Application of Android Based Mobile Learning Platform Using Latent Semantic Analysis

Nowadays, the growth of mobile learning systems has been remarkable, as it helps in transforming the educational landscape globally and emerged as a natural extension of Electronic Learning (E-learning). In previous, mobile learning platforms are used such as Java-based Mobile application for Mathematics Learning (JMML). However, the existing JMML has restricted generalizability and there is no automatic grading functionality. Hence, this paper presented an effective Android based Mobile Learning Platform Using Latent Semantic Analysis (AML-LSA) to provide automatic grading results. Initially, software architecture with client-server model and a web application server is implemented. Then, a database system to store files, a speech recognition system to recognize phrases, and a validator program to compile answer submission files. Finally, LSA is introduced to evaluate validation results and offers grading results to students and teachers based on the answer submission. From the results, the proposed AML-LSA model achieved outperforming results when compared to existing Smart Learning Media based on Android Technology (SLMAT) model by providing results in terms of mean score and Standard Deviation (SD) with 89.10% and 2.23 respectively.