Akademik Veri Yönetim Sistemi
TECHNISCHE UBERWACHUNG, cilt.25, sa.10, ss.140-155, 2025 (Scopus)
Purpose: The aim of this study; is to examine technology addiction, which deeply affects social life, and to identify university students' technology addictions and to evaluate them in terms of various variables. Method: This study, which aims to describe the technology addiction and virtual life levels of undergraduate students in our country, is in a qualitative and descriptive model. This type of research; It is defined as a research method consisting of conversations, opinions, impressions and ideas. In this type of research, questionnaires are less structured. Qualitative research is considered as a research method that aims to examine the researched subject in depth in order to gain knowledge. Therefore, this type of research is aimed at revealing the current and existing situation of the problem that is interested and wanted to be researched. The most distinctive feature of this method is to study the current situation in its own conditions and as it exists. In this study, it was aimed to determine the technology addiction and virtual life levels of undergraduate students and to evaluate the obtained data in terms of the determined variables. 130 undergraduate students who were applied the "Technology Addiction Scale" were determined as the study group. The developed information form and data collection tool (Technology Addiction Scale) were applied to the participants. The data collection tool is rated and multiple choice. Findings: According to the findings obtained with the data collection tool used in the study, the mean score of the technology addiction scale was 47.81±14.77. The arithmetic mean of the whole scale is “Not dependent” between 0-24 points, “Low dependent” between 25-48 points, “Moderately dependent” between 49-72 points, “Highly Dependent” between 73-96 points, 97-120 score range is accepted as “Full Dependent”. According to this, it can be said that the participants in the research have a "low level of addiction" to Technology Addiction. It was found that 57.9% of the participants had a low level of technology addiction, 36.8% had a medium level of technology addiction, 4.5% had a highly dependent level of technology addiction, and 0.8% had a fully dependent level of technology addiction. and age, in terms of Technology Addiction Scale scores, all the differences between them were found to be insignificant at the p>0.05 significance level. At the same time, according to the time spent by the students on social networks and the average amount of time they are on the Internet, the differences between them in terms of the Technology Addiction Scale scores are significant at p<0.05 importance level, while the status of having their own smart phone, having a desktop computer or laptop computer, the status of the family The differences between them in terms of Technology Addiction Scale scores were found to be insignificant at p>0.05 significance level, depending on their economic status, average daily use of instant messaging programs, how long they play online games on average, and which types of websites they use. These findings show that there is a difference between the students participating in the research in terms of the Technology Addiction Scale scores according to the time they spend on social networks and how long they are on the Internet on average per day. Dunnet T3 Post Hoc test was applied to understand how much time spent in social networks differed in terms of Technology Addiction Scale scores and it was observed that Technology Addiction increased as the time spent increased. Dunnet T3 Post Hoc test was applied in order to understand the difference in terms of the Technology Addiction Scale scores of those who spend an average of time on the websites, and it was observed that the Technology Addiction increased as the time spent on the websites increased. Results: The study shows that the increase in the level of technology addiction is directly proportional to the increase in the time we spent on websites and the time spent on social networks, and it has been understood that there is a significant relationship between them. It was determined whether the level of technology addiction increased or not according to the department, age and class distribution.