Adaptive Hypermedia Research Articles

Modeling and supporting adaptive Complex Data-Intensive Web Systems via XML and the O-O paradigm: The OO-XAHM model

The data model is a critical component of an Adaptive Web System (AWS). The major goals of such a data model are describing the application domain of the AWS and capturing data about the user in order to support the “adaptation effect”. There have been many proposals for data models, principally based on knowledge representation, machine learning, logic and reasoning, and, recently, ontologies. These models are focused on the implementation of the core layer of AWS, that is realizing the adaptation of contents and presentations of the system, but sometimes they are poor with respect to the application domain design. In this paper, we present an extension of the state-of-the-art XML Adaptive Hypermedia Model (XAHM), Object-Oriented XAHM (OO-XAHM) that supports the application domain modeling using an object-oriented approach. We also provide the formal definition of the model, its description via Unified Modeling Language (UML), and its implementation using XML Schema. Finally, we provide a complete case study that focuses the attention on the well-known Italian archaeological site Pompeii.

Model for motivating learners with personalized learning objects in a hypermedia adaptive learning system

<span lang="EN-US">A number of weaknesses were demonstrated in the E-learning platforms during the Covid-19 pandemic despite the efforts invested. This has negatively influenced learners' motivation and consequently their performance. With the proliferation of technology and the revolution of information and communication technologies (ICT), learning objects have become new epitomes widely used, accessible, and implemented with educational resources and technological support. The integration of learning objects into E-learning has enhanced educational progress, but during critical periods, it is crucial to ensure pedagogical continuity and learner motivation. Based on this observation, we will propose architecture of a personalized learning object model in the context of an adaptive hypermedia learning system (AHS). The objective of our model is to increase the motivation factor which is a determining element in the success of E-learning, our model aims to improve the performance of the learners in order to avoid the abounding of learning and to promote the attendance of the learners. This will be useful later for any design or development of learning objects in hypermedia learning systems that are adaptive to the needs of the learners and in line with their preferences and profiles throughout the learning process offered by the system. </span>

Enhancing Adaptive Pedagogical Content Development with ADDIE and Scrum in Hypermedia Environments

This article explores an innovative approach that combines the ADDIE and Scrum methodologies to develop pedagogical objects in adaptive hypermedia systems. The aim is to address the evolving needs of learners in a constantly changing learning environment. This integration provides increased flexibility, allowing for quick adjustments based on learners' requirements. It also promotes multidisciplinary collaboration, enhances pedagogical quality through regular reviews, maintains alignment with educational objectives, and ensures transparent quality management. The article presents an architecture tailored to this approach, highlighting key components to promote adaptability. It discusses future prospects for the implementation of this approach, including automation and the integration of artificial intelligence, thus opening up new possibilities for continuous improvement in adaptive education and learning.

Design of an adaptive hypermedia system to strengthen algebra learning skills of high school students

The national and international parameters of educational evaluation have provided a frame of reference to analyze and compare the performance of the students, however, in Mexico these results show a low educational level. Therefore, it is important to implement tools to reduce educational deficiencies. The objective of this work is to develop an Adaptive Hypermedia System (SHA), which considers the individual characteristics of students in order to adapt and present content based on competencies, for the development of algebra skills. This research project was carried out in three phases: Phase 1. The Protocol Test was applied to identify the academic entry profile of 185 high school students who were studying algebra. Phase 2. The learning strategies contained in the SHA were designed, taking into account two key approaches: research-action-development and the ESEAC scale. Finally, in Phase 3, the SHA was used as support for students who presented low performance in the subject of algebra that they are currently studying in their high school training, and thus determine the impact and effectiveness of this system.

A comparative study of characteristics and preferences to learner models in educational adaptive hypermedia systems

Educational adaptive hypermedia systems are online learning systems that aim to tailor the learning experience to the characteristics and needs of individual learners. These systems use a variety of techniques, including data analysis, machine learning, and dynamic adaptive user interface, to provide more effective and personalized learning for each learner. The learner models in their systems are designed to help them better understand the learner and tailor their learning experience, to do this their models take into account the characteristics of the learner, such as their learning style, education level, prior knowledge and learning goals. Our work consists in making a comparative study of its models at the functional level and characteristics in the educational adaptive hypermedia systems in order to conclude the most effective learner model that can help to improve the academic results and to make online learning more accessible and effective for all learners, the results prove that the model based on learning styles allows a better adaptation in the educational adaptive hypermedia systems, its development will be devoted to the work of the next article.

