We find ourselves in an era of increased accountability through the publication of data reporting student achievement in external testing. Schools are often judged on these data and compared to other schools on the basis of these data. There are also increased expectations from governments and the community that school performance is transparent and that school leadership teams are seen to be reactive to the perceived needs identified within these data (Pettit, 2010). The publication of such information can be confronting as this type of data can be thought of as a shallow representation of work done by teachers to get the best outcomes for their students.
Publicly available data can also overshadow other areas of achievement that are revealed in data available at the school level that are not linked to external testing. School leaders and teachers are required to be ‘data-literate’ so they can communicate this information to school stakeholders and, although externally available data can be viewed through a negative lens, there is also a positive side to the analysis of data when a multifaceted approached is used that involves consideration of a number of data sources and teacher collaboration.
The National School Improvement Tool outlines nine interrelated domains that provide evidence that schools can use to make judgments about their efforts in achieving positive outcomes for students (ACER, 2012). One of the domains listed is the analysis and discussion of data. Importantly, it is not only academic data that the NSIT lists as being indicative of school performance but data regarding information about student attendance, participation in extracurricular activities, homework, formative assessment performance, behavioural issues, student well-being and perception information gathered from surveys. Furthermore, the NSIT states that outstanding schools link data explicitly to their improvement agenda and that there is a systematic approach to the collection and analysis of a range of student data. There is also an emphasis on the monitoring of student performance data to show that identified gaps in student understanding is monitored over time. Schools which are identified as outstanding also involve staff in conversations about data and the process of analysing data. Although not all teachers are proficient in analysing data they can be involved in conversations about how the data are used and how this impacts on their teaching.
When considering student academic performance, information from external tests should not be the only indicator of how students are going or how well the school has met the needs of their students. Pettit (2010) states that the use of external tests or single assessment sources to make judgments about the impact of the teacher on student performance is problematic as it can lead to ill-informed interventions. The use of data is strengthened, however, through the adoption of evidence-based leadership that focuses on the diagnostic power of feedback provided through multiple sources of data. This approach can lead to sustainable change in teacher practice.
When leading conversations which focus on data, it is important for teachers to understand that data itself is not knowledge. Data does help teachers make sense of observations and specifically what conclusions that can be drawn from observations. Data is also not information, rather, information is what is results from the interpretation of the data (Matters, 2006). Data do reveal the impact of changes to pedagogy and teacher involvement in the analysis of data with this in mind can lead to viable and effective change. Moreover, a culture of data tracked evidence of student learning is indicative of outstanding schools as described in the NSIT (ACER, 2012).
Encouraging positive conversation about data
Data driven conversations can be confronting for teachers and often there is an element of defensiveness surrounding such conversations. Without collaboration and collegiality, however, the effective use of data for school improvement is difficult to achieve. One way to overcome this defensive barrier is to make data a regular part of meeting times, whether this be a well-being team meeting, faculty meeting or school executive meeting. In data-focused meetings, teachers analyse a wide variety of data, consider multiple interpretations, help one another grow and support each other in achieving school improvement. It is important to recognise though, that not all data focused conversations are productive and there is an essential formula for quality conversation about data:
- Students are the shared responsibility of everyone: If teachers are only concerned about the students in their class, they have little motivation to assist colleagues in examining data and developing and refining instructional practices. School leaders have a responsibility to develop a culture of collective efficacy among staff a cultivate a sense of collective responsibility for all students. Data informed leadership is a characteristic of authentic distributed leadership as teachers share a responsibility for making informed decisions for improving student achievement.
- Conversations about data include healthy disagreement: School leaders are encouraged to allow teachers to express divergent opinions around the impact of initiatives. Divergent opinions allow different ideas to develop and to critically analyse the status quo. Of course, it is important that lively discussions are conducted respectfully and that these discussions are centered around improving teaching and learning. The use of data is one way to inform discussion and, importantly, the triangulation of data reduces subjectivity that can permeate such discussions.
- Conversations about data engender trust rather than suspicion: Teachers who have high expectations of their students continually embrace opportunities for professional growth. They seek the data that informs them of their impact. Some teachers, however, fear that data will be used against them and become defensive about what these data show. School leaders are encouraged to use data to inform the plan ahead and to provide opportunities for teachers to be a part of the conversation around what these data are showing. This also allows a culture of trust to develop between teachers and school leaders and then conversations around data become a collaborative process. Conversations about data take a solution-oriented approach: As part of a continual improvement process, productive teacher teams use data discussions as a launching pad to discuss student thinking and understanding. It is imperative for teachers to engage in reflective practice and data assist teachers in this process. Data support judgments about the impact of teaching for students and assists teachers and school leaders in planning for future directions in teaching and learning. Focusing on a preferred future and being positive are crucial features of a solution-oriented culture.
