Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 3 |
Descriptor
| Addictive Behavior | 3 |
| Information Technology | 3 |
| Predictor Variables | 3 |
| Foreign Countries | 2 |
| Handheld Devices | 2 |
| Bullying | 1 |
| Correlation | 1 |
| Educational Attainment | 1 |
| Electronic Mail | 1 |
| Employees | 1 |
| Gender Differences | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 2 |
| Reports - Research | 2 |
| Dissertations/Theses -… | 1 |
Education Level
| Secondary Education | 2 |
| Elementary Education | 1 |
| Grade 5 | 1 |
| Grade 6 | 1 |
| Grade 7 | 1 |
| Grade 8 | 1 |
| High Schools | 1 |
| Intermediate Grades | 1 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
Audience
Location
| Turkey | 2 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Esra Malkoç; Tugba Yanpar Yelken – Journal of Educational Technology, 2023
The aim of this study is to examine the relationship between technology addiction levels and peer bullying levels of students at secondary school and to reveal their views on this topic. The survey model from quantitative research method was used in the research. While the population of the research is composed of all secondary schools in district…
Descriptors: Secondary School Students, Information Technology, Addictive Behavior, Student Behavior
Ramazanoglu, Mehmet – World Journal of Education, 2020
The purpose of this study is to examine the relationships between high school students' internet addiction, social media usage disorder, and smartphone addiction. The descriptive relational scanning model, one of the quantitative research methods, was used to determine this relationship. The research was carried out with 215 students who continue…
Descriptors: Correlation, High School Students, Internet, Addictive Behavior
Hunka, Patricia L. – ProQuest LLC, 2014
This study was completed to understand whether or not work addiction or work addiction intensity could be predicted from mobile technology use. The study further investigated whether or not gender, workspace, income, or education level would moderate the relationship. The sample used was drawn from service industry employees who are not in the…
Descriptors: Work Attitudes, Addictive Behavior, Information Technology, Handheld Devices

Peer reviewed
Direct link