A comparative study of characteristics and preferences to learner models in educational adaptive hypermedia systems

A comparative study of characteristics and preferences to learner models in educational adaptive hypermedia systems

Improving Students' Critical Thinking Ability with Enhanced-Open Learning Approach Using Adaptive Hypermedia

The Critical thinking is important in education because it encourages students to gain an understanding of more complex information. High critical thinking skills will lead students to find and conclude their understanding. The prolonged COVID-19 pandemic has made global changes in the implementation of learning. Until now, the learning process is still directed at the online learning model with the help of various Learning Management System (LMS) platforms. Conditions like this have implications for the decline in students' critical thinking skills in various aspects, such as inference, interpretation, explanation, analysis, evaluation, and self-regulation. This study aims at proposing an alternative learning approach, namely the enhanced-open learning model which is used to empower and improve students' critical thinking skills. This learning model was developed using the Research and Development (R&D) method and implemented with an adaptive hypermedia learning application media designed with the Luther development model. The sampling technique used was cluster random sampling on 98 students of informatics education in Surakarta City. The data were analyzed with the prerequisites for normality and homogeneity of the data before the Wilcoxon Signed Rank Test and Mann Whitney U test was carried out to determine the effectiveness of the model. The results of the increase in the gain score obtained from the experiment are in the aspect of interpretation of 93.18%, inference 76.74%, explanation 96.33%, analysis 97, 87%, evaluation 63.01%, and self-regulation 98.13%. Based on the experiments conducted, it is proven that the adaptive open learning approach has a very significant impact on improving students' critical thinking aspects so that it can be concluded that the model is effective in improving students' critical thinking skills.

Design and development of a computer system adaptative for the management of the learner profile

In the educational context, an adaptive hypermedia will make it possible to better guide the learner in his learning, to offer him courses and educational content that are adapted and personalized, and to take into account his learning profile. The idea developed in this article lies in the design and management of a valid learner model for all adaptive hypermedia systems (adaptive, macro-adaptive e-learning, ITS, AHES). Through this work, we first offer an overview of the learner profile by citing the difference between the model and the profile of a learner. Next, we deal with the learner model in adaptive systems by identifying the different systems. Then, we process learner modeling based on learner model content, specific information domain, and independent information domain and learner model components. Finally, we propose the process of developing a learner model: Steps and techniques especially data collection, learner model initialization and learner model update.

Öğrencilerin Hiper Ortamlarında İkili Kodlamaya Yönelik Algıları: Dinleme Metinleri, Anahtar Kelimeler, Görseller ve Altyazılar

This study investigated 57 participants’ (N= 57) perceptions towards dual-coding in design of audio-only listening texts (i.e. re-provision of the same audio-only listening texts in the form of audio-only listening texts + keywords or supplementary contextual visuals + keywords at non-initial phases of the while-listening stage, and audio-only listening texts + (full) captions at final listening stage) in adaptable hypermedia environments (HEs) for foreign language learning (FLL). The study also aimed to find out whether there were any differences between their perceptions in terms of participants’ characteristics as well as between their perceptions towards dual-coding. The study was both quantitative and qualitative in nature. The results of the quantitative data were analysed with SPSS (i.e. Mean, Std. Deviation, ANOVA, Pearson Correlation Test). The results revealed that the participants were overwhelmingly in favour of the use of dual-coding in design of audio-only listening texts in HEs for FLL. The majority believed that not only did the dual-coding in design of audio-only listening texts benefit them in different ways, but it also contributed to the enhancement of their learning. Moreover, the results of the quantitative data revealed that there were some significant differences between the participants’ perceptions.

Adaptive Educational Hypermedia System Based on Variational Bayesian Petri Net

The traditional teaching model fails to support the modern requirements, which seek to support the diversity of each student in terms of skills, inclinations, and educational level. The adaptive educational hypermedia systems are a learning model that is both adaptive and personalized, and it is gaining popularity (AEHSs). These tools can be used by students to present, navigate, provide feedback, and assess. However, even in these systems, internal differentiation should include a wide range of practices, personalized forms of learning process organization, and high-quality education, taking into account each students’ diverse educational needs and capabilities, interests, unique experiences, personal rhythms of integration of educational functions, and personal learning style. So, the learning style, the cognitive background, and the student’s interest are decisive factors for the structure of a next-generation learning system. To overcome the issues of the traditional learning systems, this paper proposes an AEHS based on Variational Bayesian Petri Net (VBPNet). It is an intelligent system that can, by overcoming the significant limitations of the Petri Nets, depict any complex procedure with great precision and without considerable computing power requirements. The proposed VBPNet was used as an AEHS implementation algorithm to classify students based on their skills and real educational needs.

