Teachers can analyse data in order to improve their performance.
Data has become a critical driver of decision-making.
"Without data, you're just another person with an opinion"
W. Edwards Deming
Collecting and analysing data supports teacher inquiry. You can gather and analyse data to identify at-risk students, inform your inquiry, and quantify the impact your interventions are having on student learning.
Data provides you with:
Student data is more than just test scores. It comes from a variety of sources to give a fuller picture of student learning. Being able to access shared data via a student management system (SMS) enables teachers to identify areas of need, organise student groupings, and work collaboratively with students and whānau to set learning goals.
Schools gather a range of student data, including aspects of a student's identity such as:
Although this data may be useful to support a teacher inquiry, it is usually the student data that can change that will be most relevant to teacher inquiry. This includes:
The right data in the right format can inform teacher practice and student learning goals. Privacy and data security must be considered when sharing data with whānau and other schools.
Source: Data Quality Campaign
A visual overview of different types of student data presented as in infographic by Data Quality Campaign.
Quantitative data is numerical information, such as:
Quantitative data can be easily entered into a spreadsheet and visualised in tables and graphs.
Qualitative data is descriptive, rather than numerical. It can provide insights into what your students are thinking and feeling about their learning.
Methods for gathering qualitative data include:
"Qualitative data can put flesh on the bones of quantitative data" - Anthony Shaddock
Qualitative data should be used in conjunction with quantitative data in order to triangulate (validate) your results.
Coding and categorising qualitative data into numerical data sets makes it easier to visualise and analyse.
Use the insights, revealed by collecting and analysing student feedback data to inform your actions.
There are several tools available for helping you collect, analyse, and visualise data, ranging from professional software to tools designed for casual users.
The technology-rich environment of schools provides easy access to student data. Collecting data to inform teacher inquiry, and classroom teaching and learning is common practice in all schools.
Collecting data can be construed as an invasion of privacy. When collecting, sharing, and reporting on data, ensure you:
In New Zealand schools, it is important for leaders and teachers to analyse assessment and attendance data in order to gauge student progress, as well as provide accountability to Board of Trustees, and Ministry of Education. While you may use this data to inform an area for inquiry, this is a different purpose for data gathering and analysis. Assessment Online provides information about gathering, analysing, interpreting, and using information about students' progress and achievement in relation to The New Zealand Curriculum.
An explanation of why using data is an important focus for education going into the future from CORE Education.
Technology has expanded our horizons and there is an obvious role for teachers to engage with data to assess what works for them, in their school, with their students.
Using data to improve learning: A practical guide for busy teachers (Shaddock, 2014).
As teachers, we all have hunches about what isn't working and what could work better for our students. Timperley, Kaser, and Halbert (2014), define developing a hunch as a vital phase in their Spiral of Inquiry framework
Without evidence to back them up, hunches remain subjective. The well-planned use of data in an inquiry can turn a hunch into a credible, evidence-based hypothesis and call-to-action.
Use data to:
Helen Timperley, Linda Kaser, and Judy Halbert outline their model for teacher inquiry.
High School science teachers inquire into improving outcomes for at-risk students by introducing flipped learning.
|Teacher inquiry cycle steps||Actions taken|
|1. Scanning – What's going on for learners?|| |
Achievement data reveals that at-risk students are unable to demonstrate progress in understanding of key indicators.
Submission rates of assignments and homework tasks are low.
Teacher observations describe some students as presenting signs of disengagement from classroom learning.
|2. Focusing – Where will concentrating our energies make the most difference?|| |
Teachers collect student feedback through a questionnaire. They gather qualitative feedback from students regarding likes and dislikes of classroom and assignment/homework tasks.
Teachers analyse the data. Qualitative feedback shows that students are:
3. Developing a hunch – How are we contributing|
to the situation?
Teachers reflect on how they might be contributing to the situation.
They wonder whether there might be too much teacher-talk or lecture-style presentation of key concepts in the classroom.
|4. New learning – How and where will we learn more about what we do?|| |
Teachers collaborate and consult experts within the school or Community of Learning | Kāhui Ako.
They consider best-practice pedagogy and research on student engagement and motivation. They find flipped learning:
|5. Taking action – What can we do differently to make enough of a difference?|| |
Teachers introduce a flipped learning component to the next assignment.
