by Victoria L. Bernhardt, Ph.D., Executive Director of the Education for the Future Initiative
Victoria L. Bernhardt is Executive Director of the Education for the Future Initiative, a not-for-profit organization whose mission is to build the capacity of learning organizations at all levels to gather, analyze and use data to continuously improve learning for all students. She is also a professor in the Department of Professional Studies in Education at California State University.
Her presentation at EQAO’s November learning symposium entitled “Using Data to Improve Student Learning” provided insight into the importance of collecting data and using it effectively.
Dr. Bernhardt’s presentation allowed for discussion and deliberation among school teams, and we invite you to review this article with your own school team to find out how you can use data to improve student learning at your school.
Before you examine your own school community’s data, Dr. Bernhardt suggests that you consider a general question to begin the thinking process:
What would it take to achieve student-learning increases in every grade level, subject area and with every student group?
The data show us where we are currently and how we got there. It is vital to know where we are, as opposed to where we think we are. A school requires data in order to evaluate what is currently working and what areas require improvement, and uses this information to plan for the future. In this way, data predict and prevent failure, ensuring success. This article will show you why having access to reliable sources of data is important and how a systematic approach to using this information is valuable.
Dr. Bernhardt says that educators should use data, not hunches, to identify areas of challenge, improve instructional practices and improve student learning. She points to EQAO assessment results as one piece of the puzzle and stresses that schools need to collect additional demographic, perceptual, student-learning and school-process data, as outlined in the “Multiple Measures of Data” chart below. Examining each of these sources of information in isolation and then in combination allows for a rich understanding of your school community. This allows you to predict and plan the actions, processes, and programs that best meet the learning needs of all students.
According to Dr. Bernhardt, it has been proven that achieving student-learning increases in every grade level, subject area and student group in as little as one year is possible if we collect and use the information outlined above effectively. Throughout the process, it is critical to measure progress along the way, examine all of the various types of data and continuously monitor what your students need.
In order to use the Multiple Measures of Data, a school team can begin its data analysis with the top circle: examining demographics.
Demographic data are important because they allow you to define the context of your school and help in understanding other data such as achievement results.
Some examples of demographic data include
When examining any demographic data, as Dr. Bernhardt reminds us, it is best to look longitudinally, over at least three to five years, in order to recognize trends. Now that you are familiar with what types of information is classified as demographic data, as a school team, consider the following:
What demographic data do you have available or need to collect?
The next type of data to consider involve perception. According to Dr. Bernhardt, perceptions need to be measured to understand how students, teachers and parents perceive their learning environment. For example, based on an extensive student-perception survey, administered to 10 000 students from kindergarten to Grade 12, the number one answer was a caring teacher. Then, “a teacher who helps me learn what I didn’t think I could learn” and “a teacher who likes to have fun in helping me learn.”
Dr. Bernhardt suggests that a school team consider
What perception data do you have available or need to collect?
Sources of perception data include
Examining a combination of demographics and perception data can show you how different groups of students experience school differently.
Over time, student-learning data provide an understanding of student achievement through different measures. Some of these measures may include
These data are important because they show us what students are learning and help us understand what is being taught. Also, this information helps educators determine which students may need extra help and attention.
By considering a combination of student-learning data and perception data, we can observe the impact of student perceptions of the learning environment on student learning. If we factor in demographic data, we will learn the impact of demographic factors and attitudes on learning.
The last measure is school-process data. School processes provide important data that tell us how a school community functions in terms of its programs and processes and, therefore, how it obtains its results.
Some examples of school processes include
As a school team, take a few minutes to consider what student learning and school-process data you have available or need to collect.
Reviewing a combination of school-process and demographic data will inform you of student participation in different programs and processes. If you include perception data, it will show you the perceptions of various sub-groups of students regarding the processes and programs in your school community.
It is crucial to look at school-process data combined with student-learning data, as this will show you if school programs are making a difference in student-learning results. When it is combined with demographic data, you can determine which programs and processes work best for various groups of students. When it is combined with perception data, you will gain insight into the impact of programs on learning based on student perceptions of programs and processes.
A combination of the four categories of data above will allow you to predict and plan the actions, programs and processes that best meet the learning needs of various groups of students based on demographics and perceptions.
Looking at the results of the data described here empowers educators to adapt instructional methods in order to reach every student. The aim should be continuous improvement in any or all of the following categories:
As demonstrated in this article, a systematic approach to collecting and analyzing data is necessary in order to achieve school improvement. Dr. Bernhardt leaves no doubt in her belief that data-driven decision-making, instructional coherence and a shared vision for school improvement are preconditions for purposeful school improvement.