The artificial neural network modeling of language learning challenges of French-speaking students learning Turkish as a foreign language: The case of France

Abstract

This study is about artificial neural network modeling of the linguistic challenges encountered by students learning Turkish as a foreign language in universities in France. The study was conducted in four universities where Turkish is taught as an optional foreign language. Sixty-six students whose mother tongues were either Arabic or French constituted the study group. Planned on a background of an integrated single-case pattern, this study was conducted using a mixed research method which involved gathering and joint interpretation of qualitative and quantitative data groups with an objective to better understand the gaps in knowledge encountered in this research field. The research data were collected through participants’ answers to the following open-ended question prepared by the researcher: What are the challenges you encounter when learning Turkish? Data were analyzed using the content analysis method. The results indicated that students find the linguistic elements the most challenging, followed by the aspects of “suffixes,” “grammar” and “syntax.” In line with these results, an artificial neural network model using the MATLAB computing environment software was created based on the students’ mother tongues and linguistic challenges, and the application of this modeling in teaching environments is explained in detail.