Design of Computerized Adaptive Testing Module into Our Dynamic Adaptive Hypermedia System

By the end of the 20th century, the most common and traditional paper and pencil tests (PBT) were faced with an increasing set of difficulties and drawbacks. Proceed and meet the measurement and evaluation needs of the 21st century; it is mandatory to have radical and qualitative changes. The accelerating pace of technological innovation in Education shows a clear path to computer-based testing, which offers a more engaging and innovative testing environment, as well as the ability to obtain instant results and feedback, the use of dynamic, multimedia learning objects (LO), and the implementation of adaptive, individualized assessment approaches. In this sense, this paper presents an adaptive formative assessment framework in which test adaptation is based on multiple criteria. The presented system bases its adaptation on the test takers' proficiency, schemata, desirable learning goal, cognitive level, and learning style. The main objective of this paper is to discuss the value of the adaptive testing system. Therefore, it presents the design and implementation of the system and the adaptive rules employed.

Design of educational scenarios of activities in a learning situation for online teaching

Through this work, based on research works concerning e-learning in particular works dealing with e_learning project management systems, adaptive hypermedia systems and decision-making systems on the one hand. Work on the impact of project-based learning on self-regulation in teaching and the design of pedagogical scenarios for classical education and in particular for modular online education on the other hand. Our work concerns the design and scripting of a modular online education by proposing different possible scenarios according to the nature of the learning or assessment activities linked to a learning situation without taking into account the nature of the discipline and the nature of the concept to be addressed.

Enhancing the prediction of student performance based on the machine learning XGBoost algorithm

ABSTRACT Performance Factors Analysis (PFA) is considered one of the most important Knowledge Tracing (KT) approaches used for constructing adaptive educational hypermedia systems. It has shown a high prediction accuracy against many other KT approaches. While, the desire to estimate more accurately the student level leads researchers to enhance PFA by inventing several advanced extensions. However, most of the proposed extensions have exclusively been improved in a pedagogical sense, as the improvements have mostly been limited to the analysis of students’ behaviour during their learning process. In contrast, Machine Learning provides many powerful methods that could be efficient to enhance, in the technical sense, the prediction of student performance. Our goal is to focus on the exploitation of Ensemble Learning methods as an extremely effective Machine Learning paradigm used to create many advanced solutions in several fields. In this sense, we propose a new PFA approach based on different models (Random Forest, AdaBoost, and XGBoost) in order to increase the predictive accuracy of student performance. Our models have been evaluated on three different datasets. The experimental results show that the scalable XGBoost has outperformed the other evaluated models and substantially improved the performance prediction compared to the original PFA algorithm.

Endogenous Eye Blinking Rate to Support Human–Automation Interaction for E-Learning Multimedia Content Specification

As intelligent systems demand for human–automation interaction increases, the need for learners’ cognitive traits adaptation in adaptive educational hypermedia systems (AEHS) has dramatically increased. AEHS utilize learners’ cognitive processes to attain fair human–automation interaction for their adaptive processes. However, obtaining accurate cognitive trait for the AEHS adaptation process has been a challenge due to the fact that it is difficult to determine what extent such traits can comprehend system functionalities. Hence, this study has explored correlation among learners’ pupil size dilation, learners’ reading time and endogenous blinking rate when using AEHS so as to enable cognitive load estimation in support of AEHS adaptive process. An eye-tracking sensor was used and the study found correlation among learners’ pupil size dilation, reading time and learners’ endogenous blinking rate. Thus, the results show that endogenous blinking rate, pupil size and reading time are not only AEHS reliable parameters for cognitive load measurement but can also support human–automation interaction at large.

