Conference Agenda
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09 SES 07 C: Student Well-Being, Inclusion and Equity in Assessment Outcomes
Paper Session | ||
| Presentations | ||
09. Assessment, Evaluation, Testing and Measurement
Paper Adolescent Well-Being Across Educational Transitions: A Longitudinal Study University of Gothenburg, Sweden Presenting Author:A growing body of research and official reports has documented a negative trend in the well-being of children and young people (Inchley et al., 2020; Public Health Agency of Sweden, 2014, 2018). However, far less is known about how well-being develops within individuals over time, particularly across key educational transitions such as the move from lower to upper secondary school. Longitudinal research examining multiple dimensions of well-being during adolescence is therefore needed to generate deeper insights that can inform interventions aimed at promoting children’s and young people’s well-being. Supporting this perspective, a systematic review by Donaldson et al. (2023) shows that challenges encountered during transitions between educational stages can have long-lasting effects on academic achievement, self-concept, and trajectories of well-being and health. The authors further emphasize that interventions designed to enhance student well-being should prioritise strengthening relationships among parents, teachers, and peers, as these social connections are critical to their effectiveness. Given that children and adolescents spend a substantial proportion of their time in school during compulsory education, it is reasonable to assume that changes in well-being are closely linked to school-related factors (Högberg et al., 2019), as well as to individual characteristics. In the present study, we focus on three central dimensions of well-being: social, psychological, and psychosomatic. Although these dimensions do not capture all aspects of children’s and adolescents’ well-being and mental health, they are widely recognised in the literature as core components. Social well-being concerns supportive and functional interpersonal relationships, with difficulties in this domain linked to social isolation (Pollard & Lee, 2003). Psychological well-being reflects emotional stability and life satisfaction, characterised by low levels of stress and worry. Psychosomatic well-being captures physical symptoms arising from psychological strain, such as headaches, stomach pain, and sleep disturbances (National Agency of Public Health, 2018). The primary aim of the study was to examine intraindividual development in social well-being, psychological and psychosomatic ill-being over time. This was accomplished using longitudinal data collected at three time points, spanning the transition from lower to upper secondary school (Grades 6, 9, and 12), for a nationally representative cohort of students born in 2004. The study addressed the following research questions:
Methodology, Methods, Research Instruments or Sources Used In this study, we draw on data from the Swedish longitudinal project Evaluation through Follow-Up (UGU) which consists of representative samples from 11 birth cohorts, born approximately every sixth year between 1948 and 2016. Each sample is about 10% of the population. In the present study, a sample of the birth cohort born in 2004 was analysed when the students attended their sixth (age 12-13), ninth (age 15-16), and twelfth (age 18-19) year of schooling. The sample was drawn when students were in the third grade (age 9-10), using a two-stage stratified procedure. First drawing municipalities and then schools. The total sample consisted of 9,775 students, but with missing observations considered, N = about 5,000 in sixth grade, N = about 2,500 in ninth grade, and N = about 2,000 in twelfth grade. As a first step, an unconditional model was specified for each factor (social well-being and psychological and psychosomatic ill-being), examining the mean change over time. A conditional model was then specified for each factor, including independent time-invariant variables that potentially could explain the growth trajectories of social well-being and psychological and psychosomatic ill-being. Three latent variables were included in the study, each measured on three occasions (in Grades 6, 9, and 12). Three time-invariant manifest variables (GPA, gender, and parental education) were also included. Descriptive statistics, measurement invariance and Confirmatory factor analysis (CFA) were conducted. To examine changes in students’ well-being and ill-being over time, latent growth curve modelling was applied. These models allow us to examine changes in longitudinal data over time by defining one latent intercept variable and one latent slope variable with data from each measurement occasion as indicators (Little, 2024). As a first step, an unconditional model was specified for each factor (social well-being and psychological and psychosomatic ill-being), examining the mean change over time. A conditional model was then specified for each factor, including independent time-invariant variables that potentially could explain the growth trajectories of social well-being and psychological and psychosomatic ill-being. Conclusions, Expected Outcomes or Findings One of the main findings of the study was a statistically significant intraindividual decline in well-being and mental health over time. Social well-being, reflected in satisfaction with social relationships at school, decreased across the study period, while psychological and psychosomatic ill-being increased. Specifically, students reported growing levels of low mood, irritation, and sadness, as well as increasing problems related to stomachaches and sleep disturbances. Gender and parental education emerged as important correlates of these developmental patterns. Compared with boys, girls reported lower levels of social satisfaction at school and consistently higher levels of psychological ill-being throughout both lower and upper secondary school. Girls also experienced more psychosomatic complaints, including headaches, stomachaches, and