An Arabic Text-to-Picture Mobile Learning System

Abstract

Handled devices and software applications are susceptible to ameliorate learning strength, awareness, and career development. Many mobile-based learning applications are obtainable from the market but Arabic learning shortage is not taken in consideration. We conduct an Arabic Text-to-Picture (TTP) mobile educational application which performs knowledge extraction and concept analysis to generate pictures that represent the content of the Arabic text. The knowledge extraction is based on Arabic semantic models cover important scopes for young children and new Arabic learners (i.e., grammar, nature, animals). The concept analysis uses semantic reasoning, semantic rules, and Arabic natural text processing (NLP) tool to identify word-to-word relationships. The retrieval of images is done spontaneously from local repository and online search engine (i.e., Google or Bing). The instructor can select the Arabic educational content, get semi-automatic generated pictures, and use them for explanation. Preliminary results show improvement in Arabic learning strength and memorization.