14. Communities, Families and Schooling in Educational Research
Paper
Difference in Personal Characteristics and Attitudes Between High and Low Achievers in PIRLS2021
Kristine Kampmane, Andrejs Geske, Antra Ozola
University of Latvia, Latvia
Presenting Author: Kampmane, Kristine
The COVID-19 pandemic has brought many different changes in education. Outcomes of education have also been affected. IEA’s PIRLS2021 was the first of the large-scale international studies of education that measured 4th-graders’ reading literacy during and right after the pandemic. The results have brought surprises for many countries, for example, when compared with PIRLS2016, Finland has lost 17 score points (19 points since PIRLS2011) and there is also a decrease in average achievement scores for Latvia – a drop by 30 points since PIRLS2016. Some countries were not affected, for example, Ireland had gained 10 points since PIRLS2016 and 25 points since PIRLS2011; Lithuanian average achievement score had risen by 4 points since PIRLS2016 and 24 points since PIRLS2011 (Mullis et al., 2023). These four countries were selected for comparison because of their achievement characteristics – Finland was the top-performing EU country in PIRLS2011, and together with Ireland the top-performing countries from the EU in the PIRLS2016. In PIRLS2021 the roles in the international ranking table have changed - Ireland still being the first among EU countries, Latvia being the country with the largest achievement drop, Lithuania rising its achievement to the top 5 among EU countries, but Finland falling behind Lithuania.
The purpose of this study is to find out students’ personal, classroom, and home characteristics that differ between high and low-achieving students in all countries of comparison.
Previous studies have examined that student’s socioeconomic status (Eriksson et al., 2021; OECD, 2020a; Mullis et al., 2023) and intelligence (Roth et al., 2015; Kriegbaum et al., 2018) are the main factors influencing student’s achievement. Among the significant factors explaining achievement distribution often falls motivation (Mullis et al., 2023; Kriegbaum et al., 2018), attitude (Mullis et al., 2023), and confidence in reading or reading self-concept (Geske et al., 2021). It is common to address gender issues when researching reading achievement. There have been studies that claim that the gender gap in reading performance is present already upon students’ entry to school (Ferrer et al., 2015; Mesite, 2019). PIRLS and PISA studies provide evidence that girls outperform boys in reading in the majority of participating countries (OECD, 2020b; Mullis et al., 2023). At the same time – the gender effect on reading disabilities is questionable – some researchers conclude that males are more often diagnosed with reading disabilities (Berninger et al., 2008), but others argue that there are no differences (Shaywitz et al., 1990) or that females are just underdiagnosed (Limbrick et al., 2008; Quinn & Wagner, 2015).
Although PIRLS does not measure students’ intelligence or disabilities, other factors such as students’ personal, school, classroom, and home characteristics can be compared. The authors of this study compared the discrete values of following PIRLS2021 scales (Mullis et al., 2023):
- students’ sense of school belonging, bullying, engagement in reading lessons, and, disorderly behaviours in reading lessons as classroom factors,
- students like reading, students are confident in reading and performance in early literacy tasks as personal factors, and
- home resources for learning, socio-economic status, and parents like reading as students’ home factors.
The results of comparison showed the important role of the language students speak at home every day and their preschool education quality. On average only less than 2% of students who did not speak the language of test at home could perform at the advanced level. More than 90% of students in Ireland who performed at the advanced level before entering school recognized most letters in the alphabet very well, almost 60% of students could read a story and approximately 70% of students could write other words than their name.
