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Journal articles on the topic 'Adaptive hypermedia system'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Sudomo, R. Irlanto, and Toni Setiawan. "Implementasi Adaptive Hypermedia System Berbasis Moodle untuk Mengatasi Keragaman Gaya Belajar Pada Pendidikan Vokasi." Joined Journal (Journal of Informatics Education) 2, no. 2 (2020): 71. http://dx.doi.org/10.31331/joined.v2i2.1009.

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Penelitian ini bertujuan untuk mendeskripsikan implementasi Adaptive Hypermedia System Berbasis Moodle dilihat dari aspek: (1) Keragaman Gaya Belajar siswa berupa Visual, Auditory Kinestetik (2) Perencanaan pembelajaran, (3) Pelaksanaan pembelajaran, (4) Sistem penilaian. Penelitian ini dilaksanakan menggunakan pendekatan deskriptif kualitatif. Penelitian yang dilakukan berupaya mendeskripsikan secara jelas mengenai implementasi Hypermedia System Berbasis Moodle di Universitas IVET. Subjek penelitian adalah sekretaris program studi Pendidikan Teknik Mesin konsentrasi Otomotif (PTM-O) dosen, pe

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Khan, Mohd Javed, and Khurram Mustafa. "Adaptive hypermedia instructional system (AHIS): A model." Education and Information Technologies 24, no. 6 (2019): 3329–92. http://dx.doi.org/10.1007/s10639-019-09927-x.

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Khan, Mohd Javed, and Khurram Mustafa. "Modelling adaptive hypermedia instructional system: a framework." Multimedia Tools and Applications 78, no. 11 (2018): 14397–424. http://dx.doi.org/10.1007/s11042-018-6819-2.

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Drissi, Samia, and Abdelkrim Amirat. "An Adaptive E-Learning System based on Student's Learning Styles." International Journal of Distance Education Technologies 14, no. 3 (2016): 34–51. http://dx.doi.org/10.4018/ijdet.2016070103.

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Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia. The main objective was to develop a new Adaptive Educational Hypermedia System based on Honey and Mumford learning style model (AEHS-H&M) and assess the effect of adapting educational materials individualized to the student's learning style. To a

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Hamza, Lamia, and Guiassa Yamina Tlili. "The Optimization by Using the Learning Styles in the Adaptive Hypermedia Applications." International Journal of Web-Based Learning and Teaching Technologies 13, no. 2 (2018): 16–31. http://dx.doi.org/10.4018/ijwltt.2018040102.

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This article addresses the learning style as a criterion for optimization of adaptive content in hypermedia applications. First, the authors present the different optimization approaches proposed in the area of adaptive hypermedia systems whose goal is to define the optimization problem in this type of system. Then, they present the architecture of their proposed system. The first step involves choosing a learning style model. The selection of this style is done by using a dedicated questionnaire answered by a learner. Then a modeling of the learner is completed based on his learning style. Fi

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Pham, D. T., and R. M. Setchi. "Case-based generation of adaptive product manuals." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 217, no. 3 (2003): 313–22. http://dx.doi.org/10.1243/095440503321590488.

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This paper presents an intelligent hypermedia product support system developed for the needs of a truck manufacturer that enables formalization of and learning from experience. Case-based reasoning (CBR) is employed to interpret a user's request for information, construct a new solution and adapt it to the user and his/her task. The proposed approach is illustrated with a case study that describes context-sensitive retrieval of hypermedia documents contained within an intelligent product manual.

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Vialardi, César, Javier Bravo, and Alvaro Ortigosa. "Improving AEH Courses through Log Analysis." JUCS - Journal of Universal Computer Science 14, no. (17) (2008): 2777–98. https://doi.org/10.3217/jucs-014-17-2777.

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Authoring in adaptive educational hypermedia environment is complex activity. In order to promote a wider application of this technology, the teachers and course designers need specific methods and tools for supporting their work. In that sense, data mining is a promising technology. In fact, data mining techniques have already been used in E-learning systems, but most of the times their application is oriented to provide better support to students; little work has been done for assisting adaptive hypermedia authors through data mining. In this paper we present a proposal for using data mining

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Berlanga, Adriana, and Francisco García-Peñalvo. "Learning Design in Adaptive Educational Hypermedia Systems." JUCS - Journal of Universal Computer Science 14, no. (22) (2008): 3627–47. https://doi.org/10.3217/jucs-014-22-3627.

