Metadoc: An Adaptive Hypertext Reading System

Boyle, Craig D. B.; Encarnacion, Antonio O.

doi:10.1007/978-94-017-0617-9_3

Cited by 67 publications

(24 citation statements)

References 6 publications

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“…We integrate these adaptation levels in terms of learner context parameters, models of e-learning and LOs processes (as we discussed earlier) such as LO_design, LO_sequencing, LO_composition, LO_presentation and LO_evolution. Content level adaptation is the most studied way of hypermedia adaptation (Beaumont 1994;Boyle and Encarnacion 1998). The idea of this level is to adapt the content of a page to the knowledge, goals, and other features of an individual user.…”

Section: Levels Of Adaptation In E-learningmentioning

confidence: 99%

Learning content design and learner adaptation for adaptive e-learning environment: a survey

Premlatha

Geetha

2015

Artif Intell Rev

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This paper presents a survey about learning content designs and various adaptation levels, in order to adapt the learners' necessities in e-learning environment. Normally, learners have different learning styles, cognitive traits, learning goals and varying progress of their learning over period of time, which affects the learner's performance while providing the same bundle of course to all learners. Hence, there is a need to create adaptive e-learning environment to offer appropriate learning content to all individuals. In general, the adaptation can be done based on learners' characteristics. Here, we explore the adaptation that can be done, not only based on learner context parameters but also on the learning content (learning object) and the configuration of e-learning environment. In this paper, we provide a detail review about the various levels of adaptation, learning object design and process for learning content design, learner context parameters, and models/components of e-learning; moreover, we analyze and portray the associations among the components, necessary to achieve the well-defined adaptation in e-learning environment.

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Section: Levels Of Adaptation In E-learningmentioning

confidence: 99%

Learning content design and learner adaptation for adaptive e-learning environment: a survey

Premlatha

Geetha

2015

Artif Intell Rev

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“…Scores related to every combination and the "best" combination for each profile evaluating an adaptive system is to compare it to its non adaptive version. This approach was adopted by the evaluations of both MetaDoc (Boyle and Encarnacion 1994) and PUSH (Hook, 1997). Although these evaluations showed that the adaptive versions of the systems improved users' performance in several information tasks, the quality of the non-adapted version can often be argued.…”

Section: The Experimentsmentioning

confidence: 99%

Modeling Elementary Cognitive Abilities for Adaptive Hypermedia Presentation

Tarpin-Bernard

Habieb-Mammar

2005

User Model User-Adap Inter

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The adaptation of hypermedia can be carried out at three levels, namely the content, navigation and presentation level. The presentation level is the least studied of the three, apparently because it refers to user properties that are not easy to model. In this paper, we present a new approach to modeling cognitive abilities that relies on basic mental functionalities. We describe the Cognitive User Modeling for Adaptive Presentation of Hyper-Documents (CUMAPH) environment, which mainly provides an authoring tool and an adaptation engine. The aim of this environment is to adapt a hyper-document presentation by selecting the elements that best fit the user cognitive profile. Its architecture is based on four main components: a cognitive user model, a hyper-document builder, an adaptation engine and a generic style sheet. To validate our approach, we designed an innovative protocol and conducted an experimental study involving 39 students. The first results show that an adaptive presentation can significantly increase the efficiency of hypermedia presentations.

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“…This approach is motivated by a stream of work on adaptive presentation. Boyle and Encarnacion (1994) and Kobsa et al (2001) have shown that by adapting the level of explanation to user knowledge of a subject (i.e., providing additional explanations to novice users, while offering highly specific details to expert users) can result in faster comprehension and decreased error rate. Those prior good results could be transplantable to the visualization ground.…”

Section: Introductionmentioning

confidence: 98%

User-adaptive explanatory program visualization: evaluation and insights from eye movements

Loboda

Brusilovsky

2010

User Model User-Adap Inter

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User-adaptive visualization and explanatory visualization have been suggested to increase educational effectiveness of program visualization. This paper presents an attempt to assess the value of these two approaches. The results of a controlled experiment indicate that explanatory visualization allows students to substantially increase the understanding of a new programming topic. Furthermore, an educational application that features explanatory visualization and employs a user model to track users' progress allows students to interact with a larger amount of material than an application which does not follow users' activity. However, no support for the difference in short-term knowledge gain between the two applications is found. Nevertheless, students admit that they prefer the version that estimates and visualizes their progress and adapts the learning content to their level of understanding. They also use the application's estimation to pace their work. The differences in eye movement patterns between the applications employing adaptive and non-adaptive explanatory visualizations are investigated as well. Gaze-based measures show that adaptive visualization captivates attention more than its non-personalized counterpart and is more interesting to students. Natural language explanations also accumulate a big portion of students' attention. Furthermore, the results indicate that working memory span can mediate the perception of adaptation. It is possible that user-adaptation in an educational context provides a different service to people with different mental processing capabilities.

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Metadoc: An Adaptive Hypertext Reading System

Cited by 67 publications

References 6 publications

Learning content design and learner adaptation for adaptive e-learning environment: a survey

Learning content design and learner adaptation for adaptive e-learning environment: a survey

Modeling Elementary Cognitive Abilities for Adaptive Hypermedia Presentation

User-adaptive explanatory program visualization: evaluation and insights from eye movements

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