Collecting and analysing data is an essential part of programme evaluation and improvement. By collecting and analysing data on student performance, attendance, and engagement, for example, teachers can improve their classroom practices. Administrators can use consolidated data to gain insights on how well a programme is functioning, understand which goals are being met, and identify areas that need improvement. The same data can also help policymakers decide where to allocate resources and which interventions to implement.
At Gyan Prakash Foundation (GPF), we are working to bring about a fundamental change in learning through competency-based education in rural government schools in four districts of Maharashtra (Parbhani, Nandurbar, Satara, and Solapur). We have adopted a collaborative approach since our inception in 2011, working with teachers, school leaders, cluster officers, block- and district-level officials, and parents and community representatives—all of whom play a significant role in improving learning outcomes for children.
This article is based on our learnings from adopting a decentralised approach to data, which we believe can be used by all the stakeholders involved—policymakers and teachers alike—for effective decision-making.
How do different stakeholders use data?
In the education sector, if a programme involves children, the most common data point is child learning data. This data is typically for two sets of stakeholders: decision-makers (such as cluster heads and block and district education officers) and teachers in the classroom. The data intended for decision-makers is usually consolidated child assessment data, details pertaining to school infrastructure, plans for the following academic year, etc. This data is crucial to understanding the status of education in the cluster, block, and district, and is used to inform strategies, make programmatic changes, and write publicly accessible reports. The data meant for teachers is mostly individual child assessment data that helps inform their own teaching practices.
The direction of the data is almost always fixed—it flows from the teachers to the decision-makers.
Data is mostly demanded by those at higher levels in the hierarchy from those at lower levels and is often associated with performance, be it of a child, a teacher, or an official in the system. There is a tendency to evaluate a child based on their scores on a test, and a teacher based on the number of students in their classroom who are performing ‘well’. This association, however inaccurate it may be, has led to a general fear of data among teachers. As a result, teachers either disengage from the process of collecting data or tend to report to higher authorities what may not be a completely accurate representation of their students’ performance in the classroom.
The direction of the data is almost always fixed—it flows from the teachers to the decision-makers. For example, a teacher consolidates the data for their class and submits it to the cluster head, who takes the data sets of all the schools in the cluster and creates a cluster-level report. The cluster report will be submitted to the block head, who will consolidate the data of all the clusters to create a block report. This unidirectional flow of data shifts the ownership from one entity to another, ultimately rendering the information non-actionable at the source, which is the teacher. The teacher maintains a data set of each student’s performance that can be used to bring about a change, but in reality, it does not directly inform their teaching practices to improve children’s learning.
How can data be made more actionable?
Data is actionable when the user is empowered to make certain decisions based on it. Data should be easy to collect and organise and should be actionable to users at every level. In education, however, the data is only actionable at the policy level. The teachers’ lens is missing—in the context of a classroom, data that is collected should reveal the actual learning level of each child. Teachers should then be able to identify their students’ needs and adapt their approach based on the learning data of each child.
In our programme, we came up with three core strategies to make data actionable: make data actionable for teachers, change higher authorities’ perspective on data, and use tech to consolidate data.
1. Make data actionable for teachers
Data is most useful to teachers when they can interpret it, that is, use it to assess children’s learning status and identify key actions to improve it.
To make this happen, in 2016, we created a simple offline spreadsheet with the teachers that helped them interpret data from their classrooms. Each row listed the name of a student and each column the skills or competencies they were expected to master (for example, recognising numbers up to 10, or understanding concepts of ‘more’ and ‘less’) within a certain period. Teachers were given green pencils to mark the competencies that students had mastered and red pencils to mark the ones that students had yet to master.
By simply glancing at a page, teachers could now deduce whether or not a child had mastered a certain skill or competency. It also became easy to see whether the class, as a whole, was doing well or not. Using this sheet, teachers could identify two major things: the specific support that individual students required, and the competencies that they needed to work on with the entire class. Combining these two, teachers were able to plan better for individual students and for the group as a whole, as well as for how to utilise time in the classroom. When teachers saw that this data was helping them work better with the students, it took out their fear of data. Once the ownership of data stayed with the source and the direction of the information was reversed, it had meaning. The same sheet could also be used to create data sets such as class averages that had to be submitted to higher authorities.
For two years, GPF used the ‘red–green sheet’ to make student learning data actionable. The process was manual, which made it prone to errors and difficult to manage and scale. In 2018, GPF transitioned to a digital platform—Learning Navigator—developed by the nonprofit Gooru. This platform catered to the exact same need, but made the management and presentation of data more efficient. It enables the teachers to manage childwise data of assessments; get individual, group, and consolidated performance reports; and identify competencies that need further attention.
2. Change higher authorities’ perspective on data
We wanted to make the data from the red and green sheet actionable to not just the teachers, but also to higher authorities who could make informed decisions using the same data. At the monthly shikshan parishad (a meeting of all teachers in a cluster), teachers were requested to bring their red–green sheets for a group discussion. This gave cluster officials an opportunity to look at the data from a new perspective. Rather than viewing data solely as a reflection of individual teacher or school performance, the collective data from all classrooms and schools helped the cluster head understand the challenges faced by students in their learning journey and identify teachers’ pain points. Which competencies were students struggling with? What challenges were teachers facing in teaching those concepts?
Teachers observed that the data collected from their classrooms was being utilised in enhancing their ability to work effectively with their students. As a result, they became less apprehensive about reporting accurate data. Consequently, cluster resource groups consisting of six to seven experienced teachers from each subject were convened. These groups played an important role in building the capabilities of other teachers in the cluster. The use of data from the red–green sheet during shikshan parishads helped the cluster head identify specific learning outcomes to focus on in a particular month and ensure that all teachers were equipped with skills to teach those competencies in their classrooms.
3. Use tech to consolidate data
Since GPF is a large-scale programme, our core interest was in consolidated data. In October 2021, consolidated data was made available to authorities that support teachers in four districts in Maharashtra. With this update to the ‘mission control’ feature on Learning Navigator, data from all schools in a district were made available in real time not only to the teacher, but to school management committees, cluster heads, block education officers and district officials across the system.
One cluster head said that he finds it easy to monitor the work of all the teachers that fall within the area for which he is responsible. “The total number of teachers from the two clusters [I oversee] is more than 182. But today, wherever I am, it is possible for me to see how many teachers have worked on which specific learning outcomes.”
Data can be useful to stakeholders at all levels of a programme.
A block education officer described how the mission control feature would be beneficial to him. “We will use mission control to track students from nine blocks of Parbhani district. This will help us in working towards the goal of enabling every student to achieve all the learning outcomes as expected of their grade.”
The strategies we employed helped ensure that users at every level were empowered with data in their hands and could make decisions to improve learning for every child in every classroom. We often mistake that the real and only consumers of data are the entities that fund the activities. This is almost always a myth. Data can be useful to stakeholders at all levels of a programme. Whether or not data is actionable can be a self-check for how authentic it is, which is something that many programmes struggle with.
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Know more
- Read this article to learn about whether nonprofits should buy tech applications or build them from scratch.
- Watch this video to learn more about how Gyan Prakash Foundation used technology to enable competency-based teaching and learning.
