In contemporary education, data collection and presentation are pivotal as instruments for measuring both teacher and student performance, writes Dr Hugh Gundlach, from the Faculty of Education at The University of Melbourne.
Data insights serve as a basis for discussions among students, teachers, parents, leaders, and policymakers. While numbers and statistics can sometimes take precedence over other important issues in a rounded education, ideally, data can be used to improve student learning outcomes through superior feedback, relevant differentiation, and improved teaching practice.
Understanding data
Data, in its essence, serves as information that aids in assessing past or ongoing situations and informs future decisions. The reliability, relevance, and validity of data are critical considerations. While numbers are a prevalent form of data, it’s worth noting that numbers alone can sometimes create an illusion of accuracy that may not align with the quality of the source data.
Ensuring data documentation is comprehensible, verifiable, and reusable is essential, especially when data is intended for use by others. Recording the ‘When, why, and by whom?’, as well as the methods or instruments used, is important when reporting results.
Textual and visual representations, such as charts, graphs, plots, and dashboards, offer invaluable insights into achievements, progress, benchmarks, and comparative analyses, but can also be easily misrepresented.
Utilising data for feedback
Feedback on students’ performance allows them to identify where they may individually or as a collective need development. Assessments, be they informal or formal, formative or summative, immediate or delayed, often serve as sources of data.
Quizzes, tests, polls, assignments, and projects tend to provide such data directly, but with the prevalence of online learning platforms, metadata (data about data) can also be useful. Metrics like student visits to subject pages, draft submissions, submission punctuality, engagement with materials (eg, file downloads), and forum interactions all contribute to understanding of students’ performance and progress.
Supporting differentiation
Data enables teachers to gain insights into the readiness levels of their students. Armed with this knowledge, teachers can tailor lessons to suit individual learning profiles.
Ultimately, data provides an informed basis from which to discern specific needs, provide additional support, pinpoint those in need of extra support or enrichment, facilitates strategic grouping for personalised instruction, such as tutoring, mentoring, or individualised learning plans, and offer enrichment opportunities ensures that teaching is student-centric rather than content-centric.
It’s not just about student data
Data is not solely for the benefit of students and parents; it holds tremendous potential for educators too, of course. By collecting and analysing a range of quantitative and qualitative data beyond students’ results, teachers can evaluate the effectiveness of their teaching methods, the quality of materials, and the overall learning experience.
Such data may encompass whether sufficient time was allocated to each topic, the completion status of instructional units, the quality and robustness of materials, student engagement levels, teacher confidence, the effectiveness of questions posed, participation in class discussions. This aids teachers in setting professional goals and continuously developing.
Teacher-led research and data
In the ‘Capstone’ subject in the Master of Teaching Student Internship program in the Faculty of Education, The University of Melbourne, teacher interns embark on a year-long ‘self-study’ project. This entails the collection and analysis of data with the primary aim of enhancing teaching performance and improving student learning outcomes. These interns work in diverse school environments across Victoria, each conducting a personalised research project tailored to their unique context, situation, and research interest.
After setting a research question and conducting a literature review, interns design a method of data collection and analyse their data to produce insights that can be generalised to a wider audience for a publication and presentation at the end of the year within the subject cohort.
Restrictions are placed on the nature of the data gathered and method used; nothing that requires Human Research Ethics approval may be performed. This ensures that the experiences, privacy, and rights of all school stakeholders are safeguarded, and the interns’ regular teaching responsibilities remain unaffected.
As a supervisor of many of these research projects, it is stimulating to help interns brainstorm sources of data that can help them reflect on their own practice.
Sources of data in schools
A wide array of data sources is available, extending beyond conventional assessments and standardised tests. These sources include ABCD cards, entry and exit slips, learning logs, low-stakes writing, mini whiteboards, portfolios, surveys, polls, short-answer questions, and calculations.
Teachers can also generate data directly through sources such as portfolio materials, field notes, critical friend feedback, observation records, notes on student-produced documents and artifacts, diaries, reflective journals, and photos and videos of non-sensitive content (eg, classroom layouts, student work).
Sometimes the interns find that there is not enough data from the student work, so we supplement with other contextual data and reflection. Similarly, individual data points may have limited insights, but their true potential emerges when collected over time, across diverse students, and complemented by relevant metadata.
For interns (and audiences) who might not see patterns in numbers as well as others, the visualisation of data through various chart types or even illustrative text, quotes, and samples, can effectively convey nuanced narratives.
Improved teaching practice
In the Capstone program, the interns are challenged to consider what knowledge and skills are measured by the assessments schools use, whether relationships between concepts are correlational or causational, and whether certain concepts may be ‘leading’ or ‘lagging’.
As an example, the topic of student engagement is always popular to study, and it often leads to deep thinking about whether it can be validly and reliably measured; whether it is a cause, product or by-product of great learning, and even whether it is necessary for learning. In this way, engaging in thinking and discussions about the data we generate, gather, analyse and use in our daily roles can lead to questioning assumptions and professional learning.
When used effectively, data empowers educators to make informed decisions. It bridges the gap between theoretical insights and practical classroom application, ultimately benefiting both educators and students. Consider running a workshop, panel, discussion or professional learning activity with your team to explore how rethinking data and data sources could benefit your learning context.
About the author
Dr Hugh Gundlach is a lecturer in Business Studies and Commerce Coordinator in the Faculty of Education at The University of Melbourne. He completed a PhD in Education under the Research Training Program Scholarship and the Department of Education’s ‘Strengthening Teachers’ Grant, investigating teacher wellbeing and retention. He is one of the Australian Council for Educational Leaders’ New Voices in Educational Leadership Research.