From Traditional Teaching to Continuous Learning: The Role of Data-driven Transformation in Education
Adaptation is what has enabled us to thrive. We have learned about natural selection and ‘survival of the fittest’, nature's way of continuous improvement. This adaptation however was random i.e., left to chance, slow-paced and had significant inefficiency. We have realised, nonetheless, that learning, and adaptation is central to innovation in the 21st Century. Modern companies use approaches like six-sigma and lean-processes with ‘build-measure-learn’ philosophy. These are widely used to enable learning and adaptation that is intentional, quick and efficient. They put feedback loops in place to help us get to our desired results, quicker.
Why we must systematically learn and adapt in 21st Century Schools
Education is a complex challenge: Education is one of the most complex challenges that we face today. In fact, complex social challenges like education have been given the term ‘wicked problems’ by theorists because of their complex and dynamic nature. ‘Wicked challenges’ are difficult or impossible to solve due to incomplete or contradictory knowledge, the involvement of multiple stakeholders with different values and interests, and the interconnectivity of the problem with other issues. Education is a social or cultural problem that is often systemic, persistent, and resists traditional problem-solving methods.
Today’s world is changing fast: Further, as the world continues to evolve at an unprecedented pace, it is essential to ensure that our education system keeps up with these changes. Traditional ways that are slow to adapt to change will not suffice anymore.
In this context, our school systems must have the ability to continuously learn and evolve.
To enable this, schools must adopt a data-driven approach to continuous learning and improvement. Our National Education Policy (NEP) 2020 also emphasises the importance of continuous assessment and review in education.
What is Data Driven Learning and Adaptation in Education?
Data-driven improvement is when we use information and analysis to figure out what we need to do better, set goals to improve, and make changes to reach those goals.
What does this look like in a school setting?
In Schools, data-driven improvement is an approach to improving education that uses data and analysis to inform decision-making and continuous improvement. It involves the collection and analysis of various types of data, including student achievement data, teacher performance data and school climate data, among others. This approach enables schools to make informed decisions, monitor progress, and adjust strategies as needed to achieve their goals and ensure that students receive a high-quality education.
However, collecting data in schools can be challenging. In schools, our primary goal is to develop people - students. Students are complex and their performance or learning cannot be reduced simply to numbers. Moreover, school systems typically are slow changing, making it difficult to adopt new technologies and digitise data collection.
Despite these challenges, if we want Schools to thrive in the 21st Century it is essential to start collecting data in schools to drive continuous improvement.
3 tips for implementing Data-Driven Approaches at your School.
Here are three tips for Educators or Schools that are looking to get started:
Why collect data: Focus on learning, not compliance.
Focus on using data for learning and improving rather than just control and compliance.
A strong focus on learning creates a culture in which Students and Teachers view data as a means of tracking progress and improving their performance. They feel a sense of ownership. They feel secure enough to take risks and reflect on mistakes honestly. They trust each other enough to engage in collaborative dialogue, with a focus on solution-finding and without fear of personal judgement. They value this process and understand that this is an essential part of learning.
Further, once you begin using data to measure progress, compliance and accountability fall into place naturally. But they cannot be the primary motivation for using data because they do not create the conditions for learning and improvement. When teachers feel that the data is going to be used to judge them, in the best case they will view this as a banal process that they must complete. In the worst case, they are at risk of feeling pressured enough to comply at all costs and compromise the fidelity of their data.
What data should be collected: Start small and intentionally, don’t just collect everything you can.
To quote Charlie Munger, “People calculate too much and think too little.” Start slowly and thoughtfully. Don’t fall into the trap of ‘collecting everything’. Far too many schools enthusiastically collect everything they can think of, but they don’t have the time or capacity to process the data in a useful way. This can lead to disillusionment with data-driven processes because teachers can burn out from all the mindless data collection and even worse, they view it as a useless process when they see that the data is not used meaningfully.
"Students are complex and their performance or learning cannot be reduced simply to numbers. Moreover, school systems typically are slow changing, making it difficult to adopt new technologies and digitise data collection."
Instead, start small by collecting a few meaningful pieces of data that you can use purposefully to improve. As the team understands more, expand the data metrics and sources that you include in your process.
How you collect data: The reliability of data and sustainability of the process matter
It is important to collect and use data that can be trusted. Inaccurate data will lead to ineffective or even incorrect solutions that take you off course. Often, consumers of the data i.e. educators are too eager to draw conclusions from the data, without evaluating how reliable the data is. Is it a good measure to answer your questions? Are there limitations? Was the data collected with fidelity? Was there room for error?
Hand in hand with this is the task of supporting the team in building their tech and data literacy skills. Thinking about the quality of the data being used is an essential step before we use it to guide our decisions.
