacy, valence, job/career variables, situational variables, personality, and motivation to learn on learning outcomes and the implications for E-learning. Because the model is based on research on traditional classroom settings, however, some relationships between variables in the model may change in a E-learning environment. Thus, we will also discuss the implications of E-learning for the model and suggest directions for research.