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The purpose of this paper is to review the use of adaptive systems in education. It is intended to be a useful introduction for the non-specialist reader.

A distinction is made between intelligent tutoring systems (ITSs) and adaptive hypermedia systems (AHSs). The two kinds of system are defined, compared and contrasted. Examples of the implementation of the two kinds of system are included.

Similarities and differences between the two kinds of system are highlighted. A conceptual unification is proposed based on the architecture of Course Assembly System and Tutorial Environment, a seminal prototype learning environment developed by Pask and Scott in the 1970s as an application of Pask’s conversation theory.

The architecture shows how the key aspects of ITSs and AHSs can be combined to complement each other. It is intended to be an original contribution that is of particular interest for the specialist reader.

The purpose of this paper is to review recent developments in educational informatics relating to the provision by information systems of pedagogical support to web‐based learners, and to propose further investigation of the feasibility and potential value of web‐based “conversational” information systems to complement adaptive hypermedia and information retrieval systems.

The potential of Pask's conversation theory is considered as a potentially useful framework for the development of information systems capable of providing pedagogical support for web‐based learners, complementary to that provided by existing computer‐assisted learning and adaptive hypermedia systems. The potential role and application of entailment meshes are reviewed in relation to other forms of knowledge representation including classifications, semantic networks, ontologies and representations based on knowledge space theory.

Concludes that conversation theory could be a useful framework to support the development of web‐based “conversational” information that would complement aspects of computer‐assisted learning, adaptive hypermedia and information retrieval systems. The entailment mesh knowledge representation associated with conversation theory provides the potential for providing particularly rich pedagogical support by virtue of its properties of cyclicity, consistency and connectivity, designed to support deep and enduring levels of understanding.

Although based on a considerable body of theoretical and empirical work relating to conversation theory, the paper remains speculative in that the gap is still great between, on the one hand, what has so far been achieved and, on the other, the practical realisation of its potential to enhance web‐based learning. Much work remains to be done in terms of exploring the extent to which procedures developed and benefits found in relatively small‐scale experimental contexts can effectively be scaled to yield enhanced support for “real world” learning‐related information behaviour.

The ideas of Pask, discussed in this paper, are capable of guiding the structuring of information according to parameters designed to facilitate deep and enduring understanding via interactive “conversational” engagement between the conceptual structures of information source authors and learners. If one can scale Pask's work to “real world” learning‐related information behaviour, one can increase the range of web‐based information systems and services capable of providing pedagogical support to web‐based learners.

Interest is currently growing in open social learner modeling (OSLM), which means making peer models and a learner's own model visible to encourage users in e-learning. The purpose of this study is to examine students' views about the OSLM in an e-learning system.

This case study was conducted with 40 undergraduate students enrolled in advanced programming and database management system courses. A Likert-type questionnaire and open-ended questions were used to obtain the students' views. System usage data were also analyzed to ensure the richness and diversity of the overall data set.

The quantitative data of the students' views were analyzed with descriptive statistics; the results are presented as graphics. The qualitative data of the students' views were examined by content analysis to derive themes. These themes are organized into four subtopics: the students' positive views, their negative views, their improvement suggestions and their preferences about using similar OSLM visualizations in other e-learning systems. The students' subjective views are discussed in the context of their recorded interactions with the system.

Competition due to seeing peer models was considered by participants both as positive and negative features of the learning system. So, this study revealed that, the ways to combine peer learner models to e-learning systems that promote positive competition without resulting social pressure, still need to be explored.

By combining open learner models with open peer models, OSLM enhances the learning process in three different ways: it supports self-regulation, encourages competition and empowers self-evaluation. To take advantage of these positive contributions, practitioners should consider enhancing e-learning systems with both own learner and peer model features.

Despite increasing interest in OSLM studies, several limitations and problems must be addressed such as sparsity of data and lack of study of different contexts and cultures. To date, no published study in this area exists in Turkey. The purpose of this study is to fill this gap by examining OSLM features in an e-learning system from the perspectives of Turkish students by using both their system interaction data and their subjective views.

