Preparation and compilation of electronic content
S.F. Noor Behbahani; A. Kardan
Abstract
Nowadays e-learning has an important role as a collaborative learning environment in education. Obviously one of the most important challenges in e-learning is to produce appropriate learning contents for learners. One solution could be selecting and edit appropriate annotations being placed by learners. ...
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Nowadays e-learning has an important role as a collaborative learning environment in education. Obviously one of the most important challenges in e-learning is to produce appropriate learning contents for learners. One solution could be selecting and edit appropriate annotations being placed by learners. Due to the possibility of adding annotations to a specific learning content, exploiting learners’ annotations can help course author to improve his/her learning content. Regarding to concepts’ ontology and contents’ annotations, it is possible to edit certain contents in content hierarchy. Furthermore, it is possible to create learning contents by selecting high rated learners’ annotations and presenting them to other learners. Being an implicit method related content annotation that can be easily edited or removed are considered as the advantages of the proposed method of using annotations for editing contents. In this paper a framework for using learners’ annotations for selecting and editing learning contents in e-learning systems is presented. The details of annotations classification and method of rating annotations will be discussed. In addition, the proposed solution is tested and advantages of annotations are analyzed in order to produce feedbacks for authors and the conclusions are shown.
Information literacy
A. Kardan; S. Kardan
Abstract
One of the important issues in a learning management system is the assessment of the learner’s knowledge level. In basic methods of assessment, questions are simply ticked by the learners, and then automatically scored by machine. In this sort of examinations, two problems may be raised. Firstly, ...
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One of the important issues in a learning management system is the assessment of the learner’s knowledge level. In basic methods of assessment, questions are simply ticked by the learners, and then automatically scored by machine. In this sort of examinations, two problems may be raised. Firstly, the learner may answer and mark the questions accidentally by guessing the answer without having enough knowledge about the related subject. Secondly, he/she may slip in answering the questions due to his/her inattention, although he/she has enough knowledge about the related subject. In this work, an improved method for knowledge level assessment is presented. In the proposed method learning concepts are modeled based on the hierarchical construct of learning objectives, and the learner’s knowledge model is used to estimate his/her knowledge level. This model is established on the basis of Bayesian networks, and considering the hierarchical construct of learning objectives. To evaluate the proposed method, a set of questions by considering the learning objectives was designed and ordered into different levels of complications. Then these questions were used for assessments. In this work also a new algorithm for updating the nodes in a Bayesian network is introduced. By means of this algorithm the effect of guessing and slipping answers in an assessment is undoubtedly reduced. Finally, by presenting a model for knowledge and use of the hierarchical construct of learning objectives, an effective solution for three above mentioned problems of guessing answers, slipping answers, and the origin of wrong answers have been established.
