Smart Concept Map Generation for Learning Using Class of Hash Functions

Abstract

Concept Maps have recently been used by several researchers to construct web-based learning systems. This is due to their flexibility in organizing knowledge. However, for an effective use of Concept Maps in web-based learning, automated construction is necessary. This study first gives brief details about the use of Concept Maps in electronic and mobile learning environments. Direct Hashing and Pruning algorithm is then used for automated generation of Concept Maps. The generated Concept Maps, however, depend on the nature of the hash function. The uses of three different types of hash functions are investigated and results compared. A prototype of the learning system is developed using an Android emulator. Finally, the proposed methodology is compared with other pioneering learning systems developed by the researchers using Concept Maps.