AwARE: a framework for adaptive recommendation of educational resources

Recommender systems appeared in the early 90s to help users deal with cognitive overload brought by the internet. From there to now, such systems have assumed many other roles like help users to explore, improve decision making, or even entertain. The system needs to look to user characteristics to accomplish such new goals. These characteristics help understand what the user task is and how to adapt the recommendation to support such task. Related research has proposed recommender systems in education. These recommender systems help learners to find the educational resources most fit for their needs. In this paper, we present an integration model between recommender and adaptive hypermedia systems. It results in a new process for educational resource recommendation, using a new algorithm of adaptive recommendation. Through a prototype and an online experiment on the educational scenario, we proved that AwARE could improve the recommendation accuracy, interaction with the system, and user satisfaction. Besides the prototype description, the paper presents a protocol to evaluate the proposed approach by both the providers’ and consumers’ point of view.

A Web Based System Design for Creating Content in Adaptive Educational Hypermedia and Its Usability

Adaptive educational hypermedia is an environment that offers an individualized learning environment according to the characteristics, knowledge and purpose of the students. In general, adaptive educational hypermedia, a user model is created based on user characteristics and adaptations are made in terms of text, content or presentation according to the created user model. Different contents according to the user model are shown as much as user model creation in adaptive educational hypermedia. The development of applications that allow the creation of adaptive content according to the features specified in the user model has great importance in ensuring the use of adaptive educational hypermedia in different contexts. The purpose of this research is to develop a web-based application for creating content in adaptive educational hypermedia and to examine the usability of the developed application. In order to examine the usability of the application developed in the scope of the study, a field expert opinion form was developed and opinions were asked about the usability of the application from 7 different field experts. As the result of the opinions, it has been seen that the application developed has a high usability level. In addition, based on domain expert recommendations, system revisions were made and the system was published at www.adaptivecontentdevelopment.com.

A Proposed Conception of the domain Model for Adaptive Hypermedia

A Proposed Conception of the domain Model for Adaptive Hypermedia

Toward an Adaptive Educational Hypermedia System (AEHS-JS) based on the Overlay Modeling and Felder and Silverman’s Learning Styles Model for Job Seekers

In this paper we introduce a new design of an adaptive educational hypermedia system for job seekers, this proposal is based, for the part of learning objectives, on a job model which allows adapting the content and the path of education to the intended jobs, and, for the learner model construction, on a specific use of the learning styles of Felder and Silverman.
 First, we present existing literature to give a general review on adaptive edu-cational hypermedia systems, in that way; we have reported the related items to different notions in the adaptive educational Systems area as the differentiated pedagogy, the learning objects, and the learner profile. Then we argued our choice of the components of our model and we detailed the new ones.
 As designed, the model can produce a suitable learning path for the user to match the job characteristics and the learning style of the person in order to help the user owning the job sought. With the possibility of linking the required com-petencies to the education skills, we aim to map business tasks to learning activi-ties. 
 Based on this approach, we designed an Adaptive Educational Hypermedia System named AEHS-JS that will help to improve the efficiency and pragmatism of job search activities. 
 In plus of the social impact of this work as it help job seekers to complete their profiles and get the career they are looking for, this work will allow companies to find the candidates that match the job criteria sought.

Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content Personalization

Adaptive Educational Hypermedia Systems (AEHS) play a crucial role in supporting adaptive learning and immensely outperform learner-control based systems. AEHS’ page indexing and hyperspace rely mostly on navigation supports which provide the learners with a user-friendly interactive learning environment. Such AEHS features provide the systems with a unique ability to adapt learners’ preferences. However, obtaining timely and accurate information for their adaptive decision-making process is still a challenge due to the dynamic understanding of individual learner. This causes a spontaneous changing of learners’ learning styles that makes hard for system developers to integrate learning objects with learning styles on real-time basis. Thus, in previous research studies, multiple levels navigation supports have been applied to solve this problem. However, this approach destroys their learning motivation because of imposing time and work overload on learners. To address such a challenge, this study proposes a bioinformatics-based adaptive navigation support that was initiated by the alternation of learners’ motivation states on a real-time basis. EyeTracking sensor and adaptive time-locked Learning Objects (LOs) were used. Hence, learners’ pupil size dilation and reading and reaction time were used for the adaption process and evaluation. The results show that the proposed approach improved the AEHS adaptive process and increased learners’ performance up to 78%.

ВОПРОСЫ АДАПТИВНОСТИ В СИСТЕМАХ ДИСТАНЦИОННОГО ОБУЧЕНИЯ

This paper considers the problems of adaptivity realization in intelligent e-learning tutoring systems, based on adaptive hypermedia technologies and individual learning styles models.