Methodology, Methods, Research Instruments or Sources UsedIn this analysis all students were partitioned into the following groups according to PIRLS2021 reading assessment test results: advanced students (625 achievement points and above), and low-achievers (400 achievement points or less) as defined in PIRLS2021 methods and procedures (Wry et al., 2023). The following scales were used (Mullis et al., 2023) to compare percentages of low and high-achieving students:
- Students Like Reading – 10-item scale that measures students’ motivation. The scale was split into three levels: “Very much like reading”, “Somewhat like reading” and “Do not like reading”;
- Students Confident in Reading – 6-item scale that measures a student's distinct view of his/her reading ability. The scale was partitioned into three confidence levels: “Very confident”, “Somewhat confident” and “Not confident”;
- “Could Do Early Literacy Tasks When Beginning Primary School” scale – 6-item scale that indicates quality of kindergarten and early education. The scale was broken down into three proficiency levels: “Very well”, “Moderately well” and “Not well”;
- “Sense of School Belonging” scale – 5-item scale that measures levels of students’ connectedness with their school. The scale was partitioned into three levels of belonging: “High sense of school belonging”, “Some sense of school belonging” and “Little sense of school belonging”;
- “Students Engaged in Reading Lessons” scale – 9-item scale that measures students’ interaction with learning content. The scale was partitioned into three engagement levels: “Very engaged”, “Somewhat engaged”, “Less than engaged”;
- “Disorderly Behaviour During Reading Lessons” scale – 5-item scale that measures students’ behaviours in reading lessons and teacher’s classroom management. The scale was split into three engagement levels: “Few or no lessons”, “Some lessons”, “Most of the lessons”;
- “Student Bullying” scale – 10-item scale that measures repeated aggressive behaviours towards students from classmates. The scale was broken down into three bullying frequencies: “Never or almost never”, “About monthly”, “About weekly”;
- “Parents Like reading” – 9-item scale that measures parents as being role models for their children. Values were partitioned into three levels – “Very much like reading”, “Somewhat like reading” and “Do not like reading”;
All scales except the bullying scale were created from students’ and parents’ answers given in a 4-level Likert scale ranging from “Agree a lot” to “Disagree a lot”. The items in the bullying scale were presented in a 4-level frequency scale: “Never”, “A few times a year”, Once or twice a month”, “At least once a week”.
Conclusions, Expected Outcomes or FindingsIn all countries of comparison some traits were common. Analysis of students’ classroom factors has shown that all countries of comparison share:
- three (in Latvia, Lithuania) to six (Finland, Ireland) times more low-achieving students than advanced that had little sense of school belonging;
- approximately 1.5 (Ireland) to 5 (Latvia) times more low-achievers than advanced that were minimally engaged in reading lessons;
- approximately two (Finland) to six (Ireland) times more low-achieving students than advanced that reported their classmates had disorderly behaviour during most reading lessons;
- 12 (Ireland) up to 28 (Finland) times more low-achievers that were bullied about weekly;
Analysis of students’ personal factors have shown that although both groups share very similar distribution in “Students like reading” scale, it can be noted that more than 50% low-performing students (51% in Finland, 65% in Ireland, 67% in Latvia, and 73% in Lithuania) were not confident in their reading skills compared with less than 5% (1% in Finland, 2% in Ireland, 4% in Latvia, and 2% in Lithuania) advanced students who also were not confident in reading. More than 55% of advanced students entered school with early literacy skills (57% in Finland, 81% in Ireland, 77% in Latvia, and 65% in Lithuania) whereas less than 15% of low-performing students could demonstrate the same abilities (15% in Latvia, 13% in Ireland, 3% in Finland, and 0% in Lithuania).
Analysis of students’ home factors has shown that more than 30% (38% in Latvia, 53% in Lithuania, 55% in Ireland, and 57% in Finland) parents of advanced students like reading whereas more than 30% of low performing students’ parents do not like reading.
Thus, this study supports the body of research emphasizing the importance of preschool educational quality, family engagement and students' well-being at school.
