Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 0 |
| Since 2006 (last 20 years) | 3 |
Descriptor
Publication Type
| Journal Articles | 3 |
| Reports - Research | 2 |
| Reports - Evaluative | 1 |
Education Level
| High Schools | 3 |
| Middle Schools | 1 |
| Secondary Education | 1 |
Audience
Location
| South Korea (Seoul) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkMarvul, John N. – Urban Education, 2012
To assess whether a 5-month program involving attendance monitoring, sports participation, and a moral character class would reduce absenteeism, 40 students in a small transitional high school were randomly assigned to intervention and control groups and assessed pre- and postintervention on educational expectations, attitude toward education, and…
Descriptors: Control Groups, Intervention, Predictor Variables, Academic Aspiration
Lee, Jung; Cerreto, Frank A.; Lee, Jihyun – Educational Technology & Society, 2010
According to Ajzen's Theory of Planned Behavior (TPB), behavioral intention (BI) is predicted by attitude toward the behavior (AB), subjective norm (SN), and perceived behavioral control (PBC). Previous studies using the TPB to explain teachers' intentions to use technology have resulted in inconsistent findings. This inconsistency might be due to…
Descriptors: Intention, Educational Technology, Technology Integration, Computer Uses in Education
Ham, Ok Kyung; Lee, Young Ja – Journal of School Health, 2007
Background: Smoking is popular among Korean male high school adolescents, with the prevalence of 20.7% differing markedly with the type of school, being 16.3% and 27.6% in academic and vocational technical high schools, respectively. The purpose of this study was to identify significant variables that predict stages of smoking cessation among…
Descriptors: Vocational High Schools, Smoking, Metropolitan Areas, Predictor Variables
