Session Information
05 SES 09, Bullying, School Drop-out, and Addiction
Paper Session
Contribution
The main topic is dropout from upper secondary school in Norway, and the research aim is to illuminate differences in intentions to quit between boys and girls in two different educational lines: specialization in general studies and vocational studies – four groups in total. Although the study is focused towards the intention to quit, and not the actual action, research has shown, i.e. within the framework of “Theory of Planned Behavior” (Ajzen, 1991), that the intention to quit is a good indicator of actually dropping out of school (Davis, Ajzen, Saunders and Williams, 2002; Freeney and O'Connell, 2012).
The research is anchored in an ecological theoretical understanding of dropout as the endpoint of a long process where students gradually lose their school engagement (Rumerberger, 1987; 2011). From this perspective, both individual and institutional factors affect the decision. Individual aspects are associated with the student`s background, attitudes, behaviours, and performance. Institutional aspects are situated in three major contexts – families, schools and communities, and the several key features within them: composition, structure, resources and practices. In sum, this implies variables such as e.g. demographics, self-perceptions, social support, goal-structure, engagement, loneliness, coping etc. These are all appraised as possible protective- and/or risk-factors that are crucial to gain insight about, in order to understand the dropout-process. By mapping such factors and finding effective measures to reduce them, one can affect the students while they are still in school, instead of putting in measures after they have finished. Such an approach will provide a proactive and offensive approach to the problem.
Understanding the dropout-process is critical for informing efforts to address this educational problem. Dropping out of school has consequences for both the national socio-economics and, most importantly, the dropouts themselves. Dropouts face gloomy economic futures as they are the least educated workers in the labour market and thus have the poorest job prospects compared to more educated workers. Furthermore, research indicate that dropouts also have poorer mental and physical health and, as a result, have a more difficult and shorter life span compared persons with more education (Rumberger, 2011).
This paper will present findings and discuss the following research question: “What affects the student`s intentions to quit upper secondary school?” Based on a literature review I have formulated five hypotheses: The student`s intentions to quit school will be predicted by the students…:
- … social background and high school grades (Tinto, 1993)
- … experience of parental support (Malecki og Demary, 2002).
- … experience of teacher support and goal structure at the school (Malecki and Demary, 2002; Midgley et al., 2000)
- … school engagement and current grades (Fredricks, Blumenfeld og Paris, 2004)
- … experience of loneliness (Asher & Wheeler, 1985; Valås, 1999)
Method
A longitudinal design was used to investigate students in Norwegian upper secondary school. A cohort of 1695 students from 13 different upper secondary schools, 866 females (51,1%) and 829 males (48,9%), was followed through their first two years upper secondary school participation. The data that will be presented in this paper originates from two quantitative surveys, collected in the fall of 2015 and spring of 2017, respectively. Dependent variable: Intention to quit: 6 items (Valås, 2001). Example: "I often think I want to finish this school". A sum score was calculated by calculating the average of the statements. (α = 0.82.) Independent variables: Mother`s education level: 4 items. The lowest level indicates only primary school, the highest level is university education in excess of 3 years. This is the same scale that is used in the PISA questionnaire (OECD, 2009). Parental support: 6 items (Malecki & Demary, 2002). Example: "My parents are interested in my schoolwork" (α = 0.87). Teacher support: 4 items x 2 (Malecki and Demary, 2002). Examples: "I feel that my teachers care about me and I feel that my teachers treat me in a friendly way" (emotional support); "My teachers explain to me what I do not understand and my teachers continue to explain until I understand" (academic support). A factor analysis showed a clear one-factor structure, so a single scale for teacher support was made based on all 8 items. (α = 0.92). Goal structure: 4 items x 2 (Midgley et al., 2000). Examples: "What matters in our class is that we do as well as we can in the subjects" (learning-oriented) (α = 0.71). "The most important thing in our class is to get good grades" (performance-oriented) (α = 0.89). School engagement: operationalized as a multidimensional phenomenon involving both behavioral (effort and skipping school), emotional (internal motivation) and cognitive (coping competence) aspects. - Effort: 4 items. Example: "I work well with the tasks we get at school" (α = 0.78). - Skipping: One question: "How many times have you skipped school this year?" with the answer options: 1 = Never, 2 = 1-5, 3 = 6-10, 4 = Over 10. In the analyzes I will use this as a continuous variable. - Internal motivation: 4 items (Deci & Ryan, 1985; Vallerand et al., 1992). Example: "I think it's fun working with the subjects" (α = 0.90). - Coping competence: 5 items (Schroder and Ollis, 2013). Example: "I often feel I can`t solve my problems" (α = 0.86). Loneliness: 4 items (Valås, 1999). Example: "I do not have any friends at school" (α = 0.86).