ReferencesBerninger, V. W., Nielsen, K. H., Abbott, R. D., Wijsman, E., & Raskind, W. (2008). Gender differences in severity of writing and reading disabilities. Journal of school psychology, 46(2), 151-172
Eriksson, K., Lindvall, J., Helenius O., & Ryve A. (2021). Socioeconomic Status as a Multidimensional Predictor of Student Achievement in 77 Societies. Frontiers in Education, 6(731634)
Ferrer, E., Shaywitz, B. A., Holahan, J. M., Marchione, K. E., Michaels, R., & Shaywitz, S. E. (2015). Achievement gap in reading is present as early as first grade and persists through adolescence. The Journal of pediatrics, 167(5), 1121-1125
Geske, A., Kampmane, K., & Ozola, A. (2021). The Impact of Family and Individual Factors on 4th Grade Students’ Self-Confidence in Reading Literacy: Results From PIRLS2016. Society Integration Education Proceedings of the International Scientific Conference, 2, 203-213
Kriegbaum, K., Becker, N., & Spinath, B. (2018). The relative importance of intelligence and motivation as predictors of school achievement: A meta-analysis. Educational Research Review, 25, 120-148
Limbrick, L., Wheldall, K., & Madelaine, A. (2008). Gender ratios for reading disability: Are there really more boys than girls who are low-progress readers?. Australian Journal of Learning Difficulties, 13(2), 161-179
Mesite, L. (2019). Exploring Gender Differences in Children's Early Reading Development in the US. Harvard University
Mullis, I. V. S., von Davier, M., Foy, P., Fishbein, B., Reynolds, K. A., & Wry, E. (2023). PIRLS 2021 International Results in Reading. Boston College
OECD (2020a). Students’ Socio-economic Status and Performance, PISA-2018 Results (Volume II): Where All Students Can Succeed. OECD Publishing
OECD (2020b). Girls’ and boys’ performance in PISA, PISA-2018 Results (Volume II): Where All Students Can Succeed. OECD Publishing
Quinn, J. M., & Wagner, R. K. (2015). Gender differences in reading impairment and in the identification of impaired readers: Results from a large-scale study of at-risk readers. Journal of learning disabilities, 48(4), 433-445
Roth, B., Becker, N., Romeyke, S., Schäfer, S., Domnick, F., & Spinath, F. M. (2015). Intelligence and school grades: A meta-analysis. Intelligence, 53, 118-137
Shaywitz, S. E., Shaywitz, B. A., Fletcher, J. M., & Escobar, M. D. (1990). Prevalence of reading disability in boys and girls: Results of the Connecticut Longitudinal Study. Jama, 264(8), 998-1002
Wry, E., Fishbein, B. G., & Von Davier, M. (2023). Using Scale anchoring to interpret the PIRLS 2021 achievement results. In von Davier, M., Mullis, I. V. S., Fishbein, B., & Foy, P. (Eds.) Methods and procedures: PIRLS2021 technical report. Boston College
14. Communities, Families and Schooling in Educational Research
Paper
Addressing Entrenched Educational Inequalities through Research-Practice Partnerships: an Illustrative Case Study
Claire Forbes, Stephen Rayner, Kirstin Kerr, Mel Ainscow, Bee Hughes, Paul Armstrong
University of Manchester, United Kingdom
Presenting Author: Forbes, Claire;
Rayner, Stephen
Background and Objectives
The interplay between social background, educational attainment and life chances has long been an issue across Europe (d’Addio, 2007). Country-specific policy reform aimed at addressing inequities has largely failed to narrow educational gaps (Bénabou et al, 2009), which have become further entrenched by the socio-educational uncertainty engendered by national responses to Covid-19 (Blaskó et al, 2022). Social-reform policies have largely remained unchanged since the pandemic (Zancajo et al, 2022), causing concern for educational stakeholders who place equity at the heart of their practice.
However, there is cause for hope, where place-based approaches and local multi-disciplinary partnerships are developing in ways that prioritise equity in education. We refer to these approaches as research-practice partnerships (RPPs), a growing international movement (Coldwell et al, 2017; Farrell et al, 2022). RPPs tend to be situated within defined local contexts and grown through prolonged contact between school leaders, other educational stakeholders, local policymakers and researchers (Ainscow, 2023). Hence, they are well positioned to shape local enactments of national policy, and generate local policy endogenously, through sustainable relationships and mutual trust.
This paper presents an illustrative case of a developing RPP in NB, a defined area within a post-industrial town in the North of England. Poverty is high in NB, with 50% children living in low income families. It has therefore been identified as a site for a ‘cradle to career’ approach, emulating aspects of the Harlem Children’s Zone in the USA (Whitehurst & Croft, 2010) by ‘joining-up’ local service infrastructure in ways that holistically support local children’s educational journeys in their home, school and community contexts. The NB RPP is currently working with eight local schools, a multidisciplinary team, and multiple voluntary/community sector organisations.
Our objectives in presenting this case are to understand intra-/inter-organisational relationships within the complex socio-educational landscape of NB, and to evaluate to what extent, and how, these might need to be redefined for the future.
We argue that RPPs are well-positioned to reimagine community relationships in ways that cohesively unite community members, including families, schools and other education-related services and stakeholders. This entails blending local, endogenous knowledge of neighbourhoods and communities with researchers’ more exogenous knowledge. In so doing, we directly address the Network 14 call for contributions on school-community relationships, considering how RPPs can be initiated and sustained to foster the development of more inclusive communities, especially at a time of change and uncertainty.
Research Questions
- What are the educational opportunities and challenges in NB?
