The purpose of this research is to assess the sports and socialization of the students studying in different sports branches in Gumushane University. “Socialization- Sports and Socialization Scale” developed by Sahan was used in this research. A total of 742 students composed of 316 females and 426 males studying in Gumushane University participated in this survey modelled research. Data obtained were evaluated in SPSS package program. Reliability coefficient of the scale was found to be 0.896. T-Test, Kruskall Wallis and Anova were used in statistical assessment of data. Pearson Product-Moment Correlation analysis was used to determine whether there was a significant relation between socialization and sports-socialization scores and the causal relations between two variables were tested with simple linear regression analysis. The study was analyzed in terms of certain variables and it was concluded that the variables of gender, age, place of residence and type of sports done by the participants didn’t make a difference on sports-socialization and socialization scores. It is also observed that there is a positive and significant relation between the variables of socialization and sports-socialization (r= .624, p<.01). In other words, it can be stated that the higher the socialization scores of the participants are, the higher their sports-socialization scores become, accordingly.  

The study's goal was to examine the correlation between the computer programming self-efficacy and computational thinking skills of gifted and talented students. The capacity of the computer programming self-efficacy of gifted and talented students to predict their computational thinking skills were also examined. The relational screening model has been implemented in the research. The participants of the study were composed of 106 secondary school gifted and talented students studying the Individual Ability Recognition Program (IAR) at the Science and Art Center in the city center. Typical case sampling was applied for the student identification of the participants, 46 are female and 60 are male. Gifted and talented students' computational thinking skills were assessed using the "Computational Thinking Skills Scale” and the computer programming self-efficacy was measured by using the "Computer Programming Self-Efficacy Scale". Data were analysed by Pearson correlation analysis and simple linear regression analysis in statistical software SPSS 22. Research results found that there was a positive and high correlation between the computer programming self-efficacy and computational thinking skills. The gifted and talented students' computer programming self-efficacy demonstrated 31.5% of the total variance in computational thinking skills. This finding supports the claim which is present in the literature that self-efficacy in computer programming is the affective aspect of computational thinking skills. To predict computational thinking skills, it may be recommended to build multiple models for cognitive and affective skills of gifted and talented students.