Adaptive Hypermedia Research Articles

The open corpus challenge in eLearning

Learning has transcended into a life-long endeavor in the information age. It is no longer restricted to confines of formal classrooms. Consequently, a student is not restricted to traditional learning resources like teachers, textbooks or printed content. Digital resources available on the Internet form a very significant component of self-learning. Copious volumes of learning resources without legal barriers to self-learning reside in digital repositories, educational institution portals and on numerous websites. Learners wishing to utilize the web for personalized learning are faced with a daunting array of content to wade through and select the suitable ones to fulfill his/her learning objectives. Therefore, it is not a question of availability; it is one of relevance and suitability. Typically, in addition to time constraints, learners lack the expertise to screen content for effective eLearning. Adaptive hypermedia systems (AHSs) offer a path to harnessing this large volume of learning resources for personalized learning. This review paper provides a concise and coherent discussion about the evolution of AHSs along with the challenges that need to be addressed for effectively harnessing openly available educational resources referred to as open corpus resources (OCRs).

ACM UMAP 2018 - User Modeling, Adaptation and Personalization

UMAP (User Modeling, Adaptation and Personalization) is the premier international conference for researchers and practitioners working on systems that adapt to individual users, to groups of users, and that collect, represent, and model user information. UMAP is the successor to the biennial User Modeling (UM) and Adaptive Hypermedia and Adaptive Web-based Systems (AH) conferences that were merged in 2009. It is sponsored by ACM SIGCHI and SIGWEB, and organized under the auspices of User Modeling Inc. The proceedings are published by ACM and will be part of the ACM Digital Library.

Selection and Prioritization of Adaptivity Criteria in Intelligent and Adaptive Hypermedia e-Learning Systems

One of the main characteristics of Intelligent and Adaptive Hypermedia E-Learning Systems (IAHe-LS) are adaptivity criteria. Selecting adaptivity criteria is one of the main steps in developing a prototype of a System for Dynamic Generating of Learning Objects (SDGLO) that will support the individual personalised learning process. The selection of those criteria has a high impact on the quality of usage of those systems. This paper presents research into prioritisation of adaptivity criteria from the perspective of their usage and the selection of adaptivity criteria for creating the SDGLO prototype. The methods that were used in the research are: descriptive statistics, Cronbach Alpha, one-way ANOVA, and Analytic Hierarchy Process (AHP) with final qualitative analysis. In conclusion, for the development of a prototype of SDGLO, adaptivity criteria that are selected are learning style, cognitive style and learning objectives.

Role and Value of Learning Theories in the Area of Adaptive Educational Hypermedia Systems Incorporating Learning Styles

The purpose of this study was to investigate the pedagogical basis of Adaptive Educational Hypermedia Systems (AEHS) that incorporate Learning Styles concerning learning paradigms and learning theories through a meticulous review of the relevant published work. We investigated twenty (20) AEHS and analyze them comparatively to a variety of adaptivity determinants. Two are the pivotal points that are crucial in exploration of pedagogical approaches of these systems: the locus of control and the provided learning material. We conclude that these systems are based mostly on the learning paradigm of Cognitivism and Constructivism. In addition, we assume that the concept of learning theory is not such a narrow term, given that networked world imposes the concept of personal learning.

Emotion Recognition Using Multiple Kernel Learning toward E-learning Applications

Adaptive Educational Hypermedia (AEH) e-learning models aim to personalize educational content and learning resources based on the needs of an individual learner. The Adaptive Hypermedia Architecture (AHA) is a specific implementation of the AEH model that exploits the cognitive characteristics of learner feedback to adapt resources accordingly. However, beside cognitive feedback, the learning realm generally includes both the affective and emotional feedback of the learner, which is often neglected in the design of e-learning models. This article aims to explore the potential of utilizing affect or emotion recognition research in AEH models. The framework is referred to as Multiple Kernel Learning Decision Tree Weighted Kernel Alignment (MKLDT-WFA). The MKLDT-WFA has two merits over classical MKL. First, the WFA component only preserves the relevant kernel weights to reduce redundancy and improve the discrimination for emotion classes. Second, training via the decision tree reduces the misclassification issues associated with the SimpleMKL. The proposed work has been evaluated on different emotion datasets and the results confirm the good performances. Finally, the conceptual Emotion-based E-learning Model (EEM) with the proposed emotion recognition framework is proposed for future work.

