028214 Understanding and Using Educational Data

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2024 is available in the Archives.

Description

This subject is designed to provide students with a knowledge base and practical understanding of why and how student data is used in their area of specialisation in school education. It provides a foundation for a working understanding of contextual factors, policy expectations and collaborative work that enable practicing teachers to source and use data to inform the development of their teaching practices and student learning. The emphasis in this subject on data-based decision making and planning in schools is approached using a self-directed case-study investigation to consider what practicing teachers do to collect, interpret, and work with data.
Students plan and carry out an assessed Independent Investigation Project during Professional Experience to investigate how student data is collected, understood, and used in their area of specialisation during placement. This provides the basis for the final Assessment Report to both critically discuss observations of how and why teachers currently use data as well as justify the potential and limitations of data-driven decision-making for teachers’ professional learning and practice development.

Teaching and learning strategies

This subject is presented as weekly tutorial workshops that are designed as three learning phases over a nine-week teaching session where students customise their learning to suit their area of teaching specialisation. By using a collaborative workshop process, students are guided through a range of evidence-informed teaching and learning strategies with multiple opportunities to investigate, discuss, and interact with the literature. Each subject phase examines key concepts, perspectives and subject content. Students explore and develop connections with other students in professional learning groups (PLG) to actively engage with practical examples of using data, and share their developing knowledge using multi-modal representations, critical dialogues, group workshops and assessment task responses.

Content (topics)

The students will learn:

1. To explore substantive content about assessment practices, school data-informed decision-making and data-based teaching practices (SLO a,b,d)
2. To plan, accomplish and reflect on learning about data in schools from engagement with relevant literature, placement observations, and semi-structured interviews with practicing teachers (relating to SLO a,b,c)
3. To analyse and critically discuss case studies in specialisation groups to identify the potentials and limitations of data-driven decision making in the current conditions brought by local initiatives and school development projects (SLO b,d,f)
4. To use appropriate academic genres and conventions (SLO d,e,f).

Required texts

Required readings and other recommended readings and learning resources will be available via UTS Library and UTS Online.

References

Andrews, D., & Abawi, L. (2016). Three-dimensional pedagogy: A new professionalism in educational contexts. Improving Schools, 20(1), 76–94.

Carter, D., Manuel, J., & Dutton, J. (2018). How do secondary school English teachers score NAPLAN?: A snapshot of English teachers' views. Australian Journal of Language and Literacy, The, 41(3), 144-154.

Centre for Educational Statistics and Evaluation. (2017). Report of the Evaluation of the NSW Literacy and Numeracy Action Plan 2012 – 2016. Sydney, NSW: CESE.

Chick, H., & Pierce, R. (2013). The statistical literacy needed to interpret school assessment data. Mathematics Teacher Education & Development. 15(2), 1-19.

Daffern, T., Mackenzie, N. M., & Hemmings, B. (2018). Testing spelling: How does a dictation method measure up to a proofreading and editing format?. Australian Journal of Language & Literacy. 40(1), 28-45.

Feez, S., & Cox, R. (2017). Understanding research and evidence. PETAA Paper 209.

Hamilton, M., Maddox, B., & Addey, C. (Eds.). (2015). Literacy as numbers: Researching the politics and practices of International literacy assessment. Cambridge, UK: Cambridge University Press.

Hardy, I. (2013). Testing that counts: Contesting national literacy assessment policy in complex schooling settings. Australian Journal of Language & Literacy, 36(2), 67-77.

Harris, P., Chinnappan, M., Castleton, G., Carter, J., De Courcy, M., & Barnett, J. (2013). Impact and consequence of Australia's National Assessment Program-Literacy and Numeracy (NAPLAN): Using research evidence to inform improvement. TESOL in Context, 23(1/2), 30 – 52.

Johnston, J. (2016). Australian NAPLAN testing: In what ways is this a ‘wicked’ problem?. Improving Schools. 20(1) 18–34.

Karagiorgi, Y., Nicolaidou, M., Yiasemis, C., & Georghiades, P. (2015). Emergent data-driven approaches to school improvement: The journey of three schools through self-evaluation. Improving Schools, 18(1), 69 – 82.

