عنوان مقاله [English]
The ability to read is one of the abilities effective in quality of life. From among the children with normal intelligence and more, dyslexic students have a significant lack of readability due to their age and their ability to intelligence. In any planning and designing a treatment plan for these people, diagnosis is a necessary first step. Early and timely recognition of this disorder is essential to prevent the negative consequences of impairment. The tool that is used for data gathering is an intelligent computer game that designed and developed during this study. In this study, we looked for a method for predicting dyslexia that is not read-based, so that treatment with dyslexia can be initiated before they begin to teach. The purpose of this study was to develop an intelligent diagnostic system in the form of a computer game based on artificial intelligent and supervised machine learning to predict dyslexia based on the cognitive differences of dyslexic children with other children. Games can provide a less stressful or a stress-free way for the children so that the child do not even realize that it is being measured. The intelligent diagnostic system was trained with the help of thirty students. The results of the study on performance of this intelligent system showed that the provided computer game has the ability to predict dyslexia with a probability higher than 97%.
 Afrooz, A. (2013). Learning disabilities. Tehran: Payame noor. [in Persian]
 Tabrizi, M., Tabrizi, A., & Tabrizi, N. (2016). Treatment of learning disabilities. Tehran: Fararavan. [in Persian]
 Delavarian, M., Afrooz, A., Towhidkhah, F., Rasoolzadeh tabatabaei, K., & Arjmandnia, A. (2015). a comparision between working memory in dyslexic and normal children. Learning Disabilities, 5(23), 43-53. [in Persian]
 Asgari, R. (2006). Designing and usage of an educational software based on vision psychological model for mental treatment of dyslexic elementary students (Unpublished master’s thesis). Tarbiat Moallem University, Tehran. [in Persian]
 Zare, F. (2009). Prediction of dyslexia based on graphic indicators (Unpublished master’s thesis). Sistan and Balichestan University, Sistan and Balichestan. [in Persian]
 Nazari, S. (2012). Manner of dyslexia detection in WISC-R. Atypical Education, 109, 36-46. [in Persian]
 Tabrizi, M., & moosavi, M. (2015). Administration and scoring manual for Marianne Frostic developmental test of visual perception. Tehran: Fararavan. [in Persian]
 Rostamzadeh, G. (accessible in 2015). Accession of dyslexia in elementary students in Ahwaz. Ahwaz: Educational Administration. [in Persian]
 Pashapoor, N. & Zibarzani, R. (1997). Accession of dyslexia in 3rd elementary students in Urumiah. The Proceedings of the First Congress of Iran Psychological Association (pp. 129-130). Tehran, Iran. [in Persian]
 Heidari, S. (2014). Affect of action video games on reading ability and selection visual attention in dyslexic children (Unpublished master’s thesis). Payame noor university, Tehran. [in Persian]
 Ferwerda, J., & Rehon, B. (2007). MagnoFly: game-based screening for dyslexia [Abstract]. Journal of Vision, 7(9), 520.
 Alwalib, A., & Meldah, E. (2010). Designing Educational Games for Children with Specific Learning Difficulties: Insights from Involving Children and Practitioners. The Proceedings of Computing in the Global Information Technology (ICCGI) (pp. 195-198). Valencia.
 Rello, L. Ali, A. & Bigham, J. (2015). Dytective: toward a game to detect Dyslexia. ASSETS '15 The Proceedings of the 17th International ACM SIGACCESS Conference on Computers & Accessibility (pp. 307-308). Lisbon, Portugal
 Rello, L. Ballesteros, M. Ali, A. Serra, M. Alarcon Sanchez, D., & Bigham, J. (2016) Dytective: diagnosing risk of dyslexia with a game. Pervasive Health '16 Proceedings of the 10th EAI International Conference on Pervasive Computing Technologies for Healthcare (pp. 89-96). Cancun, Mexico
 Delavarian, M., Afrooz, A., Towhidkhah, F., Rasoolzadeh Tabatabaei, K., & Arjmandnia, A. (2015). Designing an neuro cognitive application to measure working memory in order to detection of children that may have dyslexia. Tebbe tavanbakhshi. 5(3),75-83. [in Persian]
 Poorafkary, N. (2003). Brief textbook Oxford psychology. Tehran: Shahrab. [in Persian]
 Saniei abadeh, M. Mahmoodi, S., & Taherparvar, M. (2013). Applied data mining). Tehran: Niaze Danesh. [in Persian]