sleep problems, with these gender differences widening over time. In addition, students from families with lower levels of parental education reported persistently higher levels of psychological and psychosomatic ill-being compared with peers from more highly educated families. Taken together, the findings suggest that girls and students from families with lower educational backgrounds are at heightened risk of declining well-being and mental health throughout their school years. References Donaldson, C., Moore, G., & Hawkins, J. (2023). A Systematic Review of School Transition Interventions to Improve Mental Health and Wellbeing Outcomes in Children and Young People. School Mental Health, 15, 19-35. Hogberg, B., Lindgren, J., Johansson, K., Strandh, M., & Petersen, S. (2019). Consequences of school grading systems on adolescent health: Evidence from a Swedish school reform. Journal of Education Policy, 34, 1–23. Inchley, J., Currie, D., Budisavljevic, S., Torsheim, T., Jastad, A., Cosma, A., Kelly, C., Arnarsson, A. M., & Samdal, O. (2020). Spotlight on adolescent health and well-being. Findings from the 2017/2018 Health Behaviour in School-aged Children (HBSC) survey in Europe and Canada. International report. Copenhagen: WHO Regional Office for Europe. Little, T. D. (2024). Longitudinal structural equation modeling (2nd ed.). New York: The Guilford Press. Pollard, E. L., & Lee, P. D. (2003). Child well-being: A systematic review of the literature. Social Indicators Research, 61(1), 59–78. Public Health Agency of Sweden. (2014). Health behavior in school-aged children. The Public Health Agency of Sweden. Public Health Agency of Sweden. (2018). Varför har den psykiska ohälsan ökat bland barn och unga i Sverige? Utvecklingen under perioden 1985–2014. The Public Health Agency of Sweden. 09. Assessment, Evaluation, Testing and Measurement
Paper Predictors of Academic Performance Among Students with an Immigration Background: A Systematic Literature Review Tampere University, Finland Presenting Author:During the recent years, the difference between native students and students with an immigration background in educational assessment studies have provoked public discussion in many countries around the world. In Finland, this performance gap has been particularly large (OECD 2019; 2023) and research initiatives have been launched to study the reasons behind it. Earlier international research has shown that performance differences are often explained by differences in socioeconomic background (e.g. Dai et al. 2023; Ziegler, Luo & Stoege 2023; Kirjavainen & Pulkkinen 2017), deficits in the language of instruction (Schnepf 2007), gender (Karakaus, Courtney & Aydin 2023) and reading fluency (Pulkkinen et al. 2024). For first generation immigration students, the results have also been predicted by the age of arrival in the country (Pulkkinen et al. 2024). In addition, there is evidence that students’ effort measured by time spent on assessment is strong factor explaining the academic performance of students with an immigration background (Agirdag & Vanlaar 2016). However, in any assessment studies, student performance is simultaneously influenced by many kinds of factors, and there is clear a lack of research gathering systematically together evidence on the factors explaining the gap. Therefore, the aim of this study was to conduct a systematic literature review on empirical research on the factors predicting the learning outcomes of students with immigrant background.
As we were interested in the interplay of factors at different levels in explaining learning outcomes, we chose Bronfenbrenner’s (1988) ecological systems theory as our framework. The theory implies that human development is influenced by interconnected layers, the so-called micro, meso, exo and macrosystems (complemented by chronosystem, which, however, will not be addressed in the present study). At the micro level, development is influenced by the person’s immediate social environments (e.g., family, classmates and classroom activities, friends), which are also influencing each other (mesosystem). In the context of this study, the exo level refers to for instance local level education policies, practices and cultures, which influence the circumstances (e.g., class composition and school segregation) and practical teaching arrangements shaping the learning situations. The broader cultural values, ideologies and for instance national legislation influencing educational goals and implementation of education are considered here as representing macrosystems. Within this framework, the research questions of the study were:
Methodology, Methods, Research Instruments or Sources Used According to the PRISMA guidelines (Page et al. 2021), we conducted a systematic literature review to identify empirical studies examining factors predicting the academic performance of students with an immigration background. The review consisted of international peer-reviewed studies published between January 2000 and April 2024. Only studies published in English were included. A comprehensive literature search was carried out using the EBSCO and PROQUEST databases, restricted to education-related databases within these platforms. The search was conducted across the full text of the articles using the following search string: ("learning outcome" OR "learning achievement") AND ("immig*" OR "foreign born*”) **. The initial search yielded 3,348 records. After removing duplicates, titles and abstracts were screened based on predefined inclusion and exclusion criteria. Studies were included if they (a) focused on primary or secondary school students with an immigration background, (b) measured academic performance using a cognitive test or standardized assessment, and (c) analysed predictors of academic performance using quantitative or mixed methods approaches. Studies were excluded if they focused on Indigenous peoples or exchange students, examined perceptions or attitudes without linking them to measured learning outcomes, were not related to education or training, were conducted during the COVID-19 