Research
E-learning by Time Dynamic Model Using Data Mining
The object of this paper is to build up Just in Time Dynamic Learner Models to analyze learners' behaviors and to evaluate learners' performance in online education systems by using rich data collected from e-learning systems. The goal is to create metrics to measure learners' characteristics from usage data. To achieve this goal we need to use data mining methods, especially clustering algorithms, to second patterns from which metrics can be derived from usage data. In this paper, we propose a six layer models(raw data layer, fact data layer, data mining layer, measurement layer, metrics layer and pedagogical application layer) to create a just in time learner model which draws inferences from usage data. In this approach, we collect raw data from online systems, latter fact data from raw data, and then use clustering mining methods to create measurements and metrics.
On the Solutions of Generalized Fractional Kinetic Equations involving the Functions for the Fractional Calculus
The paper is devoted to the study of the solution of generalized fractional kinetic equations. Results are obtained in a compact form in terms of K4 - Function introduced by sharma [9]. The results obtained in this paper are the extensions of the results given earlier by Chaurasia and Pandey[19-20] believed to be new.