Expected Outcomes
In order to ensure the validity of the variables measured with multiple claims, I initially ran exploratory factor analyzes. To determine the extent to which the independent variables predicts the dependent variable Intention to quit, I used hierarchical regression (Wampold & Freund, 1987), which is a form of regression analysis where the independent variables are added in phases based on a theoretical model. I added the five-step variables corresponding to the hypotheses of the study. In this manner, I will test how much variance in the dependent variables the independent variables in each step explain beyond those that were added to the previous steps. I will also get a picture of how much each of the hypotheses contributes beyond the foregoing. Before I ran the regression, I conducted a descriptive analysis of all variables. I will present these findings on what different factors that leads to this intention between the four groups. In further research, these findings will be used to analyse further whether there are systematic differences between student needs. Results from preliminary analysis show that students' engagement to school, and their experience of support from parents and teachers, are important explanatory factors. Loneliness at secondary school and students ' ability to cope with stressful life events seems to be the two most important predictive factors in relation to the students' thoughts about leaving.
References
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. Asher, S.R. & Wheeler, V.A. (1985). Children's loneliness: a comparison of rejected and neglected peer status, Journal of Consulting and Clinical Psychology, 53, 500-505. Davis, L. E., Ajzen, I., Saunders, J. & Williams, T. (2002). The decision of African American students to complete high school: An application of the theory of planned behavior. Journal of Educational Psychology, 94(4), 810-819. Deci, E.L. & Ryan, R.M. (1985). Intrinsic motivation and self-determination in human behavior. New York: Plenum. Fredricks, J.A., Blumenfeld, P.C. & Paris, A.H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74, 59-109. Freeney, Y. & O'Connell, M. (2012). The predictors of the intention to leave school early among a representative sample of Irish second-level students. British Educational Research Journal, 38(4), 557-574. Malecki, C. K. & Demary, M. C. (2002). Measuring perceived social support: Development of the Child and Adolescent Social Support Scale (CASS). Psychology in the Schools, 39(1), 1- 18. Midgley, C., Maehr, M.L., Hruda, L.Z. Anderman, E. Anderman, L., Freeman, K.E., Gheen, M., Kaplan, A., Kumar, R., Middleton, M.J., Nelson, J., Roeser, R. og Urdan, T. (2000). Manual for the Patterns of Adaptive Learning Scales. The University of Michigan. OECD (2009). OECD Programme for International Student Assessment, Studentsquestionnaire Paris: OECD. Rumberger, R.W. (1987). High school dropouts: A review of issues and evidence. Review of Educational Research, 57, 101-127. Rumberger, R.W. (2011). Dropping out. Why students drop out of high school and what can be done about it. Harvard University Press. Schroder, K.E.E. & Ollis, C.L. (2013). The coping competence questionnaire: a measure of resilience to helplessness and depression. Motivation and Emotion, 37, 286-302. Tinto, V. (1993). Leaving College: Rethinking the Causes and Cures of Student Attrition, 2. utgave. Chicago: University of Chicago Press. Vallerand, R.J., Pelletier, L.G., Blais, M.R., Briere, N.M., Senecal, C. & Vallieres, E.F. (1992). The academic motivation scale: A measure of intrinsic, extrinsic, and amotivation in education. Educational and Psychological Measurement, 52, 1003-1017. Valås, H. (1999). Students with learning disabilities and low-achieving students: Peer acceptance, loneliness, self-esteem, and depression, Social Psychology of Education, 3, 173-192. Wampold, B.E. & Freund, R.D. (1987). Use of multiple regression in counseling psychology: A flexible data-analytic strategy. Journal of Counselling Psychology, 34(4), 372-382.
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