Diversity of school dropouts. A typological approach - Blöndal, Kristjana Stella; Hafþórsson, Atli (Menntavísindasvið Háskóla Íslands, 2020)
School dropout is of great concern in Iceland. After completing compulsory education at age 16, most students transfer directly to upper secondary school. However, many drop out. At the age of 24 almost 40% have still to complete upper secondary school and this situation has not altered over the years. The group of students who drop out is both large and diverse. To date, research has not paid due attention to this fact, tending to treat dropouts as a homogenous group. Our research addresses such criticism by identifying different subgroups of young people who leave school before graduation.The results are drawn from an ongoing longitudinal research – School effectiveness and students’ educational progress - commencing in 2007 with a survey in all general upper secondary schools in Iceland. A total of 3,470 students aged 16 to 20 participated, followed over a seven-year period. We build on three different sources: A self-report questionnaire administered in upper secondary schools, registered data on educational trajectories and status at age 23 to 27, and standardized tests on academic achievement at the end of compulsory school at age 15.The typology is based on significant factors that contribute to early school leaving, i.e. students’ behavioral, emotional and cognitive engagement and emotional problems in upper secondary school, and academic achievement at the end of compulsory school. Student engagement is a key concept in theories and research on school dropout; leaving school is viewed as a long-term process of disengagement. Increasingly, emotional problems are receiving attention in this field of study, both because of the relation to school dropout and because young people’s mental health seems to be declining. Previous academic achievement is the single strongest predictor of school dropout.We conducted cluster analysis in two steps. First, we conducted hierarchical analysis using Ward’s method. Second, we used K-means cluster analysis to refine the fourcluster solution. We based the clustering on ...