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…

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…

Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…

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…

A considerable amount of research has been undertaken to provide insights into the valid assessment of team performance. However, in many settings, manual and therefore labor-intensive assessment instruments for team performance have limitations. Therefore, automated assessment instruments enable more flexible and detailed insights into the…

University education often suffers from a lack of an explicit and adaptable didactic design. Students complain about the insufficient adaptability to the learners' needs. Learning content and services need to reach their audience according to their different prerequisites, needs, and different learning styles and conditions. A way to overcome such…

This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…

This chapter states and explains that a Learning Design is the result of a knowledge engineering process where knowledge and competencies, learning design and delivery models are constructed in an integrated framework. We present a general graphical language and a knowledge editor that has been adapted to support the construction of learning…

In this paper, we present an ontology to represent the semantics of the IMS Learning Design (IMS LD) specification, a meta-language used to describe the main elements of the learning design process. The motivation of this work relies on the expressiveness limitations found on the current XML-Schema implementation of the IMS LD conceptual model. To…

Investigates the effects of context-weak versus context-strong tasks and learning style on the citation-frequencies and citation-percentages of four mental models (semantic networks, concept maps, frames/scripts, and schemata) students perceived to be inherent in a hypermedia learning environment. (Author/AEF)

The paper describes an ontology-based framework for bridging learning design and learning object content. In present solutions, researchers have proposed conceptual models and developed tools for both of those subjects, but without detailed discussions of how they can be used together. In this paper we advocate the use of ontologies to explicitly…

The objective of this paper is to introduce a standards-based model for adaptive e-learning and to investigate the conditions and tools required by authors to implement this model. Adaptation in the context of e-learning is about creating a learner experience that purposely adjusts to various conditions over a period of time with the intention of…

This paper presents a hybrid course framework at the Teachers College at Columbia University (New York) that seamlessly integrates a traditional course plan designed for on-campus students with an online course plan designed for distance learning students. Based on innovative teaching and learning principles, the course encourages active…

Describes a modelling language for representing teaching strategies, based in the context of the COCA intelligent tutoring system. Examines work on meta-reasoning in knowledge-based systems and describes COCA's architecture, giving details of the language used for representing teaching knowledge. Discusses implications for future work. (AEF)

This paper presents a new model for simulating procedural knowledge in the problem solving process with our ontological system, InfoMap. The method divides procedural knowledge into two parts: process control and action performer. By adopting InfoMap, we hope to help teachers construct curricula (declarative knowledge) and teaching strategies by…