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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 2020 is available in the Archives.

UTS: Education: Initial Teacher Education
Credit points: 6 cp
Result type: Grade, no marks


A large range of data on student performance is available to schools and teachers, particularly in regard to measuring literacy and numeracy progression. Schools, school systems and individual teachers are expected to critically analyse and reflect on these data to gain greater insight into the needs and achievements of their students, and to make considered use of data to inform teaching priorities and approaches to teaching in general, and teaching literacy and numeracy in particular. The range of data available to teachers include informal and formal school assessments, state and national standardised assessments (HSC, NAPLAN), and large scale international assessments (e.g. PISA, TIMSS). This subject is the final subject in the Primary English and Mathematics specialisation streams. It develops students' knowledge of key sources of assessment data that teachers need to work with. Students gain knowledge and skills to understand the purpose and key assumptions underpinning standardised assessment instruments; exercise critical literacy and numeracy to interpret standardised assessment data; and productively use these data to improve school students' learning, with an emphasis on literacy and numeracy improvement. Students also learn about the sociopolitical contexts of standardised assessments, and important ethical and equity considerations surrounding them.

Subject learning objectives (SLOs)

a. Recognise different kinds of data that teachers can use to continuously improve teaching and learning in the classroom and the school.
b. Apply statistical concepts and methods to summarise and interpret data.
c. Accurately interpret and purposefully use data from multiple sources to investigate individual student and student cohort performance.
d. Use assessment and evaluation data to inform professional inquiries and reflections.
e. Critically analyse the political and ethical dimensions of the collection and uses of a range of educational data, including ‘big data’ and large-scale assessment data. from societal, professional and personal perspectives.
f. Produce accurate and cohesive academic and professional texts.

Teaching and learning strategies

Teaching and learning will take place in weekly two hour face to face workshops, weekly online lectures and in students’ out of class environments.

Teaching strategies (both online and face to face) in this subject involve:

Short online lectures to introduce, contextualize and illustrate new theoretical concepts and information.
Scaffolding of readings, class activities and assessment tasks in workshops and through online resources.
Facilitation of student discussions and learning activities in workshops.
Formative feedback on students’ understanding of concepts and tasks in workshops.

Learning strategies in this subject involve:

Group based investigative activities in face to face workshops.
Group based discussions of readings in face to face workshops.
Independent reading of specified academic texts.
Independent research.

There is a ‘mastery’ component in the content, including terminology, concepts and basic statistical concepts and methods that students need in order to work with educational data. Students have the opportunity to practise the application of these concepts and methods in the workshops, and to test their mastery through not-for-marks online practice quizzes before taking a mastery test (Assessment task 1).

Students are expected to undertake preliminary reading of the weekly ‘target texts’ before each workshop. These readings are scaffolded by the weekly online lectures and the weekly short ‘stimulus texts’ that are written/ produced for the non-specialist audience.

The subject is practice-based and includes tasks that simulate authentic school practices. For example, students work with real data from schools, and simulate ways in which teachers work with data to investigate student performance and inform their practice and curriculum. Students engage in contemporary issues about schooling and teachers’ work by reading and critically appraising a range of current Australian and international literature on topical issues such as ‘big data,’ learning analytics, standardised tests and teachers’ work.

Content (topics)

The subject content has a strong but not exclusive focus on literacy and numeracy teaching, learning and assessment. The content consists of skills, knowledge and methods needed to develop a working knowledge around the following questions:

Why is ‘data’ in schooling so topical now?

What is meant by data-driven decision making?
What is meant by evidence-based policy making?
What kind of data and evidence ‘counts’?

What are different types of data about students’ learning and performance that teachers and schools have available?

What are: ‘big data’, big-test data, data analytics and learning analytics?
What are some ‘everyday’ classroom data that teachers have about their students?
What can/ can’t these different types of data tell us?
How are different types of data used by teachers and/ or by schools to inform pedagogy, curricula and policies?

What skills do teachers need in order to be data literate and numerate?

How do teachers identify, collect and collate the data they need to gain insight into the problems they are trying to address?
What skills are needed to interpret and draw conclusions from quantitative data?
What skills are needed to interpret and draw conclusions from qualitative data?
How are different sources of data used together to provide insights into problems and their possible solutions?
How do groups of teachers work together to analyse data to inform their practice and improve the learning experiences and outcomes of their students?

What do teachers do with data?

What are statistical reports about schools and standardized tests conveying?
How can externally produced data be related to classroom data?
How are data used to inform pedagogy and curricula?

What critical perspectives do teachers need to exercise in working with data in their work?

What ethical guidelines and legal requirements are there in the collection, use and reporting of student and school data?
What critical literacy and numeracy skills do teachers need to make informed responses to the public discussions about school and student performance?
How do expectations of teachers to work with new forms of student and school data impact on teachers’ work?

Minimum requirements

Attendance at workshops is critical because they provide students opportunities to ‘practise’ the skills and knowledge that they are learning through applications in realistic problems. A roll will be taken at each workshop. Students who are absent in more than one workshop out of the nine workshops may not have their final assessment task assessed.

Required texts

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


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:

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

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.


ABS – Australian Bureau of Statistics

ACARA - Australian Curriculum Assessment and Reporting Authority My School website

ACARA – Australian Curriculum Assessment and Reporting Authority Reporting page

ACER – Australian Council for Education Research PISA page

AITSL – Australian Institute for Teaching and School Leadership Analysing data to improve student learning

CESE – Centre for Educational Statistics and Evaluation

IEA – International Education TIMMS & PIRLS page

Laboratory of International Assessment Studies -

NESA – NSW Education and Standards Authority NAPLAN page

OECD - Organisation for Economic Co-operation and Development PISA page