In this paper a conception of the model for learning scenario determination is presented. We define the learning scenario as a sequence of the hypermedia pages, representing particular knowledge units, and tests related to them. The scenario determination is a dynamic process that begins when a new student takes up a course. The opening scenario for this student is chosen as the consensus of the final scenarios of the students, who have already finished this course, and who belong to a class of the learners similar to the new one. We have elaborated the consensus‐based procedure for the scenario determination. Since this procedure operates on a set of similar learners, we have developed the conceptions of learner’s profile and students’ classification. The learner’s profile is proposed to include the attributes describing students’ personal data (as name, birthday etc.), their cognitive and learning styles as well as their usage data (represented by the learning scenarios). The students’ classification is based on a set of the basic attributes that seem to influence the learning effects. Their significance is verified during the learning process. We have also elaborated the procedure of reducing undistinguishable values of the attribute and removing useless attributes from the set of basic attributes. A learning procedure proposed, describes generally the situations when the scenario is modified, and the methods used for its modification.

This research aims to investigate how a generic web‐based ITS can be created which will adapt the training content in real time, to the needs of the individual trainee across any domain.

After examining the various alternatives SCORM was adopted in this project because it provided an infrastructure that makes it possible to deliver personalised learning dynamically using re‐usable learning objects.

The results show that a system which presents a student with content that is supplementary to an authored course should be accompanied by a tool to help the trainee's navigation. For such a tool, key functionality would be: first, to identify learning objects that would take the student towards the ultimate learning goals; second, to suggest a pathway through the authored course structure and additional learning objects to the student; and finally, to present the student with different choices of pathway, such as fastest, most comprehensive and most popular routes.

This investigation has taken another approach of adapting the course by displaying an adapted set of learning objects to the trainee, instead of using a linear course structure.

Through harnessing the benefits of the internet, e-learning systems provide flexible learning opportunities that can be delivered at a fixed cost at a time and place to suit the user. As such, e-learning systems can allow students to learn at their own pace while also being suitable for both distance and classroom-based learning activities. Adaptive educational hypermedia systems are e-learning systems that employ artificial intelligence. They deliver personalised online learning interventions that extend electronic learning experiences beyond a mere computerised book through the use of intelligence that adapts the content presented to a user according to a range of factors including individual needs, learning styles and existing knowledge. The purpose of this paper is to describe a novel adaptive e-learning system called dyslexia adaptive e-learning management system (DAELMS). For the purpose of this paper, the term DAELMS will be employed to describe the overall e-learning system that incorporates the required functionality to adapt to students’ learning styles and dyslexia type.

The DAELMS is a complex system that will require a significant amount of time and expertise in knowledge engineering and formatting (i.e. dyslexia type, learning styles, domain knowledge) to develop. One of the most effective methods of approaching this complex task is to formalise the development of a DAELMS that can be applied to different learning styles models and education domains. Four distinct phases of development are proposed for creating the DAELMS. In this paper, we will discuss Phase 3 which is the implementation and some adaption algorithms while in future papers will discuss the other phases.

An experimental study was conducted to validate the proposed generic methodology and the architecture of the DAELMS. The system has been evaluated by group of university students studying a Computer Science related majors. The evaluation results proves that when the system provide the user with learning materials matches their learning style or dyslexia type it enhances their learning outcomes.

The DAELMS correlates each given dyslexia type with its associated preferred learning style and subsequently adapts the learning material presented to the student. The DAELMS represents an adaptive e-learning system that incorporates several personalisation options including navigation, structure of curriculum, presentation, guidance and assistive technologies that are designed to ensure the learning experience is directly aligned with the user's dyslexia type and associated preferred learning style.

This article aims to propose an adaptation algorithm that combines the analytical hierarchy process (AHP), a rule-based system, and a k-means clustering algorithm. Informatic tools are very useful to enhance the learning process in the classroom. The large variety of these tools require advanced decision-making techniques to select parameters, such as student profiles and preferences, to adjust content and information display, according to specific characteristics and necessities of students. They are part of the Kamachiy–Idukay (KI), a platform to offer adaptative educational services to students with learning difficulties or disabilities.

