International Journal of Managing Information Technology (IJMIT) WJCI Indexed
ISSN: 0975-5586 (Online); 0975-5926 (Print)
Article:
Performance Analysis of Hybrid Forecasting Model in Stock Market Forecasting
Authors
Mahesh S. Khadka, K. M. George, N. Park and J.B. Kim, Oklahoma State University, USA
Abstract
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The advent of asynchronous web based learning systems has helped the learner in a self paced, personalized and flexible learning style. It can be even more useful with a supportive synchronous tutorial (question-answer) session. The challenge is to provide sufficient information to the instructor about the learner’s experience in that particular course at run time. Online analytical processing (OLAP) is a very useful technique in producing such run time information in the form of reports. In this paper we have designed an automated scaffolding technique to hold this vital information about the learner which we have obtained by OLAP techniques on the log data of the LMS users. We have also proposed an overall architecture of the scaffolding where this information can be easily accessed and used by the instructor in the synchronous tutorial session to make the system more adaptive
Keywords
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OLAP, Asynchronous e-Learning, scaffolding, learner portfolio, adaptive learning;
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