Affective teachable agent in virtual learning environment
Date of Issue2014
School of Computer Engineering
Emerging Research Lab
Teachable Agent (TA) is a special type of pedagogical agent which instantiates the educational theory of “Learning-by-Teaching”. Soon after its emergence, research of TA becomes an active field, as it can solve the over-scaffolded problem in traditional pedagogical systems, and encourage students to take the responsibility of learning. Apart from the benefits, existing TA design also has limitations. One is the lack of enough proactive interactions with students during the learning process, and the other is the lack of believability to arouse student’s empathy so as to offer students an immersive learning experience. To solve these two problems, we propose a new type of TA – Affective Teachable Agent, and use a goal-oriented approach to design and implement the agent system allowing agents to proactively interact with students with affective expressions. The ATA model begins with the analysis of pedagogical requirements and teaching goals, using Learning-by-Teaching theory to design interventions which can authentically promote the learning behaviors of students. Two crucial capabilities of ATA are highlighted –Teachability, to learn new knowledge and apply the knowledge to certain tasks, and Affectivability, to establish good relationship with students and encourage them to teach well. Through executing a hierarchy of goals, the proposed TA can interact with students by pursuing its own agenda. When a student teaches the agent, the agent is performed as a “naive” learning companion, and when an educator teaches the agent during the design and maintenance time, the agent can perform as an authoring tool. To facilitate the involvement of educators into the game design, we develop an authoring tool for proposed ATA system, which can encapsulate the technical details and provide educational experts a natural way to convey domain knowledge to agent’s knowledge base. An agent-augmented educational project, Virtual Singapura, is developed as a show case to illustrate how the ATA model is implemented in a real educational system. Formative and summative assessment results are provided to show that ATA can assist students to reflect on their learning process, and consequently improved student’s learning experience and encourage them to take the learning responsibility.
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence