Hyperbook Features Supporting Active Reading Skills

MetaLinks is a domain independent authoring tool and web server for adaptive textbooks (“hyperbooks”) that supports active reading. We show how cognitive and educational research and theory from the areas of text comprehension and active reading strategies can be applied to hyperbooks. Adaptivity and other MetaLinks features allow us to create a single hyperbook that serves multiple purposes. A MetaLinks hyperbook can serve as textbook and reference book; can be equally appropriate for novice and advanced readers, and can be coherently read from a number of thematic perspectives. “Active reading/learning” refers to a set of high level reading, searching, problem solving, and metacognitive skills. We describe the MetaLinks system and how its features support a number of behavioral, cognitive, and metacognitive active reading skills.

A Conceptual Architecture for the Development of Interactive Educational Media

Learning is more than knowledge acquisition; it often involves the active participation of the learner in a variety of knowledge- and skills-based learning and training activities. Interactive multimedia technology can support the variety of interaction channels and languages required to facilitate interactive learning and teaching. A conceptual architecture for interactive educational multimedia can support the development of such multimedia systems. Such an architecture needs to embed multimedia technology into a coherent educational context. A framework based on an integrated interaction model is needed to capture learning and training activities in an online setting from an educational perspective, to describe them in the human-computer context, and to integrate them with mechanisms and principles of multimedia interaction.

A Special Purpose E-Learning Environment

This study presents the concept of Special Purpose E-Learning Environments (SPELEs). The main aim of these environments is to meet the learners’ individual learning differences related to a specific learning subject. An architecture of the design of SPELEs is presented. The background of this design, which is based on interpretations of modern constructivist and social views of learning in the Internet context, is also presented. Based on this architecture a specific SPELE, designed for the learning of concepts related to Files and Peripheral Storage Devices (FPSD.), is demonstrated and its pilot evaluation study with real students is reported. The analysis of the data verifies the theoretical design of SPELEs, which consists of five parts: (a) organization of the content of a specific learning subject, (b) learning activities (c) learner activity space (d) learner assessment, and (e) learner communication. The analysis of the data also gives evidence for future improvements of the specific SPELE mentioned above.

Effects of Teaching Science through Immersive Virtual Environments

The North Dakota State University (NDSU) World Wide Web Instructional Committee (WWWIC) is an inter-disciplinary research team, which has, since the 1990s, developed multi-user, interactive virtual environments (IVEs) to teach the structure and process of various branches of science. The most developed of these include the “Geology Explorer” and the “Virtual Cell,” (VCell). This chapter describes the key features the Virtual Cell and the Geology Explorer, the underlying philosophy and educational theory guiding their development, and results of large controlled experiments that investigate their effectiveness on student learning. Additionally, ongoing projects andexperiments of the team relevant to the development and dissemination of these software programs are explored. The underlying purpose of our IVEs is to increase student achievement and scientific problem-solving skills while providing students with opportunities to learn-by-doing in a real-world context. Research findings collected for almost a decade demonstrate the positive impact of our IVEs on science students.

Intelligent and Adaptive Web-Based Instruction

This chapter describes Web-based instructional tutors that support active and engaging learning. Towards that end, a theoretical foundation for designing such tutors is proposed and two Web-based tutors described. The tutors reason about a student’s knowledge and their own teaching strategies while taking advantage of the possibilities of the Web, by being open to other resources (Web sites) and other people (online communities). One tutor, Rashi, provides problem-based activities and tracks a student’s critical thinking in biology and geology, and the second, iMANIC, uses hypermedia to customize online lectures for individual students based on learning need. This work provides promising data points for the development of authentic and effective learning that can take advantage of the possibilities of the Web, without being rooted in extensions of what already exists in the classroom, such as lectures or bulletin boards.

An Integrated Platform for Educational Virtual Environments

In this chapter, we present the design and implementation of an integrated platform for Educational Virtual Environments. This platform aims to support an educational community, synchronous online courses in multi-user three-dimensional (3D) environments, and the creation and access of asynchronous courses through a learning content management system. In order to offer synchronous courses, we have implementeda system called EVE-II, which supports stable event sharing for multi-user 3D places, easy creation of multi-user 3D places, H.323-based voice- over IP services fully integrated in a 3D space, as well as many concurrent 3D multi-user spaces.

Modeling of Adaptive Tutoring Processes

In this chapter, a formal, adaptive tutoring process model for case-based Intelligent Tutoring Systems (ITSs) is described. Combining methods of Artificial Intelligence and Cognitive Science led to the development of ITSs more than 30 years ago. In contrast to the common agreement about the ITSs’ architecture, components of ITSs are rarely reusable. Reusability in ITSs is intimately connected with the application domain, that is, with the contents that should be learned and with the teaching and learning strategy. An example of a learning strategy is case-based learning, where the adaptation of the learning material to the learner plays a major role. Adaptation should take place automatically at runtime, and thus should be part of the ITS’s functionality. To support the development of ITSs with reusable components and the communication about and the evaluation of similar ITSs, a formal approach has been chosen. This approach is called the tutoring process model.

Knowledge Representation in Intelligent Educational Systems

In this chapter, we deal with knowledge representation in Intelligent Educational Systems (IESs). We make an effort to define requirements for Knowledge Representation (KR) in an IES. The requirements concern all stages of an IES’s life cycle (construction, operation, and maintenance), all types of users (experts, engineers, learners) and all its modules (domain knowledge, user model, pedagogical model). We also briefly present various KR schemes, focusing on neurules, a kind of hybrid rules integrating symbolic rules and nuerocomputing. We then compare all of them as far as the specified KR requirements are concerned. It appears that various hybrid approaches to knowledge representation can satisfy the requirements in a greater degree than that of single representations. Another finding is that there is not a hybrid scheme that can satisfythe requirements of all the modules of an IES. So, multiple representations or a multi-paradigm representation environment could provide a solution to requirements satisfaction.

Automatic Learning Object Selection and Sequencing in Web0Based Intelligent Learning Systems

Automatic courseware authoring is recognized as among the most interesting research questions in intelligent Web-based education. Automatic courseware authoring is the process of automatic learning object selection and sequencing. In most intelligent learning systems that incorporate course sequencing techniques, learning object selection and sequencing are based on a set of teaching rules according to the cognitive style or learning preferences of the learners. In spite of the fact that most of these rules are generic (i.e., domain independent), there are no well-defined and commonly accepted rules on how the learning objects should be selected and how they should be sequenced to make “instructional sense.” Moreover, in order to design adaptive learning systems, a huge set of rules is required, since dependencies between educational characteristics of learning objects and learners are rather complex. In this chapter, we address the learning object selection and sequencing problem in intelligent learning systems proposing a methodology that, instead of forcing an instructional designer to manually define the set of selection and sequencing rules, produces a decision model that mimics the way the designer decides, based on the observation of the designer’s reaction over a small-scale learning object selection case.

Ontologies and Contracts in the Automation of Learning Object Management Systems

Current standardized e-learning systems are centred on the concept of learning object. Unfortunately, specifications and standards in the field do not provide details about the use of well-known knowledge representations for the sake of automating some processes, like selection and composition of learning objects, or adaptation to the user or platform. Precise usage specifications for ontologies in e-learning would foster automation in learning systems, but this requires concrete, machine-oriented interpretations for metadata elements. This chapter focuses on ontologies as shared knowledge representations that can be used to obtain enhanced learning object metadata records in order to enable automated or semi-automated consistent processes inside Learning Management Systems. In particular, two efforts towards enhancing automation are presented: a contractual approach based on pre- and post-conditions, and the so-called process semantic conformance profiles.