Journal articles: 'Adaptive hypermedia'

1

De Bra, Paul, Peter Brusilovsky, and Geert-Jan Houben. "Adaptive hypermedia." ACM Computing Surveys 31, no. 4es (December 1999): 12. http://dx.doi.org/10.1145/345966.345996.

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Bailey, Christopher, Wendy Hall, David E. Millard, and Mark J. Weal. "Adaptive hypermedia through contextualized open hypermedia structures." ACM Transactions on Information Systems 25, no. 4 (October 2007): 16. http://dx.doi.org/10.1145/1281485.1281487.

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Tsandilas, T., and M. C. Schraefel. "Usable adaptive hypermedia systems." New Review of Hypermedia and Multimedia 10, no. 1 (June 2004): 5–29. http://dx.doi.org/10.1080/13614560410001728137.

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Brusilovsky, Peter, and Mark T. Maybury. "From adaptive hypermedia to the adaptive web." Communications of the ACM 45, no. 5 (May 2002): 30–33. http://dx.doi.org/10.1145/506218.506239.

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Jung, Hyosook, and Seongbin Park. "Authoring Adaptive Hypermedia using Ontologies." International Journal of Computers Communications & Control 7, no. 2 (September 20, 2014): 285. http://dx.doi.org/10.15837/ijccc.2012.2.1410.

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Federico, Pat-Anthony. "Hypermedia environments and adaptive instruction." Computers in Human Behavior 15, no. 6 (November 1999): 653–92. http://dx.doi.org/10.1016/s0747-5632(99)00044-8.

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Johnson, Andrew, and Farshad Fotouhi. "Adaptive clustering of hypermedia documents." Information Systems 21, no. 6 (September 1996): 459–73. http://dx.doi.org/10.1016/0306-4379(96)00023-3.

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Santoianni, Flavia, and Alessandro Ciasullo. "Adaptive Design for Educational Hypermedia Environments and Bio-Educational Adaptive Design for 3D Virtual Learning Environments." Research on Education and Media 10, no. 1 (June 1, 2018): 30–41. http://dx.doi.org/10.1515/rem-2018-0005.

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Abstract Adaptive learning environments design has been originally influenced by the adaptive learning environments model, which has been recently re-shaped by the bio-educational adaptive approach. Adaptive and bio-educational models share the common main idea that education should be adaptive. Since the 90’s the adoption of an adaptive educational point of view have been at the base of adaptive educational hypermedia systems, which design joins interest towards learners’ individual differences with adaptive learning environments research. Educational hypermedia systems have been overcome by the technology of 3D Virtual Learning Environments. Some emerging questions are related to the design criteria of adaptive learning environments. Which lessons learned from adaptive hypermedia systems design could be now applied to VLEs’ design? How a virtual learning environment should be designed to be adaptive? This research tries to answer to these questions by describing Federico 3DSU, an educational University 3D Virtual Learning Environment which has been designed with adaptive criteria, according to bio-educational model

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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 (July 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 achieve the main objectives, a case study was developed. An experiment between two groups of students was conducted to evaluate the impact on learning achievement. Inferential statistics were applied to make inferences from the sample data to more general conditions was designed to evaluate the new approach of matching learning materials with learning styles and their influence on student's learning achievement. The findings support the use of learning styles as guideline for adaptation into the adaptive e-learning hypermedia systems.

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KOBSA, ALFRED, JÜRGEN KOENEMANN, and WOLFGANG POHL. "Personalised hypermedia presentation techniques for improving online customer relationships." Knowledge Engineering Review 16, no. 2 (March 2001): 111–55. http://dx.doi.org/10.1017/s0269888901000108.

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This article gives a comprehensive overview of techniques for personalised hypermedia presentation. It describes the data about the computer user, the computer usage and the physical environment that can be taken into account when adapting hypermedia pages to the needs of the current user. Methods for acquiring these data, for representing them as models in formal systems and for making generalisations and predictions about the user based thereon are discussed. Different types of hypermedia adaptation to the individual user's needs are distinguished and recommendations for further research and applications given. While the focus of the article is on hypermedia adaptation for improving customer relationship management utilising the World Wide Web, many of the techniques and distinctions also apply to other types of personalised hypermedia applications within and outside the World Wide Web, like adaptive educational systems.

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Kahraman, H. Tolga, Seref Sagiroglu, and İlhami Colak. "A novel model for web-based adaptive educational hypermedia systems: SAHM (supervised adaptive hypermedia model)." Computer Applications in Engineering Education 21, no. 1 (July 1, 2010): 60–74. http://dx.doi.org/10.1002/cae.20451.

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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 (March 1, 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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Aggarwal, Arpita, and Naveen Kumar. "SAHAM: Shared Adaptive Hypermedia Application Model." International Journal of Computer Applications in Technology 40, no. 1/2 (2011): 138. http://dx.doi.org/10.1504/ijcat.2011.038561.

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De Bra, Paul. "Adaptive educational hypermedia on the web." Communications of the ACM 45, no. 5 (May 2002): 60–61. http://dx.doi.org/10.1145/506218.506247.

