Automatic selection and sequencing of learning objects in adaptive education systems based on learner traits

Abstract

E learning regarded as technology package of education has attained newlinesignificance due to its advantages of learning at any time any pace and from newlineanywhere Learning Objects LO a collection of content items practice items newlineand assessment items for education are inevitable constituents of any E learning newlinesystem Learning Objects are associated with mandatory information about newlinethemselves such as topic name objective interactivity and technology newlinerequirements This information is termed as LO Metadata LO metadata can be maintained in standard formats or in customized formats The standard metadata formats define a set of metadata elements for storing information about the Learning Objects and enable the E learning systems to record metadata in a uniform fashion across the world As opposed to this customized formats of metadata record set of information specific to thesystem and they vary from one learning system to the other Learning Management Systems and Learning communities use standard metadata formats in designing their Learning Objects A large number of LOs have been prepared by domain experts and are available in public repositories These repositories store the associated metadata in standard formats It is observed that LOs in public repositories can be reused in E Learning Systems for minimizing the newlineeffort in developing new LOs Learning is always a cognitive activity which differs from learner to learner and so raises the need of adaptive E learning Education System newlineproviding adaptive learning is referred as Adaptive Education System AES In newlineAES Learning Objects need to be selected according to the characteristics of newlinelearners and must be sequenced in a predetermined order thus giving a defined newlinelearning path to the learners newline newline