The design and implementation of the adaptation algorithm comprises the following phases: utilization of the AHP to determine the most important student parameters, parameter to take into account in the adaptation process, such as preferences, learning styles, performance in language, attention and memory aspects and disabilities; designing the first part of the adaptation algorithm, based on a rule-based system; designing the second part of the adaptation algorithm, based on k-means clustering; integration of the adaptation algorithm to KI; and validation of the approach in a primary school in Bogotá (Colombia).

The main approach is the application of computational techniques, namely, rule-based systems and k-means clustering, plus an AHP prioritization at design time to yield a system to support the teaching–learning process for students with disabilities or learning difficulties.

The algorithm found several groups of students with specific learning difficulties that required adapted activities. The algorithm also prioritized activities according to learning style and preferences. The results of the application of this system in a real classroom yielded positive results.

The algorithm performs adaptation for students with mild disabilities or learning difficulties (language, attention and memory). The algorithm does not address severe disabilities that could greatly affect cognitive abilities.

The main contribution of this paper is an adaptation algorithm with the following distinctive characteristics, namely, designed utilizing the AHP, which ensures a proper prioritization of the student characteristics in the adaptation process, and utilizes a rule-based system to identify different adaptation scenarios and k-means clustering to group students with similar adaptation requirements.

While the World Wide Web (WWW or Web) is steadily expanding, electronic books (e‐books) remain a niche market. In this article, it is first postulated that specialized contents and device independence can make Web‐based e‐books compete with paper prints; and that adaptive features that can be implemented by client‐side computing are relevant for e‐books, while more complex forms of adaptation requiring server‐side computations are not. Then, enhancements of the WWW standards (specifically of XML, XHTML, of the style‐sheet languages CSS and XSL, and of the linking language XLink) are proposed for a better support of client‐side adaptation and device independent content modeling. Finally, advanced browsing functionalities desirable for e‐books as well as their implementation in the WWW context are described.

Ubiquitous web applications (UWA) are a new type of web applications which are accessed in various contexts, i.e. through different devices, by users with various interests, at anytime from anyplace around the globe. For such full‐fledged, complex software systems, a methodologically sound engineering approach in terms of model‐driven engineering (MDE) is crucial. Several modeling approaches have already been proposed that capture the ubiquitous nature of web applications, each of them having different origins, pursuing different goals and providing a pantheon of concepts. This paper aims to give an in‐depth comparison of seven modeling approaches supporting the development of UWAs.

This methodology is conducted by applying a detailed set of evaluation criteria and by demonstrating its applicability on basis of an exemplary tourism web application. In particular, five commonly found ubiquitous scenarios are investigated, thus providing initial insight into the modeling concepts of each approach as well as to facilitate their comparability.

The results gained indicate that many modeling approaches lack a proper MDE foundation in terms of meta‐models and tool support. The proposed modeling mechanisms for ubiquity are often limited, since they neither cover all relevant context factors in an explicit, self‐contained, and extensible way, nor allow for a wide spectrum of extensible adaptation operations. The provided modeling concepts frequently do not allow dealing with all different parts of a web application in terms of its content, hypertext, and presentation levels as well as their structural and behavioral features. Finally, current modeling approaches do not reflect the crosscutting nature of ubiquity but rather intermingle context and adaptation issues with the core parts of a web application, thus hampering maintainability and extensibility.

Different from other surveys in the area of modeling web applications, this paper specifically considers modeling concepts for their ubiquitous nature, together with an investigation of available support for MDD in a comprehensive way, using a well‐defined as well as fine‐grained catalogue of more than 30 evaluation criteria.

The purpose of this paper is to identify the different sequence generation techniques for learning, which are applied to a broad category of personalized learning experiences. The papers have been classified using different attributes, such as the techniques used for sequence generation, attributes used for sequence generation; whether the learner is profiled automatically or manually; and whether the path generated is dynamic or static.

The search for terms learning sequence generation and E-learning produced thousands of results. The results were filtered, and a few questions were answered before including them in the review. Papers published only after 2005 were included in the review.

The findings of the paper were: most of the systems generated non-adaptive paths. Systems asked the learners to manually enter their attributes. The systems used one or a maximum of two learner attributes for path generation.

The review pointed out the importance and benefits of learning sequence generation systems. The problems in existing systems and future areas of research were identified which will help future researchers to pursue research in this area.