784 research outputs found
A spiral model for adding automatic, adaptive authoring to adaptive hypermedia
At present a large amount of research exists into the design and implementation of adaptive systems. However, not many target the complex task of authoring in such systems, or their evaluation. In order to tackle these problems, we have looked into the causes of the complexity. Manual annotation has proven to be a bottleneck for authoring of adaptive hypermedia. One such solution is the reuse of automatically generated metadata. In our previous work we have proposed the integration of the generic Adaptive Hypermedia authoring environment, MOT ( My Online Teacher), and a semantic desktop environment, indexed by Beagle++. A prototype, Sesame2MOT Enricher v1, was built based upon this integration approach and evaluated. After the initial evaluations, a web-based prototype was built (web-based Sesame2MOT Enricher v2 application) and integrated in MOT v2, conforming with the findings of the first set of evaluations. This new prototype underwent another evaluation. This paper thus does a synthesis of the approach in general, the initial prototype, with its first evaluations, the improved prototype and the first results from the most recent evaluation round, following the next implementation cycle of the spiral model [Boehm, 88]
Design of the CAM model and authoring tool
Students benefit from personalised attention; however, often teachers are unable to provide this. An Adaptive Hypermedia (AH) system can offer a richer learning experience in an educational environment, by giving personalised attention to students. On-line courses are becoming increasingly popular by means of Learning Management Systems (LSM). The aim of the GRAPPLE project is to integrate an AH with major LMS, to provide an environment that delivers personalised courses in a LMS interface. However, designing an AH is a much more complex and time-consuming task, than creating a course in a LMS. Several models and systems were developed previously, but the (re)-usability by educational authors of the adaptation remains limited. To simplify adaptive behaviour authoring for an educational author, a visual environment was selected as being most intuitive. This paper describes a reference model for authoring in a visual way and introduces an authoring tool based upon this model
A meta level to LAG for adaptation language re-use
Recently, a growing body of research targets authoring of content and adaptation strategies for adaptive systems. The driving force behind it is semantics-based reuse: the same adaptation strategy can be used for various domains, and vice versa. E.g., a Java course can be taught via a strategy differentiating between beginner and advanced users, or between visual versus verbal users. Whilst using an Adaptation Language (LAG) to express reusable adaptation strategies, we noticed, however, that: a) the created strategies have common patterns that, themselves, could be reused; b) templates based on these patterns could reduce the designers' work; c) there is a strong preference towards XML-based processing and interfacing. This has lead us to define a new meta-language for the LAG Adaptation Language, facilitating the extraction of common design patterns. This paper provides more insight into the LAG language, as well as describes this meta-language, and shows how introducing it can overcome some redundancy issues
Reusing adaptation strategies in adaptive educational hypermedia systems
Due to the difficulty and thus effort and expenses involved in creating them, personalization strategies in learning environments have to demonstrate a higher return-on-investment (ROI), if they are to be a viable component of the learning setting of the future. One feature that can increase this ROI is the reusability of adaptation strategies in Adaptive Educational Hypermedia Systems. This research looks into various ways of enhancing this reusability. Using multiple modular adaptation strategies (MAS) with a controlling meta-strategy is proposed as a more efficient way of authoring adaptation strategies. This renders the reuse of adaptation strategies faster and easier for course authors. A method for semi-automatically breaking down complex adaptation strategies into smaller modular adaptation strategies is described. Potential problems with using multiple strategies are described and ways to solve them are discussed. Finally, some evaluation points are illustrated, conclusions are drawn and further research areas are identified
Investigating the impact of social interactions in adaptive E-Learning by learning behaviour analysis
Adaptive Educational Hypermedia Systems (AEHSs) allow for personalization of e-learning1 . Social media tools enable learners to create, publish and share their study, and facilitate interaction and collaboration2
. The integration of social media tools into AEHS offers novel opportunities for learner engagement and extended user modelling, and thereby fosters so-called Social Personalized Adaptive E-learning Environments (SPAEEs)
3. However, there has been a lack of empirical design and evaluation to elaborate methods for SPAEEs. The goal of research, therefore, is to investigate 1) the learning
behaviour patterns within SPAEEs and the use of these patterns for learner engagement, 2) the evaluation methodologies for SPAEEs, and 3) the design
principles for SPAEEs. Topolor4 is a SPAEE that has been under iterative development for achieving our research goals. The first prototype was used as an online learning system for MSc level students in the Department of
Computer Science, at the University of Warwick, and usage data was anonymously collected for analysis5
. This poster focuses on system features and
learning behaviour analysis. We firstly present the methodologies applied in the research, followed by the social and adaptive features that Topolor provides6
. Then we revisit the analysis of learning behaviours7
. Finally we propose the follow-up work based on the evaluation results
Is adaptation of e-advertising the way forward?
E-advertising is a multi-billion dollar industry that has shown exponential growth in the last few years. However, although the number of users accessing the Internet increases, users don’t respond positively to adverts. Adaptive e-advertising may be the key to ensuring effectiveness of the ads reaching their target. Moreover, social networks are good sources of user information and can be used to extract user behaviour and characteristics for presentation of personalized advertising. Here we present a two-sided study based on two questionnaires, one directed to Internet users and the other to businesses. Our study shows that businesses agree that personalized advertising is the best way for the future, to maximize effectiveness and profit. In addition, our results indicate that most Internet users would prefer adaptive advertisements. From this study, we can propose a new design for a system that meets both Internet users’ and businesses’ requirements
Transforming a linear module into an adaptive one : tackling the challenge
Every learner is fundamentally different. However, few courses are delivered in a way that is tailored to the specific needs of each student. Delivery systems for adaptive educational hypermedia have been extensively researched and found promising. Still, authoring of adaptive courses remains a challenge. In prior research, we have built an adaptive hypermedia authoring system, MOT3.0. The main focus was on enhancing the type of functionality that allows the non-technical author, to efficiently and effectively use such a tool. Here we show how teachers can start from existing course material and transform it into an adaptive course, catering for various learners. We also show how this apparent simplicity still allows for building of flexible and complex adaptation, and describe an evaluation with course authors
Consideration of building a common platform of collaborative learning environment
This paper reports on considerations about a common and basic functions/components for building a collaborative learning environment. We make efforts to specify the technological issues towards the future standardization of this environment through our research experiences. The problem of standardization includes many embarrassed aspects, however it will extend and widen the field of applications possible within the collaborative learning paradigm, and will make possible the usage of the fruits of years of research and individual implementations of the concept of collaborative learning, from many researches, developments and experiences. So we would like to locate this problem as building a common platform
Designing social personalized adaptive e-learning
Here we introduce Topolor, a social personalized adaptive elearning system aiming to improve social interaction in the
learning process as well as applying classical adaptation based on user modeling. Here, we focus on the system architecture and preliminary evaluation that showed high system usability
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