| Row ID | Full name in Chinese/中文全名 | Full name in English/英文全名 | Gender/性別 | Current Year of Study/目前就讀的年級 |
|---|---|---|---|---|
| 1 | Zeynep Cemile Kandilli | Zeynep Cemile Kandilli | Female/女性 | Grade 10 (Secondary 4)/中學十年級（中四） |
Children's drawings, which are one of the tools used to understand children's psychological states, are an important assessment tool for psychological counsellors in the school environment. Children's drawings provide valuable clues to understand their emotional states, inner worlds and social relationships. However, it is often difficult for counsellors in schools today to analyse children's drawings in depth due to the large number of students in their classes and their limited time. This situation constitutes an important obstacle especially in terms of early identification of children's psychological support needs. The fact that psychological counsellors do not have sufficient knowledge about the analysis of children's drawings or cannot find the time to evaluate the drawings prevents the recognition and intervention of children's problems at early stages. In this context, it is necessary to develop a system that will help school psychological counsellors and speed up the analysis of drawings made on psychological tests. Such a system will enable psychological counsellors to analyse children's drawings more quickly, efficiently and accurately, and will enable the identification of children in need of psychological support in a shorter time.
In this project, it is aimed to develop an artificial intelligence-supported psychological drawing test analysis application called ‘Drawalyze’ that will allow school psychological counsellors to analyse children's psychological states more quickly and accurately. ‘Drawalyze’ will provide an important support in school counselling services by evaluating children's drawings and will alleviate the workload of teachers. During the development process of the application, criteria for the analysis of psychological drawing tests were prepared by using basic, up-to-date, reliable and scientific sources. The criteria were introduced and trained to the ChatGPT 4o-mini model using the Application Programming Interface (API) of the OpenAI Developer Platform via Python, and a system was developed that analyses the child picture uploaded to the application and provides a psychological analysis report and gives feedback on whether the child who drew the picture should receive psychological support or not. A user-friendly interface was created using the Kivy library and ‘Drawalyze’ was made available to school psychological counsellors.
The human factor in the evaluation of psychological drawing tests always brings certain limitations. Artificial intelligence supported ‘Drawalyze’ increases the accuracy and reliability of these tests by offering advantages such as speed, objectivity and consistency in the analysis of these tests. The artificial intelligence model integrated into the application in the method followed in the project provides advantages in terms of analysing the picture in detail, evaluating it holistically and presenting a detailed psychological analysis report. In addition, the introduction of criteria obtained from reliable and scientific sources to artificial intelligence has enabled Drawalyze to provide consistent, accurate and objective results in the psychological analysis of children's drawings. The developed interface makes Drawalyze a user-friendly and practical application for school psychological counsellors. Drawalyze has been tested by psychological counsellors in kindergartens and it has been found to be more objective and consistent compared to traditional methods, to be at least as accurate as psychological counsellors, and to provide a great support by reducing their workload. All these factors ensures that the proposed solution is the best solution.
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