pandemic, or were literature reviews, conceptual papers, or methodological studies. Following title and abstract screening, full-text articles were assessed for eligibility. This process resulted in a final sample of 45 empirical studies included in the review. The study selection process followed the PRISMA flow diagram, documenting each stage of identification, screening, eligibility, and inclusion. Data extraction was conducted using a structured coding framework. From each included study, information was extracted on publication year, country or region, educational level, academic domain, operationalisation of immigration background, outcome measures, and predictors of academic performance. The extracted predictors were analysed using a theory-driven qualitative content analysis (Elo & Kyngäs 2008) guided by Bronfenbrenner’s bioecological systems theory (Bronfenbrenner 1988). Predictors were categorised into micro-, meso-, exo- and macro-levels according to the level at which they were described as influencing students’ learning outcomes. The coding process was iterative, allowing refinement of categories as analysis progressed (Elo & Kyngäs 2008). When predictors could plausibly be assigned to multiple ecological levels, classification decisions were guided by the primary level of influence emphasised in the original study. Due to heterogeneity in study designs, outcome measures, and analytical methods, the results were synthesised narratively rather than through meta-analytic techniques (Higgins et al. 2023). Conclusions, Expected Outcomes or Findings The results indicate that the learning outcomes of students with an immigration background are shaped by an interplay of individual-, family-, classroom-, school- and country-level predictors. The included studies were predominantly conducted in Europe (42%) and North America (36%), with fewer studies originating from Asia, Australia, or international comparative contexts. Most studies focused on lower secondary education (53%) and primary education (31%), while upper secondary education was only marginally represented. In terms of academic domains, most studies examined academic performance in mathematics (27%), reading literacy (22%), or a combination of literacy and mathematics (29%). Fewer studies addressed outcomes in science or multiple subject areas simultaneously. Immigration background was most operationalised using students’ country of birth (58%), followed by language-related indicators (20%), while race-based definitions were less frequently applied. The findings were analysed using Bronfenbrenner’s bioecological systems theory, categorising predictors across micro-, meso-, exo- and macro-levels. At the micro-level, individual student characteristics (e.g. gender, motivation) were frequently associated with academic performance. Meso-level factors included family background and home–schoolinteractions, while exo-level factors encompassed school-level characteristics (e.g. school resources), and macro-level factors related to national contexts (e.g. integration policies). References Agirdag, O. & Vanlaar, G. (2016). Does more exposure to the language of instruction lead to higher academic achievement? A cross-national examination. International Journal of Bilingualism 22 (1), 123–137. https://doi.org/10.1177/13670069166587 Bronfenbrenner, U. (1988). Interacting systems in human development. Research paradigms: present and future. In N. Bolger, A. Caspi, G. Downey and M. Moorehouse (eds.) Persons in context: Developmental processes. Cambridge University Press. p. 25–49. Dai, S., Hao, T., Ardasheva, Y., Ramazan, O., Danielson, R. W., & Austin, B. (2023). PISA reading achievement: identifying predictors and examining model generalizability for multilingual students. Reading and Writing, 36(10), 2763–2795. https://doi.org/10.1007/s11145-022-10357-4 Elo S., Kyngäs H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107–115. https://doi.org/10.1111/j.1365-2648.2007.04569.x Higgins, J. P. T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. A. (Eds.). (2019). Cochrane Handbook for Systematic Reviews of Interventions. Wiley. https://doi.org/10.1002/9781119536604 Karakus, M., Courtney, M., & Aydin, H. (2023). Understanding the academic achievement of the first- and second-generation immigrant students: a multi-level analysis of PISA 2018 data. Educational Assessment, Evaluation and Accountability, 35(2), 233–278. https://doi.org/10.1007/s11092-022-09395-x Kirjavainen, T., & Pulkkinen, J. (2017). Takaako samanlainen tausta samanlaisen osaamisen? Maahanmuuttajataustaisten ja kantaväestön oppilaiden osaamiserot PISA 2012 -tutkimuksessa [Does a similar background guarantee similar performance? Differences in achievement between majority students and students with an immigration background in PISA 2012]. Kasvatus, 48(3), 189–202. https://jyx.jyu.fi/jyx/Record/jyx_123456789_66438 Page M. J., McKenzie J. E., Bossuyt P. M., Boutron I., Hoffmann T. C., Mulrow C. D., Shamseer L., Tetzlaff J. M., Akl E. A., Brennan S. E., Chou R., Glanville J., Grimshaw J. M., Hróbjartsson A., Lalu M. M., Li T., Loder E. W., Mayo-Wilson E., McDonald S., . . . Moher D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(71), 1–9. https://doi.org/10.1136/bmj.n71 Pulkkinen, J., Kauppinen, H., Hiltunen, J., Lehtola, P., Nissinen, K., & Rautopuro, J. (2024). Tukea tasa-arvoiselle koulutielle: maahanmuuttajataustaisten nuorten osaaminen PISA 2022 -tutkimuksessa [Supporting an equitable educational pathway: The competencies of students with an immigration background in PISA 2022]. Tutkimuksia / Koulutuksen Tutkimuslaitos, 39. https://doi.org/10.17011/ktl-t/39 Schnepf, S.V. (2007). Immigrants’ educational disadvantage. An examination across ten countries and three surveys. Journal of Population Economics, 20(3), 527–545. Ziegler, A., Luo, L., & Stoeger, H. (2023). Equity Gaps in Literacy among Elementary School Students from Two Countries: The Negative Social Resonance Effect of Intersectional Disadvantage and the Dampening Effect of Learning Capital. Education Sciences, 13(8), 827. https://doi.org/10.3390/educsci13080827 | ||