dc.contributor.author | Wakelam, Edward | |
dc.contributor.author | Jefferies, Amanda | |
dc.contributor.author | Davey, N. | |
dc.contributor.author | Sun, Yi | |
dc.date.accessioned | 2015-11-23T10:14:14Z | |
dc.date.available | 2015-11-23T10:14:14Z | |
dc.date.issued | 2015-10 | |
dc.identifier.citation | Wakelam , E , Jefferies , A , Davey , N & Sun , Y 2015 , The Potential for Using Artificial Intelligence Techniques to Improve e-Learning Systems . in ECEL 2015 Conference proceedings . ECEL 2015 , Hatfield , United Kingdom , 29/10/15 . | |
dc.identifier.citation | conference | |
dc.identifier.other | ORCID: /0000-0001-9545-1709/work/32509179 | |
dc.identifier.uri | http://hdl.handle.net/2299/16546 | |
dc.description.abstract | There has been significant progress in the development of techniques to deliver more effective e-Learning systems in both education and commerce but our research has identified very few examples of comprehensive learning systems that exploit contemporary artificial intelligence (AI) techniques. We have surveyed existing intelligent learning/training systems and explored the contemporary AI techniques which appear to offer the most promising contributions to e-Learning. We have considered the non-technological challenges to be addressed and considered those factors which will allow step change progress. With the convergence of several of the required components for success increasingly in place we believe that the opportunity to make this progress is now much stronger. We present a description of the fundamental components of an adaptive learning system designed to fulfill the objectives of the teacher and to develop a close relationship with the learner, monitoring and adjusting the teaching based upon a wide variety of analyses of their knowledge and performance. This is an important area for future research with the opportunity to deliver significant value to both education and commerce. The development of improved learning systems in conjunction with trainers, teachers and subject matter experts will provide benefits to educational institutions and help commercial organisations to face critical challenges in the training, development and retention of the key skills required to address new, emerging technologies and business models. | en |
dc.format.extent | 10 | |
dc.format.extent | 298375 | |
dc.language.iso | eng | |
dc.relation.ispartof | ECEL 2015 Conference proceedings | |
dc.subject | Adaptive learning systems, evaluation of intelligent tools, adoption of e-Learning by teachers and learners, education and career training, artificial intelligence | |
dc.title | The Potential for Using Artificial Intelligence Techniques to Improve e-Learning Systems | en |
dc.contributor.institution | School of Computer Science | |
dc.contributor.institution | Centre for Computer Science and Informatics Research | |
dc.contributor.institution | Biocomputation Research Group | |
dc.contributor.institution | ECS Computer Science VLs | |
dc.contributor.institution | Department of Computer Science | |
dc.contributor.institution | School of Physics, Engineering & Computer Science | |
dc.contributor.institution | Hertfordshire Business School | |
rioxxterms.type | Other | |
herts.preservation.rarelyaccessed | true | |