Using a Concept Mapping Tool for Representing the Domain Knowledge

Domain knowledge (DK) is a basic part of an intelligent tutoring system (ITS). DK usually includes information about the concepts the ITS is dealing with and the teaching material itself, which can be considered as a set of learning objects (LOs). LOs are described by a data set called learning object metadata. Concepts are usually organized in a network, called a concept network or map. Each concept is associated with a number of LOs. In this paper, we present a tool for managing both types of information in DM: creating and editing (a) a concept network and (b) learning object metadata. Additionally, the tool can produce corresponding XML descriptions for each learning object metadata. Existing tools do not offer all the above capabilities.

2007

Lecture Notes in Computer Science, 2013

Concept mapping is a tool used in many classrooms and highly researched in the field of education. However, there are fewer concept mapping studies in the field of artificial intelligence in education, specifically within intelligent tutoring systems. Two studies highlight the important roles that concept maps and other non-linear organizers play in learning. Concept maps provide students with a macrostructure view of the information as well as allow students to easily see relationships between concepts. Students generating material for a concept map has shown high learning gains; however, students creating maps from scratch or students being provided a completed map has not seen such positive effects. The proposed study looks at the importance of the links, or relationships between concepts, within concept maps. We plan to provide students with partially filled in concept maps as note-taking devices to investigate how much and what kind of assistance or scaffolding is needed.

Advances in Intelligent Systems and Computing

Intelligent Tutoring Systems (ITS) are software tools that mimic a teacher's teaching methods through artificial intelligence techniques. The generalized model of these systems is divided into four main modules: tutoring, student, domain, and interface. Although it has been shown that ITS is very useful in cases where a teacher cannot be present, the development of these systems is expensive and time-consuming, since it requires experts and available programmers. Therefore, this research proposes a framework to develop an authoring tool to build ITS automatically, with a focus on the domain module. We consider that the domain model represents the most important module of the ITS because it contains the knowledge that should be taught and evaluated. Based on this module, the rest of the modules will make decisions.

Third International Conference on Advances in Computing, Electronics and Electrical Technology - CEET 2015, 2015

ABSTARCT-The intelligent tutoring systems (ITS) is the most recent alternative advancement to human tutors in the teaching and learning processes in today's educational environments that started over the past three decades. The main goal of an ITS is to help students to achieve maximum learning gain and improve their skills acquisition in a particular domain. For an intelligent tutoring system to be very effective in accomplishing these tasks, the system must be equipped with an explicit representation of the domain knowledge that is the subject of the learning activity (Domain model). But the task of acquiring and designing an effective domain knowledge representation is always challenging and difficult that has been the main concern of so many research projects in the fields of ITS and other artificial intelligence (AI) domains.

2007

The difficulty of domain knowledge acquisition is one of the most sensible challenges of intelligent tutoring systems. Relying on domain experts and building domain models from scratch are not viable solutions. The ability to automatically extract domain knowledge from documents can contribute to overcome these difficulties. In this paper, we use machine learning and natural language processing to parse documents and to generate domain concept maps and ontologies. We also show how an intelligent tutoring system benefits from the generated structures.

Proceedings of the II International Conference on …, 1995

Building an intelligent tutoring system (ITS) requires the ability to model and reason the domain knowledge, human thinking and learning processes, and the teaching process. Acquiring and encoding this large amount of knowledge is difficult and time-consuming. We have been searching for efficient ways to do these knowledge engineering tasks. This paper describes our efforts toward developing uniform data and control structures that can be used by a wide circle of authors, e.g., domain experts, teachers, curriculum developers, etc., who are involved in the ITS building process. One of our goals is to build tools that will enable experts (teachers) to use the computer directly. These tools are a model of an application of object-oriented software design methodology for designing ITS knowledge bases and manipulating their contents. Such approach makes the ITS building process more natural and more user friendly, and makes it easier to extend the set of tools used to build knowledge bases. An object-oriented model of ITS knowledge bases has been developed, and its two aspects: the design and organization of knowledge bases, and communication between the knowledge base and another module of an ITS or an ITS building tool, are presented in the paper.

Journal of e-learning and knowledge society, 2014

A VLE is a system where three main actors can be devised: the teacher in the role of instructional designer, the tutor, and the stu- dent. Instructional designers need easy interaction for specifying the course domain structure to the system, and for controlling how well the learning materials agree to such a structure. Tutors need tools for having a holistic perception of the evolution of single students and/or groups in the VLE during the learning process. Finally, students need self regulation in terms of controlling their learning rate, reflect on their learning strategies, and comparing with other people in the class. In this work we claim that sharing an implicit representation of the knowledge about the course domain between all these actors can meet the requirements stated before, and we present a tool that has been developed as part of the I-TUTOR project according to our claim. The tool analyzes a suitable document corpus describing the course domain, and generates a seman...

In this paper a general purpose tool for editing Concept Maps (CM-ED) is presented. This tool exhibits the following features: templates, views and facilities for multilingual concept maps. The tool has been used in different tasks of the Computer Aided Teaching/Learning area. Concretely: domain representation, exercise design and student model visualization.

Proceedings of Concepts and Ontologies in …, 2002

Web-based Educational Systems (WBES) is one of the fastest growing and challenging areas in educational technology research. To meet the high expectations and requirements of educational community, a present challenging goal is the development of advanced intelligent WBES that adapt their behavior to the learner's state of understanding. Concept-oriented (ontology-based) architectures come as a promising solution in the development of such systems. Conceptual (ontological) structures, such as concept maps, topic maps, and conceptual graphs have a great deal of potential for organizing, processing, and visualizing subject domain knowledge and for building learner models in WBES. Concept-based courseware employs conceptual domain presentation to link educational materials to a course structure. This allows for concept-based course sequencing that supports adaptive courseware generation, concept-based information retrieval, visualization, and navigation that help students to get oriented within a subject domain and build up their own understanding and conceptual association.