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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 (March 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 extend an existing decomposition model of adaptation in AH to incorporate summative evaluation of unobtrusive user modeling. Summative evaluation examines the effects or outcomes of a system, while formative evaluation is used to improve a system under development. We also introduce a separate, two-stage model for formative evaluation of unobtrusive user modeling. We then present results from a field study for the first of the two developmental stages and describe the current field study of the second developmental stage. Finally, we compare unobtrusive and transparent user modeling, and explain the role of each.

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Pagesy, R., G. Soula, and M. Fieschi. "Improving knowledge navigation with adaptive hypermedia." Medical Informatics and the Internet in Medicine 25, no. 1 (January 2000): 63–77. http://dx.doi.org/10.1080/146392300298256.

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Bra, Paul De, and Licia Calvi. "AHA! An open Adaptive Hypermedia Architecture." New Review of Hypermedia and Multimedia 4, no. 1 (January 1998): 115–39. http://dx.doi.org/10.1080/13614569808914698.

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DATTOLO, ANTONINA, and VINCENZO LOIA. "Active distributed framework for adaptive hypermedia." International Journal of Human-Computer Studies 46, no. 5 (May 1997): 605–26. http://dx.doi.org/10.1006/ijhc.1996.0114.

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Beaumont, Ian. "Workshop on adaptive hypertext and hypermedia." ACM SIGWEB Newsletter 4, no. 1 (March 1995): 23–24. http://dx.doi.org/10.1145/209842.209847.

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Brusilovsky, Peter. "Methods and techniques of adaptive hypermedia." User Modeling and User-Adapted Interaction 6, no. 2-3 (July 1996): 87–129. http://dx.doi.org/10.1007/bf00143964.

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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 (April 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. Finally, content that is to be presented to the learner is managed by a content generator module, depending on the model of the learner. Built on methods and techniques proposed for modeling and adaptation, the adaptive hypermedia system based on learning styles provides optimized adaptations. The authors' approach has been experimentally validated and the results are encouraging.

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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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Khan, Mohd Javed, and Khurram Mustafa. "Modelling adaptive hypermedia instructional system: a framework." Multimedia Tools and Applications 78, no. 11 (November 6, 2018): 14397–424. http://dx.doi.org/10.1007/s11042-018-6819-2.

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Chun, Sungkyu, Giho Jang, Hyosook Jung, Seung-Seok Kang, and Seongbin Park. "Adaptive Hypermedia Services Using Semantic Web Reasoning." Advanced Science Letters 22, no. 11 (November 1, 2016): 3279–83. http://dx.doi.org/10.1166/asl.2016.7881.

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Henze, Nicola, and Wolfgang Nejdl. "A logical characterization of adaptive educational hypermedia." New Review of Hypermedia and Multimedia 10, no. 1 (June 2004): 77–113. http://dx.doi.org/10.1080/13614560410001728128.

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De Bra, Paul, and Peter Brusilovsky. "Introduction to Special Issue on Adaptive Hypermedia." New Review of Hypermedia and Multimedia 15, no. 1 (April 2009): 1–3. http://dx.doi.org/10.1080/13614560902944168.

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Khan, Mohd Javed, and Khurram Mustafa. "Adaptive hypermedia instructional system (AHIS): A model." Education and Information Technologies 24, no. 6 (May 30, 2019): 3329–92. http://dx.doi.org/10.1007/s10639-019-09927-x.

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Höök, Kristina, Jussi Karlgren, Annika Wærn, Nils Dahlbäck, Carl Gustaf Jansson, Klas Karlgren, and Benoît Lemaire. "A glass box approach to adaptive hypermedia." User Modeling and User-Adapted Interaction 6, no. 2-3 (July 1996): 157–84. http://dx.doi.org/10.1007/bf00143966.

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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 (April 24, 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 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.

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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 (April 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 unexpected and unpredictable way. The authors' approach is based on the Felder Learning Styles Model and Hermann thinking styles model.

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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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Brusilovsky, Peter, and Paul De Bra. "The second workshop on adaptive hypertext and hypermedia." ACM SIGWEB Newsletter 7, no. 1-2 (February 1998): 29–32. http://dx.doi.org/10.1145/951171.951177.

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Hendrix, Maurice, Alexandra Cristea, and Wolfgang Nejdl. "Authoring adaptive educational hypermedia on the semantic desktop." International Journal of Learning Technology 3, no. 3 (2007): 230. http://dx.doi.org/10.1504/ijlt.2007.015443.

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Spallek, H. "Adaptive Hypermedia: A New Paradigm for Educational Software." Advances in Dental Research 17, no. 1 (December 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 learner-centered approach first considers the learning goal(s), then evaluates the user’s abilities and determines the individual learning style, to structure and tailor the curriculum most efficiently. The presented AH environment exploits various concepts of AH. The system collects data to create a model of the individual user, which is continuously refined based on test results throughout the course. The system then adapts the learning material dynamically, using active and passive curriculum sequencing and adaptive presentation.

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Micarelli, Alessandro, Filippo Sciarrone, and Fabio Gasparetti. "A Case-Based Approach to Adaptive Hypermedia Navigation." International Journal of Web-Based Learning and Teaching Technologies 4, no. 1 (January 2009): 35–53. http://dx.doi.org/10.4018/jwltt.2009010103.