- How do local schools and education-related organisations work together within the NB cradle-to-career approach to address these educational opportunities and challenges?
Theoretical Framework
We draw upon Putnam’s (2000) conceptualisation of social capital as the ‘connections among individuals … social networks, and the norms of reciprocity and trustworthiness that arise from them’ (p. 19). These connections can be (i) bonding: the connections between local residents or intra-organisational actors, or (ii) bridging: the connections across and between diverse community members and inter-organisational actors. Mulford (2007) further proposes that social relationships can be understood as a resource to forge local policy and practice pathways, where reform agendas are filtered and enacted through the active participation of stakeholders in the local socio-educational landscape. He introduces a third form of social capital, that of linking: a relational pathway that unites communities, institutions and wider professional bodies in the creation of local, regional and national policy and practice. This is exemplified by the RPP (see also Ainscow, 2015, p. 3). Taken together, bonding, bridging and linking social capital provide a lens through which to understand the complex dynamics of NB’s socio-educational landscape.
Methodology, Methods, Research Instruments or Sources UsedOur research design, developed in conjunction with the multidisciplinary steering group in NB, aligns with the principles of design-based research approaches (DBRA), referred to as theory of change (ToC) (Kerr & Dyson, 2019). Our aim is to understand the ‘theory’ underpinning the initiative, before mapping this out and tracking its processes and outcomes over time within an RPP structure. The data reported here within our illustrative case were generated in the first stage of the ToC evaluation approach that we were commissioned in 2023 to conduct in NB, in order to explore the potential for collaborative, multi-disciplinary relationships based on current realities and future hopes.
Data Collection
We conducted 15 first-stage, scoping interviews, adopting a semi-structured format to enable robust, comparable data to be generated, while still allowing the researchers some flexibility to follow up emergent themes (Robson, 2011). Overall, our interviews were structured as follows:
• how do local professionals characterise the socio-educational landscape in NB;
• how do they feel the cradle-to-career approach is working and how might it be improved;
• what are future possibilities, hopes and priorities for the approach and the local area?
Interviewees were purposively sampled from a list of participating schools, charities, and other education-related, youth organisations. These included: local school leaders, special educational needs and disabilities (SEND) coordinators, charity and social workers, as well as key members from the steering group and community organising team. Interviews were conducted by the six-person research team, working in pairs. They took place online or face-to-face, at the convenience of the participants. All research instruments and schedules were approved by the University Ethical Committee.
Data analysis
Data were analysed thematically. The interview pairs engaged in initial work of transcription, digitising and first-cycle coding to analyse data in relation to concepts from the literature. This created the foundations for the entire research team to engage in second-cycle coding, i.e. a less formalised grounded analysis, incorporating more open descriptive coding, within a discussion-group format (Cohen et al, 2011).
Conclusions, Expected Outcomes or FindingsStrong bonds in a close community:
Marked by intergenerational unemployment through the demise of the shipping industry, a cornerstone of the local economy, NB is characterised as a socio-economically disadvantaged area across all measures. Nevertheless, bonding social capital between residents appears high, and there is a strong sense of community pride. Interviewees also mentioned a contradiction between deficit narratives around low aspiration, and their observations of families having high aspirations for their children, while being constrained by structural barriers, and resentful of the stigma attached to their community.
Successful literacy interventions offer only a partial solution:
Local schools have focused heavily – with considerable success – on improving literacy to improve access to curricula and career pathways. However, literacy is not considered a priority by some community organisations, where children’s mental health, especially following Covid-19 lockdowns, is considered more urgent. The lack of bridging social capital between organisations and individual actors results in different perceptions of educational, social and community priorities and of how the needs of the next generation can best be addressed.
Implications for the RPP:
Building bridging social capital that unites school and non-school actors is a crucial next step in the development of this RPP. Improving inter-organisational dialogue, facilitated by the research team, might enable consensus on how diverse stakeholders in the RPP might collectively shape a shared understanding of local policy enactment in holistic and joined-up ways. Doing so may pave the way towards linking social capital in the future and accord greater certainty to intra-/inter-organisational relationships in NB. This might begin the work of breaking the complex, and deeply entrenched, cycles of poverty and marginalisation that have blighted this community over time and have been exacerbated by the pandemic, offering a pathway to community autonomy, empowerment, and the fulfilment of high local aspirations.
References•Ainscow, M. (2015). Towards self-improving school systems: Lessons from a city challenge. Routledge.
