An Intelligent Web-Based System for Diagnosing Student Learning Problems Using Concept Maps

The aim of this article is to propose a method for development of concept map in web-based environment for identifying concepts a student is deficient in after learning using traditional methods. Direct Hashing and Pruning algorithm was used to construct concept map. Redundancies within the concept map were removed to generate a learning sequence. Prototype learning system was developed based on this learning sequence using Android Emulator. For analysis purpose, 42 learners were given to learn the course Java Programming taught at graduation level. A posttest was conducted after learning for evaluation purpose. Multiple regression analysis method was applied on these results to develop regression equations for the proposed method of learning. Statistical Package for Social Sciences software was used for statistical analysis purposes. It was found that posttest results are directly proportional to the quality of traditional learning. Better quality students require less time in constructing prototype system. Further concept mapping was found to have a positive impact on proposed method of learning. When the number of concepts is large, a learning sequence among these can be generated using the proposed method. This learning sequence can be used to identify the concept a student needs additional learning.