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After more than ten years of research aiming at defining methods and techniques to deliver personalized instruction, Adaptive Educational Hypermedia Systems have not made the jump into real practice systems. Reasons for this include the complexity of their development, their use of exclusive methods for defining adaptivity and educational elements, and their lack of interoperation amongst courses and applications. A possible alternative to cope with these issues is using as a common notational method the IMS Learning Design specification. This paper attempts to bring AEHS and IMS LD closer to

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Hoi�-Bo�i�, Nata�a, and Vedran Mornar. "AHyCo: a Web-Based Adaptive Hypermedia Courseware System." Journal of Computing and Information Technology 13, no. 3 (2005): 165. http://dx.doi.org/10.2498/cit.2005.03.01.

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HOLZ, HILARY J., KATJA HOFMANN, and CATHERINE REED. "UNOBTRUSIVE USER MODELING FOR ADAPTIVE HYPERMEDIA." International Journal of Pattern Recognition and Artificial Intelligence 21, no. 02 (2007): 225–44. http://dx.doi.org/10.1142/s0218001407005430.

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We propose a technique for user modeling in Adaptive Hypermedia (AH) that is unobtrusive at both the level of observable behavior and that of cognition. Unobtrusive user modeling is complementary to transparent user modeling. Unobtrusive user modeling induces user models appropriate for Educational AH (EAH) based on metaphors characterized by a shared locus of control over learning, such as small group learning. Transparent user modeling, on the other hand, induces user models appropriate for EAH based on metaphors characterized by an independent locus of control, such as social navigation. We

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Omar ABDENNOUR, Hassane KEMOUSS, Mohamed ERRADI, and Mohamed KHALDI. "Design and development of a computer system adaptative for the management of the learner profile." World Journal of Advanced Engineering Technology and Sciences 6, no. 2 (2022): 038–52. http://dx.doi.org/10.30574/wjaets.2022.6.2.0081.

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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 mo

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Mahnane, Lamia, and Mohamed Hafidi. "Development and Testing of New E-Learning Hypermedia System." International Journal of Information Technology and Web Engineering 10, no. 2 (2015): 1–15. http://dx.doi.org/10.4018/ijitwe.2015040101.

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Adaptive E-learning Hypermedia Systems (AEHS) are an innovative approach to a web learning experience delivery. They try to solve main shortcomings of classical hypermedia e-learning applications: “one-size-fits-all” approach and “lost-in-hyperspace” phenomena by adapting the learning content and its presentation to needs, goals, thinking styles and learning styles of every individual learner. This paper outlines a new approach to automatically detect learner's thinking and learning styles, and taking into account that thinking and learning styles may change during the learning process in an u

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Kovalev, I. V., M. V. Karaseva, D. V. Kustov, and D. V. Stont. "A model of an adaptive XML-oriented hypermedia system." Automatic Documentation and Mathematical Linguistics 44, no. 4 (2010): 199–205. http://dx.doi.org/10.3103/s0005105510040035.

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Mahnane, Lamia, Laskri Mohamed Tayeb, and Philippe Trigano. "A Model for an Adaptive e-Learning Hypermedia System." International Journal of Information and Communication Technology Education 9, no. 4 (2013): 21–39. http://dx.doi.org/10.4018/ijicte.2013100102.

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Recent years have shown increasing awareness for the importance of adaptivity in e-learning. Since the learning style of each learner is different. Adaptive e-learning hypermedia system (AEHS) must fit different learner’s needs. A number of AEHS have been developed to support learning styles as a source for adaptation. However, these systems suffer from several problems, namely: lack of maintenance, adaptation to learning style, less attention was paid to thinking styles and the insertion of specific teaching strategies into learning content. This paper proposes an AEHS model based on thinking

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Boussakuk, Mohammed, Ahmed Bouchboua, Mohammed El Ghazi, Moulhime El Bekkali, and Mohammed Fattah. "Design of Computerized Adaptive Testing Module into Our Dynamic Adaptive Hypermedia System." International Journal of Emerging Technologies in Learning (iJET) 16, no. 18 (2021): 113. http://dx.doi.org/10.3991/ijet.v16i18.23841.

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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 implementat

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Merida, David, Ramon Fabregat, Carlos Arteaga, and Mario Cannataro. "MAS-SHAAD: a multiagent system proposal for an adaptive hypermedia system." International Journal of Continuing Engineering Education and Lifelong Learning 14, no. 4/5 (2004): 331. http://dx.doi.org/10.1504/ijceell.2004.005725.

