Predicting Future Behaviors among Disabled Children: An Empirical Study on Schoolchildren

Autor: Svetlana G. Rozental, Tatiana Vasilyevna Artemyeva, A. I. Akhmetzyanova
Rok vydání: 2018
Předmět:
Zdroj: Tarih Kültür ve Sanat Araştırmaları Dergisi, Vol 7, Iss 4, Pp 124-131 (2018)
ISSN: 2147-0626
Popis: The problem of socio-psychological adaptation and socialization among the children with developmental disabilities in society is actively studied by researchers. As the resource for the successful socialization of children with developmental anomalies, they regard the ability to anticipate that allows children to plan their own actions, avoid psychotraumatic situations and to prevent behavioral disorders and deviant behavior. The purpose of this study was to identify the specifics of future event prediction by the children with speech, sight, hearing impairment, motor disabilities and to develop an algorithm future event prediction ability in the areas of relationships with adults and peers. The authors performed an empirical study of 184 schoolchildren at the age of 8-10 years without developmental disorders and with speech, hearing, vision and motor impairment. Using the technique "The ability to predict in the situations of potential or a real violation of the social norm", a low level of the regulatory function of forecasting was revealed in the areas of learning, family and virtual interaction among younger schoolchildren with developmental disabilities. The authors developed an algorithm to develop the ability of future event prediction by the children with developmental disabilities. The algorithm includes 2 directions: the development of forecasting in the areas of educational and extracurricular activities. The system of work for each criterion of prognostic competence includes 6 stages and has a certain sequence: from individual tasks, during which A student learns the correct forecasting strategies to group forms of work that allow to consolidate the acquired skills and learn the way of their application in life conditions close to reality.
Databáze: OpenAIRE