Show simple item record

dc.contributor.advisorRidley, Mick J.
dc.contributor.advisorAlhajj, R.
dc.contributor.authorSuleiman, Iyad*
dc.date.accessioned2015-06-24T15:10:38Z
dc.date.available2015-06-24T15:10:38Z
dc.date.issued2015-06-24
dc.identifier.urihttp://hdl.handle.net/10454/7293
dc.description.abstractA major challenge that faces most families is effectively anticipating how ready to start school a given child is. Traditional tests are not very effective as they depend on the skills of the expert conducting the test. It is argued that automated tools are more attractive especially when they are extended with games capabilities that would be the most attractive for the children to be seriously involved in the test. The first part of this thesis reviews the school readiness approaches applied in various countries. This motivated the development of the sophisticated system described in the thesis. Extensive research was conducted to enrich the system with features that consider machine learning and social network aspects. A modified genetic algorithm was integrated into a web-based stealth assessment tool for school readiness. The research goal is to create a web-based stealth assessment tool that can learn the user's skills and adjust the assessment tests accordingly. The user plays various sessions from various games, while the Genetic Algorithm (GA) selects the upcoming session or group of sessions to be presented to the user according to his/her skills and status. The modified GA and the learning procedure were described. A penalizing system and a fitness heuristic for best choice selection were integrated into the GA. Two methods for learning were presented, namely a memory system and a no-memory system. Several methods were presented for the improvement of the speed of learning. In addition, learning mechanisms were introduced in the social network aspect to address further usage of stealth assessment automation. The effect of the relatives and friends on the readiness of the child was studied by investigating the social communities to which the child belongs and how the trend in these communities will reflect on to the child under investigation. The plan is to develop this framework further by incorporating more information related to social network construction and analysis. Also, it is planned to turn the framework into a self adaptive one by utilizing the feedback from the usage patterns to learn and adjust the evaluation process accordingly.en_US
dc.language.isoenen_US
dc.rights<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>.eng
dc.subjectSchool readiness, Data mining, Social networks, Adaptive web-based assessment, Stealth assessment, Serious games, Hypermedia systems, On-line genetic algorithm, Machine learning, Cross platform applicationen_US
dc.titleIntegrating Data Mining and Social Network Techniques into the Development of a Web-based Adaptive Play-based Assessment tool for School Readiness.en_US
dc.type.qualificationleveldoctoralen_US
dc.publisher.institutionUniversity of Bradfordeng
dc.publisher.departmentComputer Science, Electrical Engineering and Computer Scienceen_US
dc.typeThesiseng
dc.type.qualificationnamePhDen_US
dc.date.awarded2013
refterms.dateFOA2018-07-25T11:41:39Z


Item file(s)

Thumbnail
Name:
Thesis-Final Submission version ...
Size:
3.663Mb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record