•Ainscow, M. (2023). Research-practice partnerships: a strategy for promoting educational recovery. Revista Perspectiva Educacional, 62(1), 8-32.
•Bénabou, R., Kramarz, F., & Prost, C. (2009). The French zones d’éducation prioritaire: Much ado about nothing?, Economics of Education Review, 28 (3), 345-356. https://doi.org/10.1016/j.econedurev.2008.04.005
•Blaskó, Z., Costa, P. D., & Schnepf, S. V. (2022). Learning losses and educational inequalities in Europe: Mapping the potential consequences of the COVID-19 crisis. Journal of European Social Policy, 32(4), 361-375.
•Cohen, L., Manion, L., & Morrison, K. (2011). Research Methods in Education (7th ed.). London: Routledge.
•Coldwell, M., Greany, T., Higgins, S., Brown, C., Maxwell, B., Stiell, B., Stoll, L., Willis, B., & Burns, H. (2017). Evidence-Informed Teaching: An Evaluation of Progress in England. Research Report; Department for Education: London, UK.
•D'Addio, A. (2007). Intergenerational Transmission of Disadvantage: Mobility or Immobility Across Generations?, OECD Social, Employment and Migration Working Papers, No. 52, OECD Publishing, Paris, https://doi.org/10.1787/217730505550.
•Farrell, C. C., Penuel, W. R., Allen, A., Anderson, E. R., Bohannon, A. X., Coburn, C. E., & Brown, S. L. (2022). Learning at the Boundaries of Research and Practice: A Framework for Understanding Research–Practice Partnerships. Educational Researcher, 51(3), 197-208. https://doi.org/10.3102/0013189X211069073
•Kerr, K., & Dyson, A. (2019). Researching complex extended education initiatives in England: a design-based approach using theory of change. In S. H. Bae, J. L. Mahoney, S. Maschke, & L. Stecher (Eds.), International Developments in Research on Extended Education. Barbara Budrich Publishers.
•Mulford, B. (2007). Building social capital in professional learning communities: Importance, challenges and a way forward. In L. Stoll, & K. Seashore Louis (Eds.), Professional learning communities: divergence, depth and dilemmas (pp. 166–188). Open University Press.
•Putnam, R. D. (2000). Bowling alone: the collapse and revival of American community. New York: Simon & Schuster.
•Robson, C. (2011). Real world research (3rd ed.). Chichester, UK: Wiley.
•Whitehurst, G. J., & Croft. M. (2010) The Harlem Children’s Zone, promise neighborhoods, and the broader, bolder approach to education. Washington: The Brookings Institution.
•Zancajo, A., Verger, A., & Bolea, P. (2022). Digitalization and beyond: the effects of Covid-19 on post-pandemic educational policy and delivery in Europe, Policy and Society, Volume 41, 1(111–128), https://doi.org/10.1093/polsoc/puab016
14. Communities, Families and Schooling in Educational Research
Paper
Learners’ Location, School Socio-Economic Status and School Performance – A Scottish Case Study
Laurence Lasselle
University of St Andrews, United Kingdom
Presenting Author: Lasselle, Laurence
This paper examines academic performance at top grades in public examinations relative to the national average between Scottish state secondary schools mainly serving young people residing in remote communities. This examination allows me to explore:
(1) how academic performance in those schools compares to schools serving young people residing in more urban areas and
(2) whether academic performance in schools with significant proportions of learners experiencing socio-economic disadvantages is weaker.
School attainment in Scottish remote areas is lower than that observed in more urban areas (Lasselle & Johnson, 2021; Scottish government, 2021). These patterns are similar to those observed elsewhere in the UK, Europe, Australia or the United States of America (Echazarra and Radinger, 2019; Gagnon, 2022; Schmitt-Wilson and Byun, 2022; Schmitt-Wilson et al., 2018; Tomaszewski et al., 2020). They may explain why youth residing in these remote areas are less likely to progress to higher education.
This paper shows that these patterns characterising remote Scotland need nevertheless to be nuanced when secondary school statistics are considered. On the one hand, schools serving remote communities with similar socio-economic status, i.e. similar proportions of learners experiencing socio-economic disadvantages, may have large discrepancies in academic performance at top grades in public examinations relative to the national average. On the other hand, schools with similar academic performance may have different socio-economic status.
