Autotutor: An intelligent tutoring system and its authoring tools
Abstract
In the domain of learning science, deep learning is an approach to study that relates old to new knowledge, knowledge from different sources, theory to application, and evidence to argument. Deep learning is a complicated process involving question asking, question answering, deep explanation, and skillful application to difficult problems. Unfortunately, this process is rarely observed in self-regulated learning or in classroom environments. Computer-based learning environments, such as AutoTutor, can help make this happen. AutoTutor often presents a difficult problem to a learner and helps the learner learn by holding a conversation that guides the learner to construct a solution to the problem and relate different knowledge components. AutoTutor conversation has been integrated into different types of learning systems, including html page-based systems with rich media (pictures, movies, simulations, etc.), desktop applications, and even virtual environments. AutoTutor authoring tools make it easy for researchers and teachers to add engaging AutoTutor conversations to their own learning environments. In this chapter, we present the ideas in AutoTutor, show how AutoTutor works, and describe the AutoTutor authoring process and tools.
Publication Title
Deep Comprehension: Multi-Disciplinary Approaches to Understanding, Enhancing, and Measuring Comprehension
Recommended Citation
Cai, Z., & Hu, X. (2018). Autotutor: An intelligent tutoring system and its authoring tools. Deep Comprehension: Multi-Disciplinary Approaches to Understanding, Enhancing, and Measuring Comprehension, 140-153. https://doi.org/10.4324/9781315109503
