In intelligent e-learning systems that adapt a learning and teaching process to student knowledge, it is important to adapt the system as quickly as possible. However, adaptation is not possible until the student model is initialized. In this paper, a new approach to student model initialization using domain knowledge representative subset is…

Adaptive learning has become a dominant theme in settings ranging from academic laboratories to commercial education. Despite tens of millions of dollars invested by governments, universities, the private sector and companies, however, progress has been both costly and limited. No established initiative has attempted to model the processes human…

Learning analytics research has used both knowledge engineering and machine learning methods to model student behaviors within the context of digital learning environments. In this paper, we compare these two approaches, as well as a hybrid approach combining the two types of methods. We illustrate the strengths of each approach in the context of…

This paper summarizes key stages in development of the Structural Learning Theory (SLT) and explains how and why it is now possible to model human tutors in a highly efficient manner. The paper focuses on evolution of the SLT, a deterministic theory of teaching and learning, on which AuthorIT authoring and TutorIT delivery systems have been built.…

AuthorIT and TutorIT represent a fundamentally different approach to building and delivering adaptive learning systems. Intelligent Tutoring Systems (ITS) guide students as they solve problems. BIG DATA systems make pedagogical decisions based on average student performance. Decision making in AuthorIT and TutorIT is designed to model the human…

Knowledge components (KCs) define the underlying skill model of intelligent educational software, and they are critical to understanding and improving the efficacy of learning technology. In this research, we show how learning curve analysis is used to fit a KC model--one that was created after use of the learning technology--which can then be…

Cyberlearning presents numerous challenges such as the lack of personal and assessment-driven learning, how students are often puzzled by the lack of instructor guidance and feedback, the huge volume of diverse learning materials, and the inability to zoom in from the general concepts to the more specific ones, or vice versa. Intelligent tutoring…

Although providing open learner models to teachers and learners has proven effective, building accurate learner models remains a very complex task, partly due to the large amount of data that must be analyzed. We propose a method for specifying an open learner model at the conceptual level. This model re-uses constraints or indicators already…

Model-tracing tutors (MTTs) have proven effective for the tutoring of well-defined tasks, but the pedagogical interventions they produce are limited and usually require the inclusion of pedagogical content, such as text message templates, in the model of the task. The capability to generate pedagogical content would be beneficial to MTT…

The increasing use of educational technologies in classrooms is producing vast amounts of process data that capture rich information about learning as it unfolds. The field of educational data mining has made great progress in using log data to build models that improve instruction and advance the science of learning. Thus far, however, the…

Intelligent Tutoring Systems (ITS) have a significant educational impact on student's learning. However, researchers report time intensive interaction is needed between ITS developers and domain-experts to gather and represent domain knowledge. The challenge is augmented when the target domain is ill-defined. The primary problem resides in…

This paper describes educational systems built by members of the Human-Centred Technology Research Group at the University of Sussex that address different aspects of motivation. These systems have been described elsewhere, so this paper is essentially a drawing together of existing work. In particular, we have recently set out a view of…

The object of this study is to model the level of a question difficulty by a differential equation at a pre-specified domain knowledge, to be used in an educational support system. For this purpose, we have developed an intelligent tutoring system for mathematics education. Intelligent Tutoring Systems are computer systems designed for improvement…

Intelligent Tutoring Systems (ITS) are effective tools for education. However, developing them is a labour-intensive and time-consuming process. A major share of the effort is devoted to acquiring the domain knowledge that underlies the system's intelligence. The goal of this research is to reduce this knowledge acquisition bottleneck and better…

More and more things that humans used to do can be automated on computer. In each case, complex tasks have been automated -- not to the extent that they can be done as well as humans, but better. I will draw and develop parallels to education -- showing how and why advances in the Structural Learning Theory (SLT) and the AuthorIT development and…