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Klasnja-Milicevic, Aleksandra, Boban Vesin, Mirjana Ivanovic, and Zoran Budimac. "Integration of recommendations and adaptive hypermedia into java tutoring system." Computer Science and Information Systems 8, no. 1 (2011): 211–24. http://dx.doi.org/10.2298/csis090608021k.

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A way to improve the effectiveness in e-learning is to offer the personalized approach to the learner. Adaptive e-learning system needs to use different strategies and technologies to predict and recommend the most likely preferred options for further learning material. This can be achieved by recommending and adapting the appearance of hyperlinks or simply by recommending actions and recourses. This paper presents an idea for integration of such recommender system into existing web-based Java tutoring system in order to provide various adaptive programming courses.

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Özaydın Aydoğdu, Yıldız, and Nursel Yalçın. "A Web Based System Design for Creating Content in Adaptive Educational Hypermedia and Its Usability." Malaysian Online Journal of Educational Technology 8, no. 3 (2020): 1–24. http://dx.doi.org/10.17220/mojet.2020.03.001.

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Spallek, H. "Adaptive Hypermedia: A New Paradigm for Educational Software." Advances in Dental Research 17, no. 1 (2003): 38–42. http://dx.doi.org/10.1177/154407370301700110.

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Traditional online dental education courses follow the broadcast paradigm which centers on the teacher, not the student. This one-size-fits-all approach resembles a mass-production idea which cannot take individual learner characteristics into account. Most online course designs do not address the issue that users with different goals and knowledge may be interested in different pieces of information about a topic. Adaptive hypermedia (AH) is an emerging field in education research which investigates how computer systems can overcome this problem. AH can be applied to any course content. This

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Mohamed, Hafidi, and Bensebaa Taher. "Combining Expert Systems and Multiple Intelligences in an Adaptive and Intelligent Tutoring System." International Journal of Information Technology and Web Engineering 8, no. 3 (2013): 22–33. http://dx.doi.org/10.4018/ijitwe.2013070102.

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This paper describes an adaptive and intelligent tutoring system (AITS) based on multiple intelligences and expert system. Most of adaptive and intelligent tutoring systems based their adaptation to user’s skill level. Other learner features taken into account are background, hyperspace experience, preferences and interests. However, less attention was paid to multiple intelligences and their effects on learning. Moreover, to design AITS which can manage both different disciplinary domains and a guide for the learner is difficult. The specialization of the analysis treatments is responsible fo

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Qodad, Aymane, Abdelilah Benyoussef, Abdallah El Kenz, and Mourad Elyadari. "Toward an Adaptive Educational Hypermedia System (AEHS-JS) based on the Overlay Modeling and Felder and Silverman’s Learning Styles Model for Job Seekers." International Journal of Emerging Technologies in Learning (iJET) 15, no. 08 (2020): 235. http://dx.doi.org/10.3991/ijet.v15i08.10574.

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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 di

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Li, Xiaojie. "Adaptive Educational Hypermedia System Based on Variational Bayesian Petri Net." Mathematical Problems in Engineering 2022 (April 23, 2022): 1–7. http://dx.doi.org/10.1155/2022/6280816.

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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

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Höök, Kristina. "Evaluating the utility and usability of an adaptive hypermedia system." Knowledge-Based Systems 10, no. 5 (1998): 311–19. http://dx.doi.org/10.1016/s0950-7051(97)00034-8.

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SowmyashreeS, Shet N. Manas, DM Prashanth, P. A. Pramanth, and MS Raghunandana. "The Role of Adaptive AI in Skill Development:A Comprehensive Survey." International Journal of Innovative Science and Research Technology (IJISRT) 9, no. 12 (2024): 134–38. https://doi.org/10.5281/zenodo.14471771.

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E-learning systems facilitate accessible, flexible learning but often lack adaptive features tailored to individual student needs, leading to reduced effectiveness. Adaptive Intelligent Tutoring Systems (AITS) and Adaptive Hypermedia (AH) offer personalized support by monitoring student progress and adapting content and instruction. However, AITS excels in customized guidance, while AH generally provides technical resources without the same level of adaptation. The AI-Tutor system proposes integrating AITS and AH into an Adaptive Intelligent Tutoring System (AITS) to create a more effective e-

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Lamia, Mahnane, and Laskri Tayeb. "Discovering Learner Styles in Adaptive e-Learning Hypermedia Systems." JUCS - Journal of Universal Computer Science 19, no. (11) (2013): 1522–42. https://doi.org/10.3217/jucs-019-11-1522.

