WES 2012 ::Technology Enhanced Shortest Learning Path


WES Track: Higher Education Track

Title of Paper: Technology Enhanced Shortest Learning Path
Author Name: Dipak Kumar Biswas
Email:dkb.ju08@gmail.com
Organization: Women’s Polytechnic
Address:  1/1/2, Garihata Road [South], Jodhpur Park, Kolkata-68, West Bengal. 700068, India

Abstract:

The main objective of the thesis is to create a pedagogical framework that attempts to blend informal and formal learning and develop a promising solution by many organizations to offer learning-on-demand opportunities to individual learner in order to gain maximum value as well as reduce training time and cost to situate learning in real world contexts. The introduction of a technologically advanced approach for learning by connecting a wide range of learning environments (for Diploma, UG, PG student, research scholars ,etc) and the bridging of theoretical and applied aspects of syllabus for the personal activities is expected to lead for the development of a new science learning scheme for all. The development of information technologies has contributed to the growth in online training as an important educational method. The online training environment enables learners to undertake customized training at any time and any place. Moreover, information technology allows both the trainers and learners to be decoupled in terms of time, place, and space. Generally speaking, the proposed model on Selection of Technology Enhanced Shortest Learning Path in e-learning systems, a course is modeled as a graph, where each node represents a knowledge unit (KU) and two nodes are connected by flows [path] to form a semantic network. The desired knowledge is provided by the student as a direct request or from search results, mapping the owned knowledge onto the target knowledge. How to select a learning path which maximize the gain [Knowledge]. In this paper dynamic programming [DP] is applied to find the shortest path in the learning environment for users and Statistical Sampling Analysis [SSA] approach is used to turn the qualitative parameters to quantitative one. Finally the shortest learning path is selected to learn the target knowledge. Keywords: Virtual learning environment [VLE], Dynamic programming [DP], Statistical Sampling Analysis [SSA], Shortest path Learning Path [SLP], Back word Recursive Formula [BRF], Learning Object [LO].

Brief Biodata of Presenter:

I am a lecturer in Mathematics posted in a Government Polytechnic, Kolkata-68. Passed M Tech IT in Course Ware Engineering from School Of Education Technology, Jadavpur University. At present I\’m working in the field of Technology Enhanced Learning in e-Learning.

 

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