The Future of Technology Enhanced Active Learning

The notion of active learning refers to the active involvement of learner in the learning process, capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learner-content interaction, is a central aspect of technology- enhanced active learning. In this roadmap, the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined, and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap.

Military Applications of Adaptive Training Technology

This chapter provides an overview of the use of adaptive training technology within the military domain. Throughout the chapter, we will discuss the use of intelligent tutoring, adaptive interactive multimedia instruction, and their combination to form closed-loop adaptive training. Frequently, the discussion of a particular approach will be illustrated with one or more case-studies. Moreover, we will explore impediments to widespread adoption of these interventions throughout the military, methods to overcome these impediments, and the migration of this technology into other domains. We will conclude by summarizing trends that are likely to characterize on-going development. Rather than providing a comprehensive review of technology-enhanced learning in the military, which is likely to be outdated before it is published, the author hopes that this illustrative review will open new avenues of thought for researchers, developers, and purchasers of these systems.

Knowledge Mining for Adaptive Multimedia Web-Based Educational Platform

This chapter introduces an Adaptive Web-Based Educational platform that maximizes the usefulness of the online information that online students retrieve from the Web. It shows in a data driven format that information has to be personalized and adapted to the needs of individual students; therefore, educational materials need to be tailored to fit these needs: learning styles, prior knowledge of individual students, and recommendations. This approach offers several techniques to present the learning material for different types of learners and for different learning styles. User models (user profiles) are created using a combination of clustering techniques and association rules mining. These models represent the learning technique, learning style, and learning sequence, which can help improve the learning experience on the Web site for new users. Furthermore, the user models can be used to create an intelligent system that provides recommendations for future online students whose profile matches one of the mined profiles that represents the discovered user models.

A Framework for Building Emotional-Motivational Agents as Intelligent Tutoring Entities

This chapter presents our efforts to integrate role theory and agent technology in order to support collaborative work/learning processes between users spatially distributed within a synchronous collaborative virtual environment. Our work aims to overcome a major inconvenience in distance education systems: tutors’ difficulties when following up a distance collaborative learning process and in particular those students who cannot keep up progress with their team-mates. Our approach embraces the learning paradigms mentioned above and the work on pedagogical and intelligent agents as a mechanism for modelling and analyzing student-tutor interactions.

Metacognition for Enhancing Online Learning

The existing research in the field of traditional didactics shows that students who have good metacognitive skills often achieve better scholastic results. Therefore, it seems that students who are aware of their cognitive processes and are able to self-monitor their learning activities tackle didactic tasks with greater success. The chapter presents an analysis of studies regarding applications of metacognition within technological learning environments which have been implemented in the last few years, and this is followed by a description of the features of the Gym2learn system. This system aims to reveal self-regulating processes and guide the student in acquiring all the steps of the executive control of some important comprehension strategies for understanding hypertexts.

The Importance of Training Needs Analysis in Authoring Technology Enhanced Learning for Companies

This chapter looks at the potential to exploit existing technology enhanced learning (TEL) authoring tools to provide customised learning solutions that address both businesses’ needs and employees learning requirements. It examines the feasibility of integrating training needs analysis into existing authoring tools to automate customisation. The chapter outlines a framework for such using best practices in the technology enhanced learning field such as sound instructional design theories, standard compliant metadata sets, and LO granularity while exploiting well established TEL authoring models. The chapter also highlights how this framework was implemented in practice in the form of an electronic tool that ties closely with existing learning content management systems.

The Blended Learning Classroom

This blended learning classroom (BLC) case study identifies and describes successful procedures and methodologies that widen the use of online tools in virtual environments. It provides a systematic and organized access to the plethora of free social software available online for the development of collaborative learning activities. The goal of this particular BLC professional development activity was to offer a face-to-face group of English teachers in Venezuela the opportunity to meet members of an international community of practice (CoP) and together review a packaged learning course material online. Blended technology, the mix and match of available tools, served to display the wide use of resources and each person’s skills. By exploring online tools, participants gained an opportunity for learning about both educational theory and the use of technology. The experience described here shows a prototype of future pathways towards educational content use and development.

Technology Enhanced Learning Tools

This chapter emphasizes the variety of today’s e-learning systems. They have both positive and negative characteristics. Several useful tools are common for these systems. The main part of this chapter contains a detailed description of e-learning systems and their tools. If a system is appropriate for the needs of the learner then it has more intelligent behavior and its tools are more specialized. Some systems have separate tools that act as standalone applications. Others contain built in tools. In this chapter, the e-learning tools are grouped by their functions. Owing to standardization efforts, the differences between the e-learning tools become their advantages, and the e-learning systems become interoperable. The intelligent learning management systems (ILMS) become a new way to integrate the benefits of the different e-learning systems. At the end of the chapter there is a short description of an ILMS named Multitutor. This represents a possible way of future e-learning systems development.

Pedagogical Uses of Multimedia Annotators and Players

Multimedia materials form an increasingly important part of technology-enhanced learning (TEL). We present two kinds of related computer programs, multimedia annotators and multimedia players, which provide greatly improved control over how the user navigates, searches, and displays multimedia materials. Our main focus will be on MannX (Multimedia Annotator—XML). The objective of this chapter is to familiarize the reader with multimedia annotators and players, explain why and how they should be used for learning and especially for foreign language learning, present the best practices for their design, and outline the future directions for developing this new technology and its pedagogical applications. We believe that for many fields of study annotated and searchable multimedia materials are the best vehicle for instruction and learning.

Towards More Intelligent Assessment Systems

This chapter presents a framework for intelligent analysis of the students’ knowledge in assessment systems, using description logics (DLs) reasoning techniques. The framework is based on Model Driven Architecture (MDA) software engineering standards. It starts from the IMS Question and Test Interoperability (QTI) standard and includes MDA-based metamodel and model transformations for QTI assessment systems. It also specifies an architecture for QTI assessment systems that is reusable, extensible, and facilitates interoperability between its component systems. An implementation of the QTI metamodel and the relevant example of transformations is provided in order to support developments according to the proposed framework.