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A distinct feature of an adaptive e-learning hypermedia system (AEHS) is the learner model it employs, that is, a representation of information about an individual learner. Learner modeling and adaptation are strongly correlated, in the sense that the amount and nature of the information represented in the learner model depend largely on the kind of adaptation effect that the system has to deliver. In fact, we see a problem arising when teachers assume similar learning styles, thinking styles, levels of knowledge and abilities for learners. This is because learners that are less able will feel

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Levacher, Killian, Seamus Lawless, and Vincent Wade. "Slicepedia: Content-agnostic slicing resource production for adaptive hypermedia." Computer Science and Information Systems 11, no. 1 (2014): 393–417. http://dx.doi.org/10.2298/csis121223014l.

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The production of resources supporting the needs of Adaptive Hypermedia Systems (AHSs) is labor-intensive. As a result, content production is focused upon meeting the needs of resources with higher demand, which limits the extent to which numerous and diverse content requirements of AHSs can be met. Open Corpus Slicing attempts to convert the wealth of information available on the web, into customisable information objects. This approach could provide the basis of an open corpus supply service meeting more diverse and unpredictable content requirements of AHSs. This paper takes a case study ap

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Stash, Natalia. "Incorporating cognitive/learning styles in a general-purpose adaptive hypermedia system." ACM SIGWEB Newsletter 2007, Winter (2007): 3. http://dx.doi.org/10.1145/1324960.1324963.

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Medina-Medina, N., F. Molina-Ortiz, and L. Garcia-Cabrera. "Diversity of structures and adaptive methods on an evolutionary hypermedia system." IEE Proceedings - Software 152, no. 3 (2005): 119. http://dx.doi.org/10.1049/ip-sen:20050026.

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Papadimitriou, Alexandros, Maria Grigoriadou, and Georgios Gyftodimos. "Interactive Problem Solving Support in the Adaptive Educational Hypermedia System MATHEMA." IEEE Transactions on Learning Technologies 2, no. 2 (2009): 93–106. http://dx.doi.org/10.1109/tlt.2009.19.

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Ray, Roger D. "MediaMatrix: An authoring system for adaptive hypermedia teaching — Learning resource libraries." Journal of Computing in Higher Education 7, no. 1 (1995): 44–68. http://dx.doi.org/10.1007/bf02946142.

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Chopra, Aditya, Devang Negandhi, Soumith Chintala, A. Kannammal, N. Ch Sriman Narayana Iyengar, and V. Ramachandran. "Frame based Intelligent Tutoring System with weighted attributes and adaptive hypermedia." International Journal of Electronic Business 8, no. 4/5 (2010): 342. http://dx.doi.org/10.1504/ijeb.2010.035291.

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Gil, Ana-Belén, Raquel Rodríguez, Francisco García-Peñalvo, and Ricardo López. "SHARP Online: An Adaptive Hypermedia System Applied to Mathematical Problem Solving." JUCS - Journal of Universal Computer Science 14, no. (19) (2008): 3099–113. https://doi.org/10.3217/jucs-014-19-3099.

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In this article we present the development of a web application called SHARP Online: An Adaptive Hypermedia System Applied to Mathematical Problem Solving. The pedagogical basis of this application is found in the support techniques for heuristic learning in mathematical problem solving developed according to the Schoenfeld model. The adaptivity of this tool is achieved by way of the utilization of an adaptive algorithm which has been developed for it and is described in this article. This algorithm implements mechanisms that make it possible for the user to construct mathematical knowledge ad

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Zhao, Xing. "Mobile English Teaching System Based on Adaptive Algorithm." International Journal of Emerging Technologies in Learning (iJET) 13, no. 08 (2018): 64. http://dx.doi.org/10.3991/ijet.v13i08.9057.

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To improve the students’ individualized and autonomous learning ability in English teaching, a mobile English learning system is designed on the basis of adaptive algorithm. The students’ need for the adaptive mobile English teaching system is analyzed through researches on students and questionnaires. According to the needs analysis, the main functional modules of the adaptive mobile English learning system are designed, including the creation module, personalized learning module, evaluation and feedback module, and management module. Then, the improved XAHM (XML adaptive hypermedia model) is

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Ikram, Chelliq, Anoir Lamya, Erradi Mohamed, and Khaldi Mohamed. "Model for motivating learners with personalized learning objects in a hypermedia adaptive learning system." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 2 (2024): 1282. http://dx.doi.org/10.11591/ijai.v13.i2.pp1282-1293.

