A Web and Software-Based Approach Blending Social Networks for Online Qur’anic Arabic Learning

About 80 percent of the world's Muslim populations are non-native speakers of the Arabic language. Since it is obligatory for all Muslims to recite Qur'an in Arabic during prayers, an extraordinary social phenomenon has taken place in some parts of the Muslim world: Muslims are taught the complex phonological rules of the Arabic language in the context of Qur'an and they recite the “sounds” of Qur'an often understanding very little. This has given rise to a demographic segment of adult learners whose main learning goal is recalling a closed set of syntactic rules and vocabularies in the context of Qur'an while reciting or listening to it so that they can reconstruct a meaning in their native-language. Despite the availability of some resources for learning language for this specific purpose, according to our detailed investigation, no work has explored the possibilities of emerging adaptive and intelligent systems for collaborative learning to address this challenge. The goals of this work are: (a) To determine the applicability of learner corpus research, declarative memory modelling, and social learning motivation on the learners' specific pedagogical objectives; (b) To use the Design-Based Research methodology (DBR) to optimize the design of such a system in real-life setting to observe how the different variables and elements work out. We present here, a prototype to gather requirement analysis of such a system by bootstrapping a user community. The compiled data were used to design an initial architecture of an intelligent and adaptive Qur'anic Arabic learning system.