Designing Empathetic Animated Agents for a B-Learning Training Environment within the Electrical Domain

Introduction Performing electrical tests involves dangerous activities. Therefore, efficient training is needed in order to minimize training time, costs, and equipment damage, and most importantly, to prevent accidents that could injure electricians. However, training on electrical tests faces some problematic situations, such as limited opportunity to practice in an actual substation, since substations are operating on a regular basis. We have developed a Virtual Reality System (VRS) to support traditional training. Trainees still attend classroom courses but they complement their learning and practice aided by the VRS. The system is used at the Mexican electricity utility by a number of electricians. However, the VRS is not adaptive to trainees' knowledge and emotional states. Training still depends on a courses schedule, which most of the times, means waiting for a training course for a long time. Based on this VRS that supports traditional training, we composed a blended learning model. Blended learning is a new strand in education, although the concept itself has already existed for a long time. It can take many forms and there are several definitions that include the same elements roughly. In a formal education context, blended learning is a formal educational program in which a student learns, at least in part through online delivery of content and instruction with some elements of student control over time, place, path, or pace, and at least in part at a supervised brick-and-mortar location away from home (Staker & Horn, 2012). A more general and perhaps more accepted definition states that blended learning is learning that is facilitated by the effective combination of different delivery modes, teaching models and learning styles, and founded on transparent communication amongst all parties involved in a course (Heinze & Procter, 2004). In addition to blended learning, the characteristics of electrical tests demand faster and more efficient training, where instruction is adaptive and responds to needs of the trainees. For that reason, we have defined a roadmap to achieve efficient and tailored training. The roadmap starts with traditional training and ends with intelligent and adaptive training. In order to have more adaptive training, we have built a trainee model. This model represents the affective and knowledge states of trainees and allows the training system to adapt the instruction to a particular trainee. Our proposal for the affective state is based on facial expressions and contextual information. We propose to present the instruction by an animated agent representing the instructor. We are designing an empathetic agent to try to engage the trainee, promote a positive emotional state and improve learning. A key highlight of the agent's design is that it is presented as an electrician so that trainees can feel identified with him. With all these elements, we are developing a model and a platform for blended training, which adapts itself to needs of the trainee in an intelligent way based on the roadmap for training. In this paper we present the outcomes of a study that we conducted on animated agents in order to refine our empathetic agent before full integration to the VRS. Experts in electrical tests who know the VRS participated in the study. We gathered useful information to improve the design of the agent, which includes ingredients such as appearance, behavior, and facial expressions. The rest of the paper is organized as follows: the next section presents some related work. Then, we present the roadmap for training, describing the virtual reality system and the elements of the blended training model, particularly, the affective student model and the empathetic agent. After that, we present the evaluation of the empathetic agent. Then, results are analysed. Finally, we present some conclusions, as well as a description of future work. …