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<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 period

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Chelliq, Ikram, Lamya Anoir, Mohamed Erradi, and Mohamed Khaldi. "Model for motivating learners with personalized learning objects in a hypermedia adaptive learning system." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 2 (2024): 1282–93. https://doi.org/10.11591/ijai.v13.i2.pp1282-1293.

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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 ensur

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Bachov, I. "THE USE OF ADAPTIVE AND INTELLECTUAL EDUCATIONAL TECHNOLOGIES IN PREPARING OF MODERN SPECIALISTS." Visnyk Taras Shevchenko National University of Kyiv. Military-Special Sciences, no. 1 (2019): 15–18. http://dx.doi.org/10.17721/1728-2217.2019.41.15-18.

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In the development of educational software, there are ongoing dynamic changes that affect the market of educational services on the Internet. The current state of the distance education system requires the latest educational technology to effectively meet the needs of students who study virtually.The article defines how intelligent systems are used in the training of modern specialists through the system of distance learning.Key words: educational systems, intellectual systems, student, internet, hypermedia.

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Medina-Medina, Nuria, and Lina García-Cabrera. "A taxonomy for user models in adaptive systems: special considerations for learning environments." Knowledge Engineering Review 31, no. 2 (2016): 124–41. http://dx.doi.org/10.1017/s0269888916000035.

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AbstractThis paper outlines the educational advantages provided by adaptive systems and stresses the importance of the user model in the task of adaptation. The paper also establishes a general taxonomy of user models thereby enabling classification of any model according to various features related to its structure and management. This taxonomy allows an exhaustive description of all user models, facilitating analysis and design of the corresponding adaptive systems. Subsequently, the taxonomy is used to describe the user modeling process in a concrete adaptive hypermedia system and to analyz

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Bouchboua, Ahmed, Rabah Ouremchi, and Mohammed El ghazi. "Educational Content Development Process in "CleverUniversity": Our Dynamic Adaptive Hypermedia Environment." International Journal of Emerging Technologies in Learning (iJET) 11, no. 12 (2016): 14. http://dx.doi.org/10.3991/ijet.v11i12.5868.

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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

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Hijikata, Yoshinori, Tetsuya Yoshida, and Shogo Nishida. "Adaptive Hypermedia System for Supporting Information Providers to Direct Users through Hyperspace." IEEJ Transactions on Electronics, Information and Systems 120, no. 11 (2000): 1720–31. http://dx.doi.org/10.1541/ieejeiss1987.120.11_1720.

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BOUSSAKUK, Mohammed. "A Fully individualized Adaptive and Intelligent Educational Hypermedia System: Details of CleverUniversity." International Journal of Emerging Trends in Engineering Research 8, no. 5 (2020): 1497–502. http://dx.doi.org/10.30534/ijeter/2020/04852020.

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Yoosooka, Burasakorn, and Vilas Wuwongse. "An Adaptive System for Retrieval and Composition of Learning Objects." International Journal of Systems and Service-Oriented Engineering 2, no. 4 (2011): 42–59. http://dx.doi.org/10.4018/jssoe.2011100103.

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This paper proposes a new approach to automatic retrieval and composition of Learning Objects (LOs) in an Adaptive Educational Hypermedia System (AEHS) using multidimensional learner characteristics to enhance learning effectiveness. The approach focuses on adaptive techniques in four components of AEHS: Learning Paths, LO Retrieval, LO Sequencing, and Examination Difficulty Levels. This approach has been designed to enable the adaptation of rules to become generic. Hence, the application to various domains is possible. The approach dynamically selects, sequences, and composes LOs into an indi

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Tmimi, Mehdi, Mohamed Benslimane, Mohammed Berrada, and Kamar Ouazzani. "Implemented and Tested Conception Proposal of Adaptation Model for Adaptive Hypermedia." International Journal of Emerging Technologies in Learning (iJET) 14, no. 02 (2019): 16. http://dx.doi.org/10.3991/ijet.v14i02.8230.

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This article is a continuation of our work concerning the development of the adaptive hypermedia; and precisely the adaptation model.  In a previous work we proposed both new Conception of the Learner Model and an Intelligent and Dynamic System Supporting Learner Ontologies. The main purpose of this article is to present our own model of adaptation that has the capacity to be implemented and that responds to all the remarks and shortcomings of the existing adaptation models while showing implementations and tests (technically) that we have developed

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Mwambe, Othmar Othmar, Phan Xuan Tan, and Eiji Kamioka. "Bioinformatics-Based Adaptive System towards Real-Time Dynamic E-learning Content Personalization." Education Sciences 10, no. 2 (2020): 42. http://dx.doi.org/10.3390/educsci10020042.