Ideas for developing a data culture
The data cycle
All teachers are researchers as they gather data in the form of school-based formative and summative assessment which may also include student work samples. They use this information to make judgments on how the student is progressing and implement changes to address the needs of the student accordingly. Making this cycle a common expectation of teacher practice leads a school to develop a culture of data-led learning. The approach of targeted teaching can make great gains in student learning as the teacher becomes responsive to the needs of the learner but the data required for targeted teaching is not drawn from one source (Goss, Hunter, Romanes, 2015).
The diagram illustrates the data cycle and focuses on the process of identifying needs, making changes and then measuring the impact of the change:
Developing teacher’s understanding of data including how it is gathered, strengths and limitations of the data sets and the relationship between data sources is important for developing a culture of data driven learning in schools (Pettit, 2010). Multiple data sources are important as no single assessment will provide all the information teachers need to make instructional change. The use of formative assessment data is useful in gauging how well benchmarks are being met and this can be tracked and then triangulated with summative assessment data and external tests. Further analysis can be enhanced by the inclusion of student work samples, attendance records, behavior records and learning profiles. Using these sources together is known as triangulation.
The method of triangulation of data sources is the process of using multiple data sources to address a particular question or problem. This can confirm or challenge information drawn from other sources and allows well justified conclusions to be made about teaching practice and student learning. When data from external sources reflect findings from internal data sources teachers can be more confident in the decisions they made to changes in practice.
Culture is created when the people of the organization have common beliefs and practices. A culture of data lead learning is fostered when teachers are provided with the opportunity to collaboratively interpret data in stage, year level or faculty teams. This allows teachers to adopt common instructional and assessment practices as well as common expectations for student performance (Hamilton, et al., 2009). When collectively interpreting data the questions in Table 1 are helpful for the data teams when they are breaking down what the data are revealing.
This collaborative approach involves establishing common learning goals and shared expectations for student learning. Benchmarking is an effective way to formulate goals, for example, by the end of 2017 at least 80% of students will be achieving at or above expected levels in Writing in NAPLAN. This goal would be reflected in the school strategic plan. Working towards the achievement of these goals can be tracked through the recording of formative assessment data. Teachers can make adjustments along the way so that they are continually working towards the end goal and not waiting for some external test to show the impact of their teaching.
When working with data teams it is useful to have the school strategic plan as a reference point so that any plan for action is aligned with the school’s plan for improvement. Likewise, data teams should also involve school executive members as facilitators or quiet observers so that they are in touch with the conversations around the data and how teachers feel about their work.
When developing a data culture in schools it is useful to identify what data sources are recorded and make these available to teachers. For example, if students are being regularly assessed for reading or numeracy, track student performance over time and have this available for teachers to refer to. Schools which subscribe to the ACER Progressive Achievement Tests have a wealth of data to use and this can easily be triangulated with NAPLAN and internal assessment data in order for well informed decisions to be made on student achievement.
In our data driven profession, it is easy to become overwhelmed with the amount of data we can gather. Data teams need to identify which sources they will use, acknowledge the strengths and limitations of each data source and use these to plan for action. Teachers make the greatest difference to student achievement and the effective use of data helps teachers to identify the impact of their practice.
Goss, P., Hunter, J., Romanes, D., Parsonage, H. (2015). Targeted teaching: how better use of
data can improve student learning, Grattan Institute.
Hamilton, L., Halverson, R., Jackson, S., Mandinach, E., Supovitz, J., & Wayman, J. (2009).
Using student achievement data to support instructional decision making (NCEE 2009-4067). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education. Retrieved from http://ies.ed.gov/ncee/wwc/publications/practiceguides/.
Pettit, P. (2010). From data-informed to data led? School leadership within the context of external testing. Leading and Managing 16(2), pp. 90–107
Matters, G. (2006). Using data to support learning in schools: students, teachers, systems.
Australian Education Review, Australian Council for Educational Leadership, Camberwell Victoria.
The National School Improvement Tool (ACER, 2012). Available at: https://www.acer.edu.au/files/NSIT.pdf