Schools and districts are awash in data, from more traditional data sources such as test scores, grades, attendance, discipline reports and surveys, to more recent innovations such as intelligent tutoring computer systems, computer interaction logfile data, and multimodal instrumented instructional spaces.
Anderson has also made fundamental contributions in applying cognitive architectures to practical problems, most notably in the development of intelligent tutoring systems: computer-based tutors that continually infer the cognitive state of the student, striving to determine what the student knows and does not know, and targeting further instruction accordingly.
Known as Intelligent Tutor Systems, computer software is able track the "mental steps" of the learner during problem-solving tasks to diagnose misconceptions and estimate the learner's understanding of the domain.
Intelligent tutoring systems (ITSs) are computer learning environments designed to help students master difficult knowledge and skills by implementing powerful intelligent algorithms that adapt to the learner at a fine-grained level and that instantiate complex principles of learning (Graesser et al. in press).
The research field of Intelligent Tutoring Systems/Artificial Intelligence in Education has long addressed learning from examples.
New Perspectives on Affect and Learning Technologies deserves a wide audience among researchers in learning technologies, affective computing, human/computer interaction, artificial intelligence in education, and intelligent tutoring systems, as well as the greater educational research and cognitive science communities.
An Artificial Intelligence approach was used to develop the computer environment, resulting in an Intelligent Tutoring System, the STCEQ.
The remainder of the article is organized as follows: Section "Related work" briefly discusses previous relevant work while Section "DeepTutor: a state-of-the-art dialogue-based intelligent tutoring system" presents a brief overview of the computer tutor that provided the context for our experimental analysis.
He has done research in Software Engineering, Artificial Intelligence, Programming Languages, Cognitive Psychology, and Intelligent Tutoring.
Person and Graesser (2002) developed an intelligent tutoring system that improves students' knowledge in the areas of computer literacy and Newtonian physics using an animated agent.
Data on heuristics and biases was collected using a computer-based system, modified from SlideTutor, an intelligent tutoring system used to teach diagnostic surgical pathology (Crowley and Medvedeva 2006).
