Knowledge tracing is the task of modeling each student's mastery of knowledge concepts (KCs) as (s)he engages with a sequence of learning activities. Each student's knowledge is modeled by estimating the performance of the student on the learning activities. It is an important research area for providing a personalized learning platform to…

Adult learners with low literacy skills compose a highly heterogeneous population in terms of demographic variables, educational backgrounds, knowledge and skills in reading, self-efficacy, motivation etc. They also face various difficulties in consistently attending offline literacy programs, such as unstable worktime, transportation…

Automatic answer assessment systems typically apply semantic similarity methods where student responses are compared with some reference answers in order to access their correctness. But student responses in dialogue based tutoring systems are often grammatically and semantically incomplete and additional information (e.g., dialogue history) is…

Intelligent tutoring systems (ITS), like human tutors, try to adapt to student's knowledge level so that the instruction is tailored to their needs. One aspect of this adaptation relies on the ability to have an understanding of the student's initial knowledge so as to build on it, avoiding teaching what the student already knows and focusing on…

Learning curves have proven to be a useful tool for understanding how a student learns a given skill as they progress through a curriculum. A learning curve for a given Knowledge Component (KC) is a plot of some measure of competence as a function of the number of opportunities the student has had to apply that KC. Consider the case where each…

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,…

Stavros Demetriadis is currently an Assistant Professor with the Department of Informatics, Aristotle University of Thessaloniki (AUTh) in Greece. He also earned his Bachelor's degree in Physics and a Master Diploma in Electronic Physics from AUTh. He became interested in information and communications technologies when he was a high school…

The popularity of intelligent tutoring systems (ITSs) is increasing rapidly. In order to make learning environments more efficient, researchers have been exploring the possibility of an automatic adaptation of the learning environment to the learner or the context. One of the possible adaptation techniques is adaptive item sequencing by matching…

This paper describes the role of simulation-based training in the military. Interviews and observations of military instructors in the damage control and shiphandling domains provide examples of how the instructors extend the student's training beyond the well-defined simulated world with qualitative reasoning about context, hypothetical variants,…

A typical tutorial system functions by means of interaction between four components: the expert knowledge base component, the inference engine component, the learner's knowledge component and the user interface component. In typical tutorial systems the interaction and the sequence of presentation as well as the mode of evaluation are…

Taking advantage of the continuously improving, web-based learning systems plays an important role for self-learning, especially in the case of working people. Nevertheless, learning systems do not generally adapt to learners' profiles. Learners have to spend a lot of time before reaching the learning goal that is compatible with their knowledge…

Purpose: One of the greatest challenges facing any intelligent tutoring system is being able to adapt its behaviour based on the student's current knowledge level, ability, needs and wishes within a course. This paper aims to present a framework of BDI agents within an agent-based intelligent tutoring system (ABITS). Design/methodology/approach: A…

Olae is a computer system for assessing student knowledge of physics, and Newtonian mechanics in particular, using performance data collected while students solve complex problems. Although originally designed as a stand-alone system, it has also been used as part of the Andes intelligent tutoring system. Like many other performance assessment…

This article presents a framework for the cognitive diagnosis of learners' errors in an interactive learning activity occurring in an intelligent learning environment. The proposed framework supports the implementation of an authoring tool. This tool helps instructional designers to specify the features of a component for cognitive diagnosis. Two…