Kippers, W. B., Poortman, C. L., Schildkamp, K., & Visscher, A. J. (2018). Data literacy: What do educators learn and struggle with during a data use intervention?. Studies in Educational Evaluation, 56, 21-31.

Krumm, A., Means, B., & Bienkowski, M. (2018). Learning analytics goes to school: A collaborative approach to improving education. New York, NY: Routledge.

Ladwig, J. G., & Luke, A. (2014). Does improving school level attendance lead to improved school level achievement? An empirical study of indigenous educational policy in Australia. The Australian Educational Researcher, 41(2), 171-194.

Lewis, S., & Hogan, A. (2016): Reform first and ask questions later? The implications of (fast) schooling policy and ‘silver bullet’ solutions. Critical Studies in Education, DOI: 10.1080/17508487.2016.1219961.

Lindgard, B., Thompson, G., & Sellar, S. (2016). National testing in schools. An Australian assessment. New York, NY: Routledge.

Love, N. (2017). Data literacy for teachers. Retrieved from Hawker Brownlow Education website: http://files.hbe.com.au/samplepages/NPR8884.pdf

Mandinach, E. B., Parton, B. M., Gummer, E. S., & Anderson, R. (2015). Ethical and appropriate data use requires data literacy. Phi Delta Kappan, 96(5), 25-28.

Maddox, B. (Ed.). (2018). International large-scale assessments in education: Insider research perspectives. London: Bloomsbury.

Mandinach, E. B., & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30-37.

McDonald, J. P., Isacoff, N. M., & Karin, D. (2018). Data and teaching: Moving beyond magical thinking to effective practice. New York, NY: Teachers College Press.

Meyer, H.-D., & Benavot, A. (Eds.). (2013). PISA, power and policy: The emergence of global educational governance. Oxford, UK: Symposium Books.

Mills, K. A. (2008). Will large-scale assessments raise literacy standards in Australian schools? The Australian Journal of Language and Literacy, 31(3), 211-225.

Polesel, J., Rice, S., & Dulfer, N. (2014). The impact of high-stakes testing on curriculum and pedagogy: A teacher perspective from Australia. Journal of Education Policy, 29(5), 640-657.

Roberts-Holmes, G., & Bradbury, A. (2016). The datafication of early years education and its impact upon pedagogy. Improving Schools, 19(2), 119 – 128.

Sampaio, M., & Leite, C. (2017). From curricular justice to educational improvement: What is the role of schools’ self-evaluation? Improving Schools, 20(1), 62 – 75.

Scanlon, S. (2012). ‘Why didn’t they ask me?’: Student perspectives on a school improvement initiative. Improving Schools. 15(3), 185–197.

Sellar, S. (2015). A feel for numbers: affect, data and education policy. Critical Studies in Education, 56(1), 131-146.

Tasmanian Department of Education. (2016). Good teaching: Data literacy. Retrieved from www.education.tas.gov.au/intranet/

White, P., & Anderson, J. (2012). Pressure to perform: Reviewing the use of data through professional learning conversations. Mathematics Teacher Education & Development. 14(1), 60-77.

Wrigley, T. (2015). Evidence-based teaching: Rhetoric and reality. Improving Schools, 18(3) 277–287.

Websites

ABS – Australian Bureau of Statistics http://www.abs.gov.au/

ACARA - Australian Curriculum Assessment and Reporting Authority My School website https://www.myschool.edu.au/home/

ACARA – Australian Curriculum Assessment and Reporting Authority Reporting page https://www.acara.edu.au/reporting

ACER – Australian Council for Education Research PISA page https://www.acer.org/ozpisa

AITSL – Australian Institute for Teaching and School Leadership Analysing data to improve student learning https://www.aitsl.edu.au/tools-resources/resource/analysing-data-to-improve-student-learning-illustration-of-practice

CESE – Centre for Educational Statistics and Evaluation http://www.cese.nsw.gov.au/

IEA – International Education TIMMS & PIRLS page https://timssandpirls.bc.edu/

Laboratory of International Assessment Studies - http://international-assessments.org/

NESA – NSW Education and Standards Authority NAPLAN page http://educationstandards.nsw.edu.au/wps/portal/nesa/k-10/understanding-the-curriculum/naplan

OECD - Organisation for Economic Co-operation and Development PISA page http://www.oecd.org/pisa/