As we move further into the 21st century, the world continues to change rapidly, and our education systems must keep up. The key to this lies in adopting data-driven approaches to continuous learning and improvement in our schools. By collecting and using data purposefully, we can ensure that our students receive a high-quality education and that our schools remain relevant and effective. So, let's embrace this mindset of learning and adaptation, and start implementing data-driven approaches in our schools today!
Why we must systematically learn and adapt in 21st Century Schools
Education is a complex challenge: Education is one of the most complex challenges that we face today. In fact, complex social challenges like education have been given the term ‘wicked problems’ by theorists because of their complex and dynamic nature. ‘Wicked challenges’ are difficult or impossible to solve due to incomplete or contradictory knowledge, the involvement of multiple stakeholders with different values and interests, and the interconnectivity of the problem with other issues. Education is a social or cultural problem that is often systemic, persistent, and resists traditional problem-solving methods.
Today’s world is changing fast: Further, as the world continues to evolve at an unprecedented pace, it is essential to ensure that our education system keeps up with these changes. Traditional ways that are slow to adapt to change will not suffice anymore.
In this context, our school systems must have the ability to continuously learn and evolve.
To enable this, schools must adopt a data-driven approach to continuous learning and improvement. Our National Education Policy (NEP) 2020 also emphasises the importance of continuous assessment and review in education.
What is Data Driven Learning and Adaptation in Education?
Data-driven improvement is when we use information and analysis to figure out what we need to do better, set goals to improve, and make changes to reach those goals.
What does this look like in a school setting?
In Schools, data-driven improvement is an approach to improving education that uses data and analysis to inform decision-making and continuous improvement. It involves the collection and analysis of various types of data, including student achievement data, teacher performance data and school climate data, among others. This approach enables schools to make informed decisions, monitor progress, and adjust strategies as needed to achieve their goals and ensure that students receive a high-quality education.
Complex social challenges like education have been given the term ‘wicked problems’ by theorists because of their complex and dynamic nature.
However, collecting data in schools can be challenging. In schools, our primary goal is to develop people - students. Students are complex and their performance or learning cannot be reduced simply to numbers. Moreover, school systems typically are slow changing, making it difficult to adopt new technologies and digitise data collection.
Despite these challenges, if we want Schools to thrive in the 21st Century it is essential to start collecting data in schools to drive continuous improvement.
3 tips for implementing Data-Driven Approaches at your School.
Here are three tips for Educators or Schools that are looking to get started:
Why collect data: Focus on learning, not compliance.
Focus on using data for learning and improving rather than just control and compliance.
A strong focus on learning creates a culture in which Students and Teachers view data as a means of tracking progress and improving their performance. They feel a sense of ownership. They feel secure enough to take risks and reflect on mistakes honestly. They trust each other enough to engage in collaborative dialogue, with a focus on solution-finding and without fear of personal judgement. They value this process and understand that this is an essential part of learning.
Further, once you begin using data to measure progress, compliance and accountability fall into place naturally. But they cannot be the primary motivation for using data because they do not create the conditions for learning and improvement. When teachers feel that the data is going to be used to judge them, in the best case they will view this as a banal process that they must complete. In the worst case, they are at risk of feeling pressured enough to comply at all costs and compromise the fidelity of their data.
What data should be collected: Start small and intentionally, don’t just collect everything you can.
To quote Charlie Munger, “People calculate too much and think too little.” Start slowly and thoughtfully. Don’t fall into the trap of ‘collecting everything’. Far too many schools enthusiastically collect everything they can think of, but they don’t have the time or capacity to process the data in a useful way. This can lead to disillusionment with data-driven processes because teachers can burn out from all the mindless data collection and even worse, they view it as a useless process when they see that the data is not used meaningfully.
"Students are complex and their performance or learning cannot be reduced simply to numbers. Moreover, school systems typically are slow changing, making it difficult to adopt new technologies and digitise data collection."
Instead, start small by collecting a few meaningful pieces of data that you can use purposefully to improve. As the team understands more, expand the data metrics and sources that you include in your process.
How you collect data: The reliability of data and sustainability of the process matter
It is important to collect and use data that can be trusted. Inaccurate data will lead to ineffective or even incorrect solutions that take you off course. Often, consumers of the data i.e. educators are too eager to draw conclusions from the data, without evaluating how reliable the data is. Is it a good measure to answer your questions? Are there limitations? Was the data collected with fidelity? Was there room for error?
Hand in hand with this is the task of supporting the team in building their tech and data literacy skills. Thinking about the quality of the data being used is an essential step before we use it to guide our decisions.
As we move further into the 21st century, the world continues to change rapidly, and our education systems must keep up. The key to this lies in adopting data-driven approaches to continuous learning and improvement in our schools. By collecting and using data purposefully, we can ensure that our students receive a high-quality education and that our schools remain relevant and effective. So, let's embrace this mindset of learning and adaptation, and start implementing data-driven approaches in our schools today!