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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 cha

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Wilson, Chunyu, and Bernard Scott. "Adaptive systems in education: a review and conceptual unification." International Journal of Information and Learning Technology 34, no. 1 (2017): 2–19. http://dx.doi.org/10.1108/ijilt-09-2016-0040.

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Purpose 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. Design/methodology/approach 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. Findings Similarities and differences between the two kinds of system are highlighted. A conceptual unification is proposed based on the architecture of Course Assembly

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Ghauth, Khairil Imran, and Nor Aniza Abdullah. "An Empirical Evaluation Of Learner Performance In E-Learning Recommender Systems And An Adaptive Hypermedia System." Malaysian Journal of Computer Science 23, no. 3 (2010): 141–52. http://dx.doi.org/10.22452/mjcs.vol23no3.1.

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Hockemeyer, Cord, Owen Conlan, Vincent Wade, and Dietrich Albert. "Applying Competence Prerequisite Structures for eLearning and Skill Management." JUCS - Journal of Universal Computer Science 9, no. (12) (2003): 1428–36. https://doi.org/10.3217/jucs-009-12-1428.

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Several approaches for formalising prerequisite structures on skills or competencies based on the psychological theory of knowledge space have been suggested and applied for adaptive eLearning. In this paper, we will discuss how these structures may be applied in skill management in a broader sense. After introducing some formal structures for prerequisite relationships between competencies, we will briefly present an example of an adaptive eLearning system based on this approach (APeLS). Several other aspects of the system which promise to be useful for advanced skill management are discussed

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Papadimitriou, Alexandros, Maria Grigoriadou, and Georgios Gyftodimos. "A Web-based Learner-Controlled Adaptive Group Formation Technique." International Journal of e-Collaboration 10, no. 1 (2014): 14–34. http://dx.doi.org/10.4018/ijec.2014010102.

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This paper presents the learner-controlled adaptive group formation technique offered by the web-based adaptive educational hypermedia system MATHEMA. More specifically, this paper describes why we take into consideration the group effectiveness, concerning the concrete-abstract dimension of learners' learning style, in forming learner groups and how the adaptive group formation algorithm generates a priority list of possible matching candidate collaborators for a certain student, taking into account the abstract or concrete dimension of his/her learning style and his/her possible candidate co

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Sumarlin, Sumarlin, Punaji Setyosari, Saida Ulfa, and Made Dunanda Kartika Degeng. "Improvement of engineering student’s learning outcomes in high schools using adaptive educational hypermedia system." International Journal of Evaluation and Research in Education (IJERE) 13, no. 5 (2024): 2925. http://dx.doi.org/10.11591/ijere.v13i5.28381.

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<span lang="EN-US">This was a research and development (R&amp;D) which aims to develop adaptive educational hypermedia system (AEHS) learning media. The use of AEHS based on learning style in supporting the online learning process is considered very effective for use by engineering students because it can be accessed via mobile devices which can make it easier for students to learn and has an effect on increasing learning outcomes, this is supported by several inputs from experts through expert learning design tests, learning instrument experts, learning media experts and learning ou

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Jeong, Hwa-Young. "UX based adaptive e-learning hypermedia system (U-AEHS): an integrative user model approach." Multimedia Tools and Applications 75, no. 21 (2016): 13193–209. http://dx.doi.org/10.1007/s11042-016-3292-7.

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Sumarlin, Punaji Setyosari, Saida Ulfa, and Made Duananda Kartika Degeng. "Improvement of engineering student's learning outcomes in high schools using adaptive educational hypermedia system." International Journal of Evaluation and Research in Education (IJERE) 13, no. 5 (2024): 2925–35. https://doi.org/10.11591/ijere.v13i5.28381.

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Abstract:

This was a research and development (R&D) which aims to develop adaptive educational hypermedia system (AEHS) learning media. The use of AEHS based on learning style in supporting the online learning process is considered very effective for use by engineering students because it can be accessed via mobile devices which can make it easier for students to learn and has an effect on increasing learning outcomes, this is supported by several inputs from experts through expert learning design tests, learning instrument experts, learning media experts and learning outcome measurement experts wit

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