In its conclusion, the paper discusses why this contextualisation of academic performance in terms of learners’ location and schools’ socio-economic status is important for policymakers and communities in Scotland and elsewhere in Europe.
Methodology, Methods, Research Instruments or Sources UsedMy methodology builds on the methodologies developed by Lasselle and Johnson (2021), Lasselle et al. (2014), Roberts et al. (2021) and Thier et al. (2021). Each school is characterised by three dimensions: its remoteness, its socio-economic status and its academic performance. School statistics are compared and contrasted across these dimensions.
Briefly speaking, school remoteness is measured from the percentage of school learners residing in remote rural areas or remote small towns as per the rural-urban classification of the Scottish government. The socio-economic status of the school is determined from the socio-economic disadvantages experienced by its learners, either the percentage of learners registered on free-school meal, or that living in the poorest areas in Scotland as defined by the national socio-economic index of deprivation. The academic performance of a school is measured from the number of its learners achieving top grade in public examinations.
In practice, I proceed in two steps. First, I construct three binary indicators capturing each dimension from schools statistics released by the Scottish government. These indicators allow me to classify all schools in various categories. Second, I intersect the three indicators. This allows me to determine how many schools are within each category enabling me to compare and contrast the distribution of secondary schools according to their location, their socio-economic status and their academic performance compared to the national average.
The work is data-driven and Scottish-based. However, it can be replicated in many countries with standard rural/urban classification and schools statistics collection including their location. The choice of Scotland as a case study is motivated by three reasons. First, the location spectrum of school location is large. It includes remote island, large remote rural areas in the mainland, town in a remote areas allowing us to distinguish various types of communities. Second, measures of socio-economic deprivation at school level are publicly available. Third, the percentage of school leavers living in remote communities and progressing to HE is well below the national average.
Conclusions, Expected Outcomes or FindingsMy examination leads to two results.
First, remoteness may not always be linked to weaker academic performance.
Second, weaker academic performance is not always observed in schools with lower socio-economic status.
In summary, my paper highlights the importance to distinguish the various local factors determining school’s academic performance. However, it raises the issue of the role of the communities in access to higher education, in particular remote communities.
ReferencesAzano, A.P., Eppley, K., & Biddle C. (Eds) (2022). The Bloomsbury Handbook of Rural Education in the United States, Bloomsbury Academic.
Echazarra, A.,& Radinger, T. (2019). Learning in rural schools: Insights from Pisa, Talis and the literature. OECD Education Working Paper No. 196. OECD Publishing.
Gagnon, D.J. (2022). Student achievement in rural America, in Azano et al. (2022) pp. 215-224.
Lasselle, L., & Johnson, M. (2021). Levelling the playing field between rural schools and urban schools in a HE context: A Scottish case study. British Educational Research Journal, 47(2), 450-468. https://doi.org/10.1002/berj.3670
Lasselle, L., McDougall-Bagnall, J., & Smith, I. (2014). School grades, school context and university degree performance: Evidence from an elite Scottish institution. Oxford Review of Education, 40(3), 293-314. https://doi.org/10.1080/03054985.2014.900485
Roberts, P., Thier, M., & Beach, P. (2021). Erasing rurality: On the need to disaggregate statistical data. In P., Roberts, & M., Fuqua (Eds), Ruraling Education Research: Connections between Rurality and the Disciplines of Educational Research (pp. 107-127). Springer. https://doi.org/10.1007/978-981-16-0131-6
Scottish Government (2021). Rural Scotland: Key facts 2021. Scottish Government. https://www.gov.scot/publications/rural-scotland-key-facts-2021/
Schmitt-Wilson, S., Downey, J.A., & Beck, A.E. (2018). Rural educational attainment: The importance of context. Journal of Research in Rural Education, 33(1), 1-14.
Schmitt-Wison, S., & Byun, S. (2022). Postsecondary transition and attainment in Azano et al. (2022) pp. 157-164.
Thier, M., Beach, P., Martinez Jr., C. R., & Hollenbeck, K. (2020). Take care when cutting: Five approaches to disaggregating school data as rural and remote. Theory & Practice in Rural Education, 10(2), 63–84. https://doi.org/10.3776/tpre.2020.v10n2p63-84
Tomaszewski, W., Kubler, M., Perales, F., Clague, D., Xiang, N., & Johnstone, M. (2020). Investigating the effects of cumulative factors of disadvantage, Final Report.
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