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De Bra, Paul, Jill Freyne, and Shlomo Berkovsky. "Introduction to the Special Issue on Adaptive Hypermedia." New Review of Hypermedia and Multimedia 19, no. 2 (June 2013): 81–83. http://dx.doi.org/10.1080/13614568.2013.821320.

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Costaridou, L., G. Panayiotakis, N. Pallikarakis, and B. Proimos. "Radiographic skills learning: procedure simulation using adaptive hypermedia." British Journal of Radiology 69, no. 826 (October 1996): 938–45. http://dx.doi.org/10.1259/0007-1285-69-826-938.

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Chittaro, Luca, and Roberto Ranon. "Adaptive Hypermedia Techniques for 3D Educational Virtual Environments." IEEE Intelligent Systems 22, no. 4 (July 2007): 31–37. http://dx.doi.org/10.1109/mis.2007.63.

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Salcedo, Pedro, M. Angélica Pinninghoff, Ricardo Contreras, and Jorge F. Figueroa. "An adaptive hypermedia model based on student's lexicon." Expert Systems 34, no. 4 (July 10, 2017): e12222. http://dx.doi.org/10.1111/exsy.12222.

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Tarpin-Bernard, Franck, and Halima Habieb-Mammar. "Modeling Elementary Cognitive Abilities for Adaptive Hypermedia Presentation." User Modeling and User-Adapted Interaction 15, no. 5 (November 2005): 459–95. http://dx.doi.org/10.1007/s11257-005-2529-3.

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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 approach, focusing on an educational sector of adaptive hypermedia, to test out the effect of using Slicepedia, a service which enables the reuse and customisation of open corpus resources. An architecture and implementation of the system is presented along with two user-trial evaluations, involving 91 participants, which suggest that slicing techniques represent a valid content production supply for AHSs.

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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 (September 20, 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 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.

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Armani, Jacopo, and Andrea Rocci. "Conceptual maps in e-learning." Information Design Journal 11, no. 2-3 (December 31, 2003): 171–84. http://dx.doi.org/10.1075/idj.11.2.09arm.

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The paper presents a design strategy for e-learning hypermedia interfaces based on the notion of conceptual-navigational map. It proposes to analyze the cognitive and communication problems that arise in the use of hypermedia applications with specific goals, such as e-learning courseware modules, with the linguistic tools of pragmatics and discourse analysis, and shows how this can help in identifying specific communication problems related to the grounding and contextualization of new information, and how it can lead to new insights for design and to interfaces inspired by the linguistic means used in verbal communication to manage analogous problems. The implementation of such a design strategy in the SWISSLING courseware modules is discussed, and future directions of development towards context- aware adaptive hypermedia are briefly outlined.

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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 (July 1, 2020): 1–24. http://dx.doi.org/10.17220/mojet.2020.03.001.

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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 (October 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 styles and knowledge level. On one hand, the developed prototype will assist a learner in accessing and using learning resources which are adapted according to his/her personal characteristics (in this case his/her thinking style and level of knowledge). On the other hand, it will facilitate the learning content teacher in the creation of appropriate learning objects and their application to suitable pedagogical strategies.

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BAIG, FAWAD. "A Critical and Comparative Study of Adaptive Hypermedia Technologies." SINDH UNIVERSITY RESEARCH JOURNAL -SCIENCE SERIES 49, no. 004 (December 19, 2017): 689——692. http://dx.doi.org/10.26692/surj/2017.12.41.

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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 (August 2010): 199–205. http://dx.doi.org/10.3103/s0005105510040035.

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Abraham-Curto, Javier. "Contributions to Improve Online Learning Through Adaptive Hypermedia Techniques." Research Papers Faculty of Materials Science and Technology Slovak University of Technology 21, Special-Issue (June 1, 2013): 1–6. http://dx.doi.org/10.2478/rput-2013-0001.

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Abstract The personalization of learning through the automatic adaptation of the educational process, especially for the contents, is regarded as an important and necessary step for the improvement of education in the future. It is believed that through individualization get improved efficiency, increased speed and quality of learning for students and by automating the process, improved efficiency, better resource utilization, scalability of the process learning. To achieve this goal we have developed different strategies. One of them are looking for Adaptive Hypermedia Systems adjust all contents in a atuomática to the characteristics of each user.

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Sinclair, Patrick A. S., Kirk Martinez, David E. Millard, and Mark J. Weal. "Augmented reality as an interface to adaptive hypermedia systems." New Review of Hypermedia and Multimedia 9, no. 1 (January 2003): 117–36. http://dx.doi.org/10.1080/13614560410001725338.

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Aroyo, Lora, Paul De Bra, Geert-Jan Houben, and Richard Vdovjak. "Embedding information retrieval in adaptive hypermedia: IR meets AHA!" New Review of Hypermedia and Multimedia 10, no. 1 (June 2004): 53–76. http://dx.doi.org/10.1080/13614560410001728146.

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Journal articles on the topic 'Adaptive hypermedia'

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