This study's goal was to investigate the effect of homogeneous and heterogeneous pairs in terms of individual differences on group compatibility, flow, and coding performance in pair programming. In line with this goal, five individual difference variables of gender, learning style, friendship, the conscientiousness component of personality traits, and prior knowledge of coding were determined in order to use them in the determination of pairs in pair programming. In the quantitative section of this mixed study, a non-equivalent control group posttest only experimental design was utilized. Sixty-four volunteer university students were included in the study. As a result of the study, it was determined that the homogeneous group experienced a higher level of flow in the case of learning style. On the other hand, in the case of friendship, the homogeneous group experienced a higher level of flow, while the heterogeneous group demonstrated a higher level of coding performance. Concerning the conscientiousness component of personality traits, the heterogeneous group showed a higher level of coding performance. In line with these findings, suggestions for both researchers and practitioners of coding education were made in the full text.
Cooperative learning manifests itself as pair programming in coding education. There is a limited number of studies experimentally demonstrating that pair programming is effective in the educational context. Therefore, in this study, solo and pair programming were compared in terms of flow experience, coding quality, and coding achievement. The method used in this study is a pretest-posttest quasi-experimental design. The study group consists of 42 volunteer senior university students (28 males, 14 females). While solo programming was performed in the control group, pair programming was performed in the experimental group. It was concluded that the flow experience of the experimental group was higher than that of the control group in four weeks of the six-week implementation, whereas the coding quality of the experimental group was higher in three weeks. No difference was found in the other weeks in terms of both flow experience and coding quality. Although the coding achievement of both the control and experimental groups increased in the study, the experimental group did not exhibit better performance in terms of coding achievement. In conclusion, since it was revealed in this study that pair programming is effective, it is recommended to use pair programming more frequently in educational settings.
Rapid changes are occurring in life owing to information and communication technologies. During this change period, digitalidentities have begun to emerge. These identities are associated with actions that users perform in online environments. Adigital footprint is formed with these actions. The purpose of this study is to determine the digital footprint awareness anddigital footprint experiences of higher education students. In order to collect data for the study, researchers developed adata collection tool titled ‘A survey for digital media use’. The study group consisted of 508 higher education students from41 Turkish universities. Data were collected through an online-form where participation was on a volunteer basis. Thefindings of the research show that students have a high level of digital footprint awareness ( x = 4.251) and a low level ofdigital footprint experience ( x = 1.907).Keywords: Digital footprint, digital footprint awareness, digital footprint experiences, higher education students.
This study aims to determine the smart phone use and addiction levels of secondary school students from 5th and 6th grades and reveal the demographic variables concerning their addiction levels. This study was conducted with 156 students from 5 th and 6 th grades in the spring term of the school year of 2015-2016. The data were collected via "Personal Information Form" and "Smart Phone Addiction Scale (SPAS)". Survey model was used in the study. Results indicated that almost half of the students that participated in the study use smart phones for less than an hour every day, and one third of them check their smart phones every 2-3 hours. Considering the actions taken by students on their smart phones; it is observed that they mainly "play games". According to the scores obtained from the Smart Phone Addiction Scale, more than half of students are involved in the group "Addiction Tendency". Regarding the Smart Phone Addiction Scale, a significant difference was determined in terms of "gender, duration of using internet, duration of using smart phones a day, frequency of checking smart phones, frequency of accessing/checking social media environments via smart phones" variables. The total percentage of accurately classifying the discriminant function was determined as 63,7%. As a result of the study, it was determined that the variable of "frequency of accessing/checking social media environments via smart phones" classified students displaying and not displaying addiction the best. Basic result of this study is that there is a distinct difference between the smart phone addiction levels of female and male students. In this context, it is recommended the reasons of this difference were examined, and the results with relevant studies being conducted in other countries were compared.
Social media usage has been popular for the last decade. Individuals use their social media environments for various reasons such as to socialize, play games, have fun and share posts. Overuse of these environments may lead to negative psychological and behavioral consequences for individuals. Additionally, it increases the worries about potential addicted/problematic use of social media. In this study, it is aimed to determine the level of problematic social media usage of participants who are active social media users and to analyze the relationships between problematic social media usage and various personal characteristics and social variables. Study in relational screening model is carried out with the participation of 580 volunteers. Partial least squares (PLS) structural equation modeling is used to analyze the data obtained through various scale according to the research model. The structural equation modeling analysis shows that there is a significant relationship between problematic social media usage and the daily time of social media usage, the use of frequency of social media for recognition, publicity, communication/interaction and education, loneliness, and social anxiety. The variable which shows higher correlation between problematic social media usage is social anxiety.
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