An alternative m-learning scoring approach to automatically evaluate Iqro’s pronunciation based on pitch, volume, and rhythm features

Abstract

The Iqro’ has been proven as an effective method to improve literacy for reading Hijaiyah letters which are the fundamental skill for reading the Qur’an. The Iqro method relies on a mentor to evaluate the accuracy of the student’s pronunciation of the Hijaiyah letters. With the advancement of mobile technology, many mobile apps are available to assist the learning process. However, the existing solution that is available on the market only provides a one-way learning experience where users only focus on enhancing vocabulary, writing, and reading ability with a simple true-false assessment. Although enhancing the vocabulary and reading ability is important, training the correct Makhraj (Arabic pronunciation) is also essential in fundamental Hijaiyah learning. This paper presents the feasibility investigation of the usage of the pitch, volume, and rhythm as the more comprehensive audio assessment parameters in the voice recognition module to evaluate the student's ability to pronounce the Hijaiyah letter in an m-learning implementation. Instead of just presenting the true-false output, the proposed method will calculate the Makhraj correctness in the range 0 to 100. Experimental results with 10 respondents show that the sample correlation coefficient using Pearson between a manual assessment by Ustaz and the application result for Iqro’ level 1 is 0.51 which means this approach is acceptable for future implementation.