Mobile Computing and Mixed-Initiative Support for Writing Competence

Writing is a core skill that learners are expected to develop in their early school years and use effectively throughout their later school years. Historically, writing has been considered the purview of grade school education, yet there is evidence that learners seem to lack basic writing skills even at the university level. Unfortunately, the challenges posed by the volume of data created when students write have hampered writing researchers’ attempts to study the impacts of grade school writing initiatives in depth. This chapter introduces two novel approaches to academic writing activities that hold the potential to enhance writing competence and make it easier for researchers to understand the impact of writing interventions. The first uses mobile devices in a situated learning context, and the second uses a mixed-initiative writing system in the classroom.

Technology Enhanced Language Learning in Virtual Worlds

The application of Information Technology makes distance learning possible. Teachers can teach students who live in another side of the globe via Internet. They can see each others’ images and hear each others’ voices, which could not be done twenty years ago, through Internet. With the development of Internet, students can learn without the limitations of time and space. American Society for Training and Development proposed that digital learning includes learning through Internet, learning by computers, learning in virtual classrooms, and digital cooperation. The digitalized course contents can be transmitted via Internet, local or global networks, audio books, videotapes, satellite, interactive televisions, and compact disks.

Intelligent Model-Based Feedback

Automated knowledge assessment methodologies provide the technological background for producing instant feedback at all times during the learning process. It is expected that the availability of such individual, dynamic, and timely feedback supports the learner’s self-regulated learning. This chapter provides the theoretical background for an intelligent feedback approach and introduces two automated model-based feedback tools: TASA (Text-Guided Automated Self Assessment) and iGRAF (Instant Graphical Feedback). The chapter concludes with a discussion of the two feedback approaches and future research directions.

Analyzing Critical Functions of Recording Tools for Synchronous Cyber Classroom Instruction

Digital learning content is one of the crucial components for online courses. There are many ways for creating digital learning contents. Among them, recording of live instructional activities is becoming one of the most important methods to produce learning contents. However, the previous studies mainly focused on how to create digital learning content in offline mode, very few literatures addressed how to effectively record live instructional activities for digital learning content. This chapter focuses on how to effectively record live instructional activities conducted in synchronous cyber classrooms. The aims of this chapter are firstly to identify the recording scenarios for different modes of instructions in synchronous cyber classrooms, secondly to explore the functional requirements for different types of instruction modes, and finally to find out the best match between the instruction modes and the essential functions of recording tools.

Software Agent Systems for Supporting Student Team Project Working

This chapter describes the trial of an experimental software agent system, designed to help students to get started on their team projects, by allocating tasks to individuals and agree on ground rules for the team. Students taking Information Technology degree programmes tried the system over several years, providing feedback on the suitability of this sort of system for supporting the process aspects of team project working. Findings from this research showed that students used the output from the system in different ways according to their previous experience and suggested additional features that students would like to see in a system for supporting their team working, which could be incorporated into future development of the system.

Context-aware Framework for Supporting Personalisation and Adaptation in Creation of Learning Designs

One of the current interests in the field of learning design is to find ways to support teachers who wish to develop designs that incorporate digital technologies. The focus from a pedagogical point of view is to enable teachers to exploit the constructivist potential of digital technologies for learning: those that support learners in discussing, collaborating, and creating user-generated designs. These general requirements align at the high-level with the Semantic Web vision of resource creation, sharing and re-use. Leveraging the Semantic Web developments and exploiting the observation that ontological models can form the domain grounding for context-aware applications, this chapter provides the design of a framework for supporting next generation learning design tools that provide adaptive and personalised experiences. Included in the chapter are the initial findings from the result of a user study of the framework.

Improving User Profiling for a Richer Personalization

This chapter presents the context-aware aspects of ADAPTSUR, a personalization approach designed for e-learning environments. The main features of ADAPTSUR are described and illustrated, showing how to use it to model context and culture for personalization in e-learning environments. The authors describe two materializations of the proposed approach, an adaptive e-learning system and an intelligent tutor, which provide personalized assistance to students taking into account their profiles. Finally, the authors discuss the benefits of their proposal.

Boosting Semantic Relations for Example Population in Concept Learning

In this chapter, we discuss the advantages of expansion of learning objects through directed semantic relations (DSRs). We then propose an approach that can automatically construct the DSRs between learning objects and form a DSR graph. This approach addresses the problem to those learners with broad backgrounds. Also, we design two learning activities to show that how this DSR graph can be used to scaffold students’ semantic reasoning. The case study suggests relevant benefit of applying semantic technologies in educational context. This may implicate that this kind of relations can foster systematic thinking and complex domain knowledge inferences by complementing the raw chunks of data with different kinds of meaningful relations (e.g. feeding relation) and semantic associations.

E-Learning Tools with Intelligent Assessment and Feedback for Mathematics Study

Mathematics students, often among large university classes of several hundreds of students, are easily daunted when solving math problems. Lacking individual feedback, they easily give up. To bolster learning, Computer-Aided Assessment may help students by giving them individual feedback about their progress. This article presents some general requirements for Intelligent Assessment using semi-automatic feedback in mathematics education with a special focus on solution processes. Intelligent Assessment implies the combination of human assessment along with electronic assessment via intelligent software for evaluating a student’s performance in a specific subject. Assessment tools are used to categorize solutions and detect errors as accurately as possible. Unusual and novel solutions and errors that the computer cannot categorize are forwarded to a tutor or teacher for assessment. Several examples demonstrate that semi-automatic and process-oriented Intelligent Assessment can help to improve learning and, ultimately, student self-confidence in mastering problems.

A Tool for Adaptive E-Assessment of Project Management Competences

This chapter proposes an e-assessment method for project management competences, using the computer adaptive testing (CAT) principle. Competences are represented using concept space graphs. The proposed model increases the tests configurability by considering several knowledge constraints when an item is selected. The proposed model is also seen as a self-directed-learning-tool, useful in the preparation process for project management certifications. The model is validated by comparison with an existing e-assessment tool, used for simulation purposes; statistic results are presented and analyzed. Although the initial level of knowledge of each user has a great impact on the final results obtained by that user, preparation with the proposed e-assessment method proved to be more efficient.