ABSTRACT

This chapter considers the design and development of a "Generalized Intelligent Framework for Tutoring" (GIFT). The methodology used to develop GIFT considered major design goals and anticipated uses, including the goal to enhance the efficiency and effectiveness of one-to-one and one-to-many training experiences beyond the state of practice for computer-based tutoring systems (CBTS). The trainee module uses preprocessed behavioral and physiological data from the sensor module, and a performance assessment along with demographic, self-reported and observed data to classify the trainee's cognitive, affective and competency states. The chapter discusses technology-based approach that provides an emerging capability to support self-regulated learning in a manner which is unobtrusive and yet tailored to the needs of individuals and small teams. It reviews the design methodology and salient capabilities of a CBTS architecture called GIFT, whose goal is to enable necessary research and development leading to standardized, adaptive tutoring systems which are accessible, flexible, affordable and easy to develop and use.