09 SES 08 D JS, School Evaluations
Joint Paper Session NW 09 and NW 11
With much of the literature on school self-evaluation (SSE) stressing the importance of data use, this paper explores how teachers in Irish post-primary schools are coming to terms with this new challenge. Since 2012, all schools in Ireland are required to engage in SSE for the purpose of improving student outcomes. For the first time, teachers and school leaders are being asked to systematically gather and analyse various types of data, devise improvement plans and implement improvements. Despite such demands, the compulsory education system in Ireland operates within a low-stakes accountability environment, with an absence of published school league tables and no consequences for poor school performance. It is also interesting to explore the introduction of a school improvement process that requires data as evidence for self-evaluation, but where very little data currently exists compared to other jurisdictions and where the discourse of data use in schools is relatively new.
This paper outlines the experience of 13 post-primary schools that were supported by the Dublin city University, Centre for Evaluation, Quality and Inspection to complete an SSE process, during which, each school gathered and analysed a range of data. This study is part of a larger action research project which explores various aspects of the implementation of SSE in schools, including models of support and continuing professional development for schools. This paper looks specifically at the use of data by the schools involved. The key research questions ask: what data was gathered by the schools and what was the attitude to and experience of data-use among teachers? In doing so, this article explores some of the current research questions in relation to data use in schools.
This research is part of a larger action research project which is taking place over a number of years. The current research used questionnaires to establish prior experience of SSE and data use. Following the SSE process in each school, questionnaires were used to identify the types of data used by schools for school self-evaluation. Focus groups were used to explore attitudes of participants to data use in schools.
Overall, the findings indicate that schools gathered a range of data, which was mainly quantitative due to a focus on quantitative target setting. The types of data used by each school is outlined. Despite a generally positive attitude to the usefulness of data and the skills learned, participants did not appear convinced that they would be involved in data use on an ongoing basis and questioned the need for teachers to develop data literacy. Teachers suggested that data use may be more relevant for management or an individual/ who is allocated responsibility for gathering and analysing data at a school level. Concerns were raised in relation to the use of data for accountability and inspection purposes. Participants were not confident that the actions plans that resulted from the school self-evaluation process, would be implemented.
Anderson, S., Leithwood, K., & Strauss, T. (2010). Leading data use in schools: Organizational conditions and practices at the school and district levels. Leadership and Policy in Schools, 9, 292- 327. Beaver, J.K., and Weinbaum, E.H. (2015). State test data and school improvement efforts. Educational Policy. 29 (3), 478-503. BERA/ RSA. (2014). Research and the teaching profession: building the capacity for a self-improving education system. London. Retrieved from: https://www.bera.ac.uk/project/research-and-teacher-education Bernhardt, V.L. (2013). Data analysis for continuous school improvement (3rd ed). New York, NY: Routledge Demski, D. ( 2014 ), Which data do principals and teachers use to inform their practice? Evidence from Germany with a focus on the influence of school culture. In A.J. Bowers, A.R. Shoho, B. G. Barnett (Eds.) Using Data in Schools to Inform Leadership and Decision Making (p.1-16). Charlotte, NC: Information Age Publishing Inc. Ebbeler, J., Poortman, C., Schildkamp, K., & Pieters, J. (2016). Effects of a data use intervention on educators’ use of knowledge and skills. Studies in Educational Evaluation, 48, 19-31. Farrell, C. 2015. Designing School Systems to Encourage Data Use and Instructional Improvement. Educational Administration Quarterly . Vol 51, Issue 3, pp. 438 - 471 Farrell, C.C., & Marsh, J. A. (2016). Contributing conditions: A qualitative comparative analysis of teachers’ instructional responses to data. Teaching and Teacher Education. 60, 398-412. Ikemoto, G.S., & Marsh, J. A. (2007). Cutting through the “data-driven” mantra: Different conceptions of data-driven decision making. In P.A. Moss (Ed.), Evidence and decision making (p. 74-104). Malden, MA: Blackwell. Kelly, A., and Downey, C. (2011). Professional attitudes to the use of pupil performance data in English secondary schools. School Effectiveness and School Improvement. 22 (4),415-437. Lai, M. K., & Schildkamp, K. (2013). Data-based decision making: an overview. In K. Schildkamp, & M. K. Lai (Eds.), Data-driven decision making in education: challenges and opportunities (p.9-12).Dordrecht, Netherlands: Springer. Mandinach, E. B., & Gummer, E.S. (2016). What Does It Mean for Teachers to Be Data Literate: Laying out the Skills, Knowledge, and Dispositions. Teaching and Teacher Education, 60, 366–376. Mandinach, E. B., & Gummer, E.S. (2013). Defining data literacy: A report on a convening of experts. Journal of Educational Research and Policy Studies, 13(2), 6-28. Schildkamp, K., Karbautzki, L., & Vanhoof, J. (2014). Exploring data use practices around Europe: Identifying enablers and barriers. Studies in Educational Evaluation, Volume 42, 15-24.
00. Central Events (Keynotes, EERA-Panel, EERJ Round Table, Invited Sessions)
Network 1. Continuing Professional Development: Learning for Individuals, Leaders, and Organisations
Network 2. Vocational Education and Training (VETNET)
Network 3. Curriculum Innovation
Network 4. Inclusive Education
Network 5. Children and Youth at Risk and Urban Education
Network 6. Open Learning: Media, Environments and Cultures
Network 7. Social Justice and Intercultural Education
Network 8. Research on Health Education
Network 9. Assessment, Evaluation, Testing and Measurement
Network 10. Teacher Education Research
Network 11. Educational Effectiveness and Quality Assurance
Network 12. LISnet - Library and Information Science Network
Network 13. Philosophy of Education
Network 14. Communities, Families and Schooling in Educational Research
Network 15. Research Partnerships in Education
Network 16. ICT in Education and Training
Network 17. Histories of Education
Network 18. Research in Sport Pedagogy
Network 19. Ethnography
Network 20. Research in Innovative Intercultural Learning Environments
Network 22. Research in Higher Education
Network 23. Policy Studies and Politics of Education
Network 24. Mathematics Education Research
Network 25. Research on Children's Rights in Education
Network 26. Educational Leadership
Network 27. Didactics – Learning and Teaching
The programme is updated regularly (each day in the morning)
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.