A concept to simplify authoring of adaptive hypermedia eLearning structures

ABSTRACTAdaptive Learning Systems have been developed to improve learning success by increasing learner satisfaction, learning speed, and educational effectiveness. However, authoring adaptive eLearning structures is still a complicated task for lecturers, because they are unaccustomed to the way of thinking and to the workflows that are needed for the creation process. This paper describes a research project developing a concept that helps authors with the structure creation process, focussed on sequencing of content. Therefore, the issue was approached from the authors' perspective. First, storytelling theory has helped understand content structures and provided insights into how authors work. Second, by investigating the linear structure of learning content, information for sequencing could be extracted, providing the basis for an approach that is based on relations of different authors' content, and defining interdependencies that delinearise the content structure.

Intelligent Model Conception Proposal for Adaptive Hypermedia Systems

The context of this article is to study and propose solutions for the major problems of adaptive hypermedia systems. In fact, the works and models proposed for these systems are made according to the tradition of studying first theories and rules, then modeling and designing a system that implements them. As a result, adaptive hypermedia systems designed reflect and support only the elements and information that were studied during the design phase. Also, these systems require a huge amount of data to power their architecture in order to start operating. This famous problem is called “cold start” and until now represents a challenge. So, in this paper, we will propose an intelligent and flexible model inspired by human nature and that proposes a promising solution to these problems concerning hypermedia adaptive systems.

SMART Education Framework for Adaptation Content Presentation

The rapid growth of the Educational System (ES) has changed traditional learning behavior and presented a new situation to learners. To address the ever increasing needs and challenges associated with ES, a strategic methods and techniques of Adaptive Learning System (ALS) is adapted, which the primary objective is the adaptation of content, presentation, and navigation. In this paper, we suggest a new framework to adapt the Content Presentation to the preferences of learners and physical disability with learners who suffer from the visual and hearing limitations to stimulate the content. This framework is intended to be integrated in Dynamic Adaptive Hypermedia System (DAHS)in a manner that increases the learner’s perceived quality, high level of adaptivity and reliability.

A Critical and Comparative Study of Adaptive Hypermedia Technologies

Hypermedia systems give freedom of navigation to users but majority of these systems provide same view to all of them which cause lack of interest. Adaptive hypermedia technologies resolve this problem through personalisation. Adaptive hypermedia systems adapt to the users’ preferences and previous knowledge regarding one particular domain by maintaining user model. In this way, adaptation improves human computer interaction and leads users towards more relevant information. In this paper, the structure of adaptive hypermedia system (AHS) comprising of domain model, user model and adaptation model is described. Then types of user model and different methods and techniques used to implement adaptation mechanism are critically and comparatively discussed. Some future prospects are also highlighted.

The Role of Learner Characteristics in the Adaptive Educational Hypermedia Systems: The Case of the MATHEMA

The Role of Learner Characteristics in the Adaptive Educational Hypermedia Systems: The Case of the MATHEMA

