With the increased popularity of electronic textbooks, there is a growing interest in developing a new generation of "intelligent textbooks," which have the ability to guide readers according to their learning goals and current knowledge. Intelligent textbooks extend regular textbooks by integrating machine-manipulable knowledge, and the…

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are…

This paper proposes a computer-aided teaching model using knowledge graph construction and learning path recommendation. It first creates a multimodal knowledge graph to illustrate complex relationships among knowledge. Learning elements and sequences are then used to form time sequences stored as directed graphs, supporting flexible path…

Educational systems use models of student skill to inform decision-making processes. Defining such models manually is challenging due to the large number of relevant factors. We propose learning multidimensional representations (embeddings) from student activity data -- these are fixed-length real vectors with three desirable characteristics:…

The representation of knowledge is a process widely used in education for its potential to generate deep learning, metacognition, and also in mapping the student's cognitive structure while developing a broad spectrum of thinking skills. Notwithstanding the above mentioned benefits, the development and evolution of new digital ecologies of…

In this paper, we demonstrate how machine learning could be used to quickly assess a student's multimodal representational thinking. Multimodal representational thinking is the complex construct that encodes how students form conceptual, perceptual, graphical, or mathematical symbols in their mind. The augmented reality (AR) technology is adopted…

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…

Artificially intelligent tools have given us the capability to use technology to address ever more complex challenges. What are the capabilities, challenges, and hazards of incorporating and developing this technology for augmentative and alternative communication (AAC)? "Artificial intelligence" (AI) can be defined as the capability 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…

Several approaches to implementing symbol-like representations in neurally plausible models have been proposed. These approaches include binding through synchrony (Shastri & Ajjanagadde, 1993), "mesh" binding (van der Velde & de Kamps, 2006), and conjunctive binding (Smolensky, 1990). Recent theoretical work has suggested that…

This article by David Aldridge concerns the promise of knowledge "insertion." The promise can be elucidated as follows: knowledge could be inserted by a less time-consuming (and possibly in many senses less expensive) technological process than traditional learning, whereby, for example, some relatively swift procedure of implanting or…

One of the attributes necessary for Watson to be considered human is that it must be conscious. From Rachlin's (2012) point of view, that of teleological behaviorism, consciousness refers to the organization of behavioral complexity in which overt behavior is distributed widely over time. Consciousness is something that humans do, or achieve, in…

Rachlin (2012) makes two general assertions: (a) "To be human is to behave as humans behave, and to function in society as humans function," and (b) "essential human attributes such as consciousness, the ability to love, to feel pain, to sense, to perceive, and to imagine may all be possessed by a computer'. Although Rachlin's article is an…

The concept of learning objects has been applied in the e-learning field to promote the accessibility, reusability, and interoperability of learning content. Learning Object Metadata (LOM) was developed to achieve these goals by describing learning objects in order to provide meaningful metadata. Unfortunately, the conventional LOM lacks the…