Although cognitive load (CL) and self-regulated learning (SRL) have been widely recognized as two determinant factors of students' performance, the integration of these two factors is still in its infancy. To further specify why and how CL links with SRL, we first conducted an overview to describe the multiple dimensions of cognitive load (i.e.,…

The purpose of intelligent tutoring systems is to provide students with personalized instruction and feedback. The focus of these systems typically rests in the adaptability of the feedback provided to students, which relies on automated assessments of performance in the system. A large focus of my previous work has been to determine how natural…

Instruction can be made relevant to students when it draws upon and utilizes their interests, experiences, and "funds of knowledge" in productive ways to support classroom learning. This approach has been referred to as "context personalization." In this paper, we discuss the cognitive basis of personalization interventions,…

Recognising students' emotion, affect or cognition is a relatively young field and still a challenging task in the area of intelligent tutoring systems. There are several ways to use the output of these recognition tasks within the system. The approach most often mentioned in the literature is using it for giving feedback to the students. The…

"Reciprocal tutoring," as reported in "Exploring the design of computer supports for reciprocal tutoring" (Chan and Chou 1997), has extended the meaning and scope of "intelligent tutoring" originally implemented in stand alone computers. This research is a follow-up to our studies on a "learning companion…

In their influential "Psychological Review" article, Bogacz, Brown, Moehlis, Holmes, and Cohen (2006) discussed optimal decision making as accomplished by the drift diffusion model (DDM). The authors showed that neural inhibition models, such as the leaky competing accumulator model (LCA) and the feedforward inhibition model (FFI), can mimic the…

Between 2002 and 2014, the Institute of Education Sciences (Institute) supported over 400 projects focused on education technology through the National Center for Education Research (NCER) and the National Center for Special Education Research (NCSER). The majority of this work has been funded through Education Technology research topics of NCER…

Operation ARA (Acquiring Research Acumen) is a computerized learning game that teaches critical thinking and scientific reasoning. It is a valuable learning tool that utilizes principles from the science of learning and serious computer games. Students learn the skills of scientific reasoning by engaging in interactive dialogs with avatars. They…

Cognitive approaches have been used for student modeling in intelligent tutoring systems (ITSs). Many of those systems have tackled fundamental subjects such as mathematics, physics, and computer programming. The change of the student's cognitive behavior over time, however, has not been considered and modeled systematically. Furthermore, the…

The interoperability of educational systems, encouraged by the development of specifications, standards and tools related to the Semantic Web is limited to the exchange of information in domain and student models. High system interoperability requires that a common framework be defined that represents the functional essence of educational systems.…

An educational assessment embodies an argument from a handful of observations of what students say, do or make in a handful of particular circumstances, to what they know or can do in what kinds of situations more broadly. This article discusses ways in which research into the nature and development of expertise can help assessment designers…

Explains the relationship between computers and multiple intelligences and explores its potential. Topics include behaviorism and cognitivism; constructivism; multiple representations in the human mind, including various forms of intelligence; individual differences; the challenge of altering early representations; and machine versus human tutors.…

Focuses on student modeling within an Intelligent Tutoring System. Describes three domain-independent properties that the formalism representing student knowledge and the processes synthesizing this knowledge must possess to build accurate student models for second-language learning. Notes when, how, and where hypothetical reasoning mechanisms…

Reviews psychometric approaches to problems of modeling student achievement (the student model) within intelligent tutoring systems (ITS). A number of cognitively oriented psychometric approaches, including latent-trait models, statistical pattern recognition methods, and causal probabilistic networks are described and discussed within the current…

Describes the Cognitive Learning from Automated Instruction (CLAI) model. Discusses cognitive learning, learning from instruction, and automatic instruction; reviews instructional theories relating cognitive processes and instruction; and describes the CLAI model for developing intelligent tutoring systems (ITS). Illustrates a practical approach…