Adaptive feedback in computer-based learning environments: a review

Adaptive support within a learning environment is useful because most learners have different personal characteristics such as prior knowledge, learning progress, and learning preferences. This study reviews various implementation of adaptive feedback, based on the four adaptation characteristics: means, target, goal, and strategy. This review focuses on 20 different implementations of feedback in a computer-based learning environment, ranging from multimedia web-based intelligent tutoring systems, dialog-based intelligent tutoring systems, web-based intelligent e-learning systems, adaptive hypermedia systems, and adaptive learning environment. The main objective of the review is to compare computer-based learning environments according to their implementation of feedback and to identify open research questions in adaptive feedback implementations. The review resulted in categorizing these feedback implementations based on the students’ information used for providing feedback, the aspect of the domain or pedagogical knowledge that is adapted to provide feedback based on the students’ characteristics, the pedagogical reason for providing feedback, and the steps taken to provide feedback with or without students’ participation. Other information such as the common adaptive feedback means, goals, and implementation techniques are identified. This review reveals a distinct relationship between the characteristics of feedback, features of adaptive feedback, and computer-based learning models. Other information such as the common adaptive feedback means, goals, implementation techniques, and open research questions are identified.

An adaptive hypermedia model based on student's lexicon

AbstractThis work presents an adaptive hypermedia proposal that focuses on the students' lexicon. An adequate lexicon knowledge affects dramatically in the learning processes in which the students are involved. In general, students manage a lexicon level that allows them to communicate. However, this is not enough for understanding specialized texts covering specific topics. Our proposal takes into account the interconnecting structures present in the lexicon associated to a student profile. More specifically, we propose a set of rules that, based on the student profile, facilitate the selection of the lexicon. We also provide a description of the different instances involved in the complete process.

Adaptive Educational Hypermedia Systems based on Learning Styles: the Case of Adaptation Rules

This paper investigates the pedagogical basis of Adaptive Educational Hypermedia Systems (AEHS) that incorporate Learning Styles in order to accommodate user's learning style preferences and needs. Therefore, AES adapt the learning content, its presentation and navigation to the user's learning style preferences. We collect thirty three (33) Adaptive and Intelligent Web-based Educational Systems (AIWBES) that incorporate learning styles and discuss twenty of them, namely the AEHS, as the remaining are Intelligent Tutorng Systems. The main achievement of this work is the investigation of AEHS' pedagogical basis in terms of adaptation rules. We conclude that these systems follow similar patterns in their adaptation logic.

Integration Strategy for the Realization of an Adaptive Hypermedia System of Natural Dyes

This work aims to develop a system allowing production, storage, management and dissemination of XML (eXtensible Markup Language) documents as well as chemical and analytical data (molecules, spectra, etc.) obtained within MED-COLOR-TECHNOLOGY project. Based on the study of user needs, modalities and systems for information access and retrieval, we have adopted a navigation system mode with the adaptive hypermedia systems. We have integrated and adapted the existing tools with new developed functionalities to ensure the full targeted functionality. Indeed, we have opted a component-based integration strategy using the plug-in mechanism and the Eclipse RCP (Rich Client Platform) framework. This architecture encompasses concepts that facilitate the adaptation of presentation, navigation, and content. Thus, the developed system is rich in functionality, extensible, portable, adaptable and evolves with user’s needs, preferences, and knowledge.

Integration Strategy for the Realization of an Adaptive Hypermedia System of Natural Dyes

This work aims to develop a system allowing production, storage, management and dissemination of XML (eXtensible Markup Language) documents as well as chemical and analytical data (molecules, spectra, etc.) obtained within MED-COLOR-TECHNOLOGY project. Based on the study of user needs, modalities and systems for information access and retrieval, we have adopted a navigation system mode with the adaptive hypermedia systems. We have integrated and adapted the existing tools with new developed functionalities to ensure the full targeted functionality. Indeed, we have opted a component-based integration strategy using the plug-in mechanism and the Eclipse RCP (Rich Client Platform) framework. This architecture encompasses concepts that facilitate the adaptation of presentation, navigation, and content. Thus, the developed system is rich in functionality, extensible, portable, adaptable and evolves with user’s needs, preferences, and knowledge.

