Many interactive learning environments (ILEs) offer on-demand help, intended to positively influence learning. Recent studies report evidence that although effective help-seeking behavior in ILEs is related to better learning outcomes, learners are not using help facilities effectively. This selective review (a) examines theoretical perspectives on the role of on-demand help in ILEs, (b) reviews literature on the relations between help seeking and learning in ILEs, and (c) identifies reasons for the lack of effective help use. We review the effect of system-related factors, of student-related factors, and of interactions between these factors. The interaction between metacognitive skills and cognitive factors is important for appropriate help seeking, as are a potentially large space of system-related factors as well as interactions among learner- and system-related factors. We suggest directions for future research.

AHA! is a simple Web-based adaptive hypermedia system. Because of this simplicity it has been studied and experimented with in several research groups, see e.g. (Cini & Valdeni de Lima, 2002), (Calvi & Cristea, 2002), (Romero et al., 2002). This paper identifies shortcomings in AHA! and presents AHA! version 2.0 which tries to overcome the known problems with AHA! while maintaining its biggest asset: simplicity. We illustrate how different user modeling and adaptation aspects can be expressed in the new AHA! system (that would be difficult in the old system, and impossible in most other systems).

Websites that show the same information to all visitors, often also presented in the same way, are no longer considered acceptable. Creating a Website with specific information for different user groups (or even individual users) is cumbersome and leads to a lot of redundancy. AHA! is a simple server-side extension that enables information providers to add automatic personalization, or adaptation, to a Website, thereby eliminating redundant and potentially inconsistent information.

In this paper we propose a set of guidelines for an adaptive authoring environment of adaptive educational h?permedia. This set consists of relevant and necessary functionalities of authoring systems (AS) for adaptive teaching and/or learning environments (LE). We extracted the core functionalities by analysing MyEnglishTeacher (MyET) and AlMS - two independently designed and built AS for adaptable/adaptive LE. The extended core led us to a conceptbased layered approach with respect to concept- and attribute-level adaptation, as well as lesson and presentation adaptation. We believe that providing adaptive authoring support for adaptive hypermedia will have a strong impact on the authors' motivation and efficiency in performing their tasks and consequently will increase the popularity of adaptive hypermedia.

Web Information Systems (WIS) present up-to-date information on the Web based on data coming from heterogeneous sources. In previous

Multimodal interfaces are becoming increasingly ubiquitous with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. In addition to improving access and delivery capabilities, such interfaces enable flexible and personalized dialogs with websites, much like a conversation between humans. In this paper, we present a software framework for multimodal web interaction management that supports mixed-initiative dialogs between users and websites. A mixed-initiative dialog is one where the user and the website take turns changing the flow of interaction. The framework supports the functional specification and realization of such dialogs using staging transformations -- a theory for representing and reasoning about dialogs based on partial input. It supports multiple interaction interfaces, and offers sessioning, caching, and co-ordination functions through the use of an interaction manager. Two case studies are presented to illustrate the promise of this approach.

A major characteristic of developments in the broad field of Artificial Intelligence (AI) during the 1990s has been an increasing integration of AI with other disciplines. A number of other computer science fields and technologies have been used in developing intelligent systems, starting from traditional information systems and databases, to modern distributed systems and the Internet. This paper surveys knowledge modeling techniques that have received most attention in recent years among developers of intelligent systems, AI practitioners and researchers. The techniques are described from two perspectives, theoretical and practical. Hence the first part of the paper presents major theoretical and architectural concepts, design approaches, and research issues. The second part discusses several practical systems, applications, and ongoing projects that use and implement the techniques described in the first part. Finally, the paper briefly covers some of the most recent results in the fields of intelligent manufacturing systems, intelligent tutoring systems, and ontologies. 2 1.

The challenge of the Semantic Web Mining technologies in the e-Learning domain can relate to the provision of personalized experiences for the users. Particularly, these applications can take into consideration the individual needs and requirements of learners. In this paper, we propose a framework for personalised e-Learning based on aggregate usage profiles and a domain ontology. We have distinguished two stages in the whole process, one of offline tasks that includes data preparation, ontology creation and usage mining and one of online tasks that concerns the production of recommendations.

Abstract. Due to the rapid growth of the Web, there is an increasing need for methodologies that support the design of Web-based Information Systems (WIS). After investigating the application of existing hypermedia design methodologies in the context of automated hypermedia presentation design we propose a specification framework for this context. The framework considers the possibility of dynamically gathering information from a collection of structured, but also possibly heterogeneous sources (relational or object-oriented databases, XML repositories etc.). The methodology associated with the framework shows two levels of abstraction: the logical level, and the presentation level. At the logical level the application diagram captures the design of slices, thus specifying the content related grouping of data elements and their relationships. At the presentation level, the presentation diagram bridges the logical level and the actual implementation by specifying how the design of slices is translated into hypermedia mechanisms, e.g. hyperlinks. 1

The AHA! system (De Bra & Calvi, 1998, De Bra et al, 2002) has been repeatedly extended over the past few years, focusing on adaptation flexibility. This has resulted in a powerful adaptation engine, but little support for creating adaptive applications. AHA! provides tools for defining the conceptual structure and the adaptation of an application, but leaves the presentation and additional support tools up to the author of that application. Interbook (Brusilovsky et al, 1998) on the other hand is a simple environment for creating and serving adaptive textbooks, with a rich user interface characterized by the use of multiple windows and frames. Authors write an annotated Microsoft Word file, which is translated to a series of files used by Interbook. This paper presents an extension of AHA! that enables a high-level specification of the presentation (layout) of an AHA! application. We illustrate this extension through a powerful demonstrator: an Interbook to AHA! compiler. The source format for Interbook is translated to AHA! with the new Layout model. The dynamic structures of the Layout model are easily extendible and give author the power to adapt the user interface to the nature of the application. AHA! can thus "emulate" not just Interbook but other adaptive environments as well.