Advanced Computing and Communication Techniques for High Performance Applications |
Foundation of Computer Science USA |
ICACCTHPA2014 - Number 3 |
February 2015 |
Authors: R.rajkumar, M.karthikeyan, N.vivekantha Moorthy |
38fea007-48a8-42b6-815a-39decb0155ea |
R.rajkumar, M.karthikeyan, N.vivekantha Moorthy . Cognitive Search E-Learning Framework: An Effective Assesment based Learning System. Advanced Computing and Communication Techniques for High Performance Applications. ICACCTHPA2014, 3 (February 2015), 1-4.
Technological advancements have made increased internet usage around the world in recent times and individuals use internet search engines as primary medium of reference for clarification of concept and knowledge level doubts. Rarely printed books are used for such purposes and its usage is fading out. However technology should help the learner to gain knowledge fully and effectively. Many learning initiatives were emerged with content based learning. Mobile based learning also came in the form of smart phone applications. Even though, these E-Learning/M-Learning systems couldn't meet the learner's preference in using contents, some of the E-Learning systems cater to learning styles of users like VARK. This may help to frame the customized learning system according learner's need. But these systems couldn't adapt to the dynamic behavior of the individual learner. In technical education, the learner should understand each of the concepts related to the domain or particular subject. To satisfy this, we have proposed a framework that performs cognitive approach in e-learning. This helps the learner to get motivated and choose learning preferences and choice of learning materials which is already available in internet. This framework is intended help the learner to gain adequate knowledge about the subject or domain to any level of depth. The learner has sufficient freedom to use this learning framework and expected to achieve the intended learning outcomes effectively. This research study also proposes a unique assessment type of learning with concept mappings. We have proposed some combinations of unsupervised and supervised learning algorithms for the self evaluation at the time of learning.