Adaptive Social Learning Based on Crowdsourcing

Many techniques have been developed to enhance learning experience with computer technology. A particularly great influence of technology on learning came with the emergence of the web and adaptive educational hypermedia systems. While the web enables users to interact and collaborate with each other to create, organize, and share knowledge via user-generated content, majority of e-learning systems do not utilize the power of their users to create high quality educational content and provide data for adaptive algorithms. In this paper, we introduce a novel social learning framework that allows anybody to author educational content in a form of mini-lessons, learn lessons by following adaptive learning pathways as well as interact with their peers as in any social network. The proposed approach combines concepts of crowdsourcing, online social networks, and complex adaptive systems to engage users in efficient learning through teaching process. We first describe the main idea behind the framework and how users interact with it, and then we describe SALT system that implements the framework. We also performed evaluation of the SALT system via several classroom studies. Our results show that collective learning experiences can be efficiently utilized in adaptive social learning. We found that students tend to form stable clusters that survive very high similarity threshold. Meanwhile, our learning pathway analysis showed that almost all students have their own unique best pathway. Experiments with various recommendation algorithms showed that most algorithms obtain very small penalty in all classes.

Interview with Paul De Bra

Prof. dr. Paul De Bra is Full Professor in the Department of Computer Science at the Eindhoven University of Technology (TU/e). He holds a doctorate in mathematics and computer science from the University of Antwerp, Belgium (1987), with a thesis on Horizontal Decomposition in the Relational Database Model. During 1988 and 1989 he was a post-doctoral researcher at AT&T Bell Laboratories in Murray Hill, New Jersey, studying principles and technology for WYSIYWYG interfaces for document processing. Since December 1989 he has been working at the TU/e, first as an associate professor, and since August 1996 as a full professor and chair of the Information Systems group. Since he started working at the TU/e the research has shifted to the area of hypertext and hypermedia, with research in adaptive Web-based systems. He initiated and led the AHAM (reference model), AHA! and GRAPPLE projects on adaptive Technology-Enhanced Learning, the NWO CHIP project on adaptation and personalization in Cultural Heritage, and numerous other activities to stimulate research and development of adaptive hypermedia technology and applications. He is scientific director of the Dutch Research School for Information and Knowledge Systems and is president of User Modeling Inc. (the non-profit organization for User Modeling and Adaptive Systems). In "real" life Paul De Bra plays, repairs, composes and arranges for the accordion (and takes pictures at conferences too). "Paul De Bra" and "accordion" currently yields 76 hits on YouTube whereas "Paul De Bra" and "hypertext" yields 0. (On Google the hypertext query is more successful.)

ACM UMAP 2017 - User Modeling, Adaptation and Personalization

UMAP (User Modeling, Adaptation and Personalization) is the premier international conference for researchers and practitioners working on systems that adapt to individual users, to groups of users, and that collect, represent, and model user information. UMAP is the successor to the biennial User Modeling (UM) and Adaptive Hypermedia and Adaptive Web-based Systems (AH) conferences that were merged in 2009. It is sponsored by ACM SIGCHI and SIGWEB, and organized under the auspices of User Modeling Inc. The proceedings are published by ACM and will be part of the ACM Digital Library.

Protocol for a systematic review: 21st century adaptive teaching and individualized learning operationalized as specific blends of student‐centered instructional events: a systematic review and meta‐analysis

Protocol for a systematic review: 21st century adaptive teaching and individualized learning operationalized as specific blends of student‐centered instructional events: a systematic review and meta‐analysis

Educational Content Development Process in "CleverUniversity": Our Dynamic Adaptive Hypermedia Environment

The implementation of a simple and flexible dynamic adaptive hypermedia environment meets several needs of teachers. Using a fitting system, teachers will be able to share their knowledge in chunks of content in order to create quality teaching resources.
 In this paper, we propose a development approach through our simple system dedicated to teachers and learners alike taking into account the different work done on the subject. Moreover, our approach is based on the various elements of our system such as the learner’s model, the domain model, the pedagogical model, the courses generator and the multimedia database.
 Our focus in this paper will be on the domain model given its importance in the development and adaptation of educational content as needed, and which consists of finding educational content related to a given field of knowledge to be adapted for a particular learner.