The component contains:
Teachers use analytics in Moodle to monitor how many times students have accessed the flipped learning material.
Teachers use the analytics embedded in the forum tool to monitor how many times a student has posted or replied to a classmate's post.
|6. Checking – Have we made enough of a difference?|| |
Teachers collect and represent all data using appropriate visualisation tools. They consult data to analyse whether their flipped learning intervention has improved outcomes.
Teachers then share and report on data with colleagues, and students where appropriate.
Teachers use data to justify changes going forward.
Learning analytics are deﬁned as “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.”
Learning analytics: drivers, developments, and challenges (Ferguson, 2012).
Many virtual platforms such as Moodle and Google classroom have built-in analytics which provide teachers with information about the digital learning activities of their students. By following students' digital actions in online learning spaces, teachers can access data to inform next steps.
Learning analytics harnesses the potential of digital learning, enabling teachers to:
Teacher inquiry is an effective method to help teachers gain a better understanding of their classroom practice. By developing reflective practitioner competencies, it contributes to teachers' self-evaluation and improvement. Emerging teaching and learning analytics technologies are at the spotlight of the research and practice communities, globally to facilitate this process.
Learning analytics and the collection of student data can play a critical role in supporting the various steps of the teacher inquiry cycle
Analytics help parents and teachers monitor student progress at a glance. It also provides recommendations for future actions.
A chat forum analytics tool for Sakai. Provides heat maps describing the interactivity of students on chat forums and social networks.
This plugin for Moodle measures student engagement and identifies at–risk students.
An adaptive learning platform that gauges what students already know and recommends pathways for learning. Teachers can draw on Knewton's open-source course content to set assignments and track student progress. Use inbuilt analytics to get a fuller picture of students' learning contexts.
|Learning analytics outcome||Description|
|Discover patterns within student data||Helps teachers provide more informed support and scaffolding to individual students and conduct more holistic assessments.|
|Predict future trends in students’ progress||Elicits how the students might perform in the future, for example in terms of performance or engagement, and plan appropriate support.|
|Recommend teaching and learning actions||Recommendations may refer to educational resources/tools or learning/assessment activities that are appropriate to meet the individual needs of students. The recommendations may be addressed to either teachers or students.|
A clear, step-by-step approach to using data for improving learning by Anthony Shaddock.
Helen Timperley, Linda Kaser, and Judy Halbert outline their model for teacher inquiry.
A US resource on data policy and use in education.
Information for NZ school leaders and teachers about gathering, analysing, interpreting, and using information about students' progress and achievement.
Learning analytics: drivers, developments and challenges (Ferguson, 2012).
A review of learning analytics, beginning with an examination of the technological, educational, and political factors that have driven the development of analytics in educational settings.
Informing pedagogical action: Aligning learning analytics with learning design (PDF) (Lockyer, Heathcote & Dawson, 2013).
How learning analytics can inform pedagogical action.
Informing learning design to improve teacher inquiry (Pozzi, 2014).
An overview of current research into the connections between learning design and learning analytics.
An enriched rubric containing some criteria and related assessment levels that are associated with data from the analysis of learners’ interaction and learning behaviour in a Moodle course, such as number of post messages, times of accessing learning material, and assignments.
A plugin that gamifies learning by converting student progress data into experience points.
A plugin that visualises interactions between students on chat forums. It reveals information such as which students are leading discussions and which students are in dialogue with each other.
A chat forum analytics tool. Provides heat maps describing the interactivity of students on chat forums and social networks.
This plugin measures student engagement and identifies at-risk students.
An adaptive learning platform that gauges what students already know and recommends pathways for learning. Teachers can draw on the open-source course content to set assignments and track student progress. The in-built analytics give a fuller picture of students' learning contexts.
Helps parents and teachers monitor student progress. It also provides recommendations for future actions.
A design app for making infographics. It has tools for visualising data in stylish charts and graphs. It has both free and premium accounts.
A graphic design app with an infographic maker.
Software for analysing and visualising data. Free to download and use, with a premium account for added features.
Software for analysing qualitative data.
This section on Assessment Online explains different types of graphs and their uses.
Explanations of and, links to, data visualisation tools on Creative Bloq's blog.