This study aims to examine how technology used in the Cyprus Turkish Blind Association assisted the teaching-learning and administrative processes for the visually impaired. Qualitative research techniques were used for data collection and analysis. This study is a case study that aims to examine how the technology used in the association facilitated the teaching-learning and administrative processes for the visually impaired people. The study also found that with the assistance of technology the participants of the study were quite motivated and could easily communicate with each other and also with people outside their organization. Yet, there is a lack of technological devices such as automatic high-speed book scanner and imported books printed in Braille that would improve the quality of life of the association members.

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The purpose of this study is to investigate the opinions and evaluations of pre-service mathematics and pre-service primary school teachers regarding the concrete models of their design during the COVID-19 Pandemic in the context of positive psychology. In this study, a mixed research method, in which quantitative and qualitative research methods are used together was used. The participant group of the study consists of 441 pre-service mathematics and pre-service primary school teachers studying at universities. For the conduct of the qualitative research, 44 pre-service teachers were selected using the purposive sampling method. “Mathematics Teaching Practices Enriched with Concrete Models Perception Scale” developed by the researchers was used to collect the quantitative data to reveal the opinions of teachers regarding mathematics teaching practices enriched with concrete models. In this study, open-ended questions were used to obtain qualitative data, and the data were evaluated with content analysis. According to the results of the study, it was determined that the majority of the pre-service teachers had positive perceptions of concrete models. Pre-service teachers argued that they would use concrete models in their professional lives and that these models were indispensable for mathematics education. In addition, advantages and disadvantages for mathematics educators regarding the use of concrete models are presented.

Individuals with special needs learn more slowly than their peers and they need repetitions to be permanent. However, in crowded classrooms, it is difficult for a teacher to deal with each student individually. This problem can be overcome by using supportive education applications. However, the majority of such applications are not designed for special education and therefore they are not efficient as expected. Special education students differ from their peers in terms of their development, characteristics, and educational qualifications. The handwriting skills of individuals with special needs are lower than their peers. This makes the task of Handwriting Recognition (HWR) more difficult. To overcome this problem, we propose a new personalized handwriting verification system that validates digits from the handwriting of special education students. The system uses a Convolutional Neural Network (CNN) created and trained from scratch. The data set used is obtained by collecting the handwriting of the students with the help of a tablet. A special education center is visited and the handwritten figures of the students are collected under the supervision of special education teachers. The system is designed as a person-dependent system as every student has their writing style. Overall, the system achieves promising results, reaching a recognition accuracy of about 94%. Overall, the system can verify special education students' handwriting digits with high accuracy and is ready to integrate with a mobile application that is designed to teach digits to special education students.