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Insights blog #3: 8 December 2023 – A forward-thinking approach


Using data to determine optimal subject interventions

Leveraging 2023 data – a forward-thinking approach to educational decision-making


By Jef Jacobs, DDD Insights and Innovation Manager


This article explores the significance of historical school data, especially final 2023 data, and its value in shaping our plans and actions for 2024 (and therefore, 2024 outcomes!).

It also provides guiding questions to help you make more informed decisions from historical data relevant to your context.

Analysing historical education data, including results from 2023 and earlier, empowers educators, policymakers and researchers to identify patterns and outcomes that enhance decision-making for the future. Reflecting on 2023 learner results facilitates the identification of successful teaching methods, interventions, and areas for improvement. Lessons learned from these outcomes inform data-driven adjustments to plans and tactics for 2024, reducing the risk of repeating ineffective strategies.


While valuable, it's essential to balance historical insights with a forward-looking approach, recognising the complex nature of basic education and our capacity for change.


Effective data-driven decision-making involves asking meaningful questions. Instead of expecting data to reveal something unknown, a better approach is to start your data analysis with a hypothesis or business question in mind. Below, we list six questions to ask yourself, irrespective of your role or level, which will maximise the value you get out of analysing final 2023 school data:


What is important to me, and what interests me?

For example, pass rates may be a performance indicator (important) for you, while changes in STEM subject participation are of interest to you.


Does the data include what I need to measure my performance metrics, and how did my entity perform against targets, assumptions, and peers?

Are my performance metrics improving, staying the same, or deteriorating? And by how much?

Can the data explain the factors behind specific measures?

For example, is there a specific subject that is responsible for most distinctions? How many learners failed 2023 only because they failed their Home Language subject?


Did my interventions work, and how well?

For example, did our weekend mathematics catch-up class improve the marks for those learners?


Can the data provide insights into the severity or quality of a metric of interest?

For example, what percentage of promoted learners almost failed?


Consider your final 2023 data today, with the above questions in mind.




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There is so much more we can do with the data we have. We can increase or decrease our assumption regarding the potential impact of a subject intervention, or we could analyse and compare all subjects. We could even analyse the effects of two or more interventions at a time. By combining education criteria, skills, and information to create informed interventions, we can deploy our scarce resources towards interventions that promise the greatest "return on effort" in achieving our specific learner outcome objectives.


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