Indira Subramanian
A teacher makes many critical instructional decisions in planning her day-to-day lessons that makes her a pedagogical decision-maker. These choices play a crucial role in not just raising the quality of learning outcomes, but can also “close the achievement gap” between students as Wiliam and Black (2010) point out in their path-breaking research. Hence, using information from a variety of sources and deploying them carefully in the classroom is now an essential part of the teacher toolkit.
In this article, I provide an overview of what is data-driven decision-making; how it can be used for analysis, evaluation and goal setting; and provide recommendations for simple use of data sets in the daily classroom.
What is data-driven decision-making?
Data-driven decision-making refers to the systematic collection and analysis of various data points in the classroom to inform classroom teaching and learning. This data could include: assessment scores and grades, student skills, rubrics, and checklists to measure learning outcomes, and review of previous attainment to name a few. This could be qualitative data or quantitative data or a combination of both.
By using such information, the teacher is able to respond to her learners’ needs using evidence based reasoning, and is able to justify her instructional choices. She is also able to cater to diverse learners by differentiating instruction appropriately. Together, data driven decision-making helps to bring in greater impact in the classroom by ensuring a better congruence between planning and actual classroom implementation of lessons.
How to use data to drive decision-making
Teachers may be unaware but they have a treasure trove of data which is quite easily accessible to them. Student assessment scores, classroom observations, rubrics, and checklists used to design and administer classroom activities, and previous years’ performance records of students are all a fund of information. The key is to convert all this “information” in the form of isolated and unorganized numbers or text into useful data, from which significant patterns can be gleaned and inferences about the quality of learning can be made.
The first step is organize data using a spreadsheet by sorting, classifying, and ordering it. Once this is done, data analysis is a fairly simple task given the availability of user friendly software applications.
Let me illustrate this with an example using a Guttman chart analysis, a powerful technique which helps teachers visualize the performance of their students. In this analysis technique, 0 and 1 are assigned against incorrect and correct answers obtained in an assessment. If an answer is partially correct, it is marked as 0 because it indicates a gap in knowledge.
An example of a Guttman chart analysis
Such an analysis helps the teacher to identify the Zone of Proximal Development of her class and establish the existing learning levels. It will also assist in goal setting for individual and groups of learners, and in differentiating instruction.
The above example is just one of many different ways that teachers can use data to make decisions in the classroom. Other examples include using standard deviation, mean scores, grouping and sorting scores according to ranges/bands. Qualitative data can be coded for patterns which can enable the teacher to find out her learners’ interests and readiness.
The way forward
Over the last decade or so, it has been increasingly recognized that data-driven decision-making can make a big difference in transforming classroom learning. Towards this end, there is a greater impetus on teachers to upgrade themselves to learn how to transition to an information rich classroom and use data in meaningful ways.
The key is to first determine the objectives of what and how teachers want to use this information, and to collaborate with colleagues and co-teachers for a more concerted and school wide approach to the process. This will help teachers become action researchers in a sense and undertake a more systematic inquiry in the classroom. Such pursuits hold great potential and promise to manage the teaching-learning environment and reduce the gap in learning levels.
Reference
Black, Paul & Wiliam, Dylan. (2010). Inside the Black Box Raising Standards Through Classroom Assessment.
The author is an educational researcher and works closely with schools in India and abroad for whole school improvement solutions. She can be reached at indira.ttf@gmail.com.