Data is one of the most powerful tools to inform, engage, and create opportunities for our students along their education journey.
Schools are turning to AI-driven data for a variety of reasons. Analysis that used to take a whole semester now takes a few days. AI platforms that collect individualised student data analyse it to gauge individual and classroom comprehension, giving teachers insight into their students’ strengths and challenges. This insight enables teachers to make specific adjustments to the curriculum to improve student understanding and allows teachers to tailor their teaching methods to optimise student achievement. Using personalised data, teachers also feel more confident when they meet parents since they have more customised details to share.
Data-driven AI’s benefits are forecasting and identifying student success, supporting struggling students, evolving curriculum to match student needs and demands, evaluating instructor performance, and optimising resources for better efficiency. Data-driven AI platforms also encourage student independence. Observing their data encourages students to set their own learning goals. With teacher assistance, they can implement beneficial changes in their learning processes.
My school uses an AI platform called MagniLearn to automatically create personalised exercises for students and collect data on their responses. The platform helps us organise, gather, manage, and analyse educational data on each student. It effectively combines big data technology, educational data models, and the expertise of professional education data analysts to assist our school’s teachers in interpreting data and surfacing actionable insights. Rather than multiple-choice, MagniLearn uses free-form answer methods, providing us with more personalised data by tracking each piece of vocabulary and grammar.
I track the results of the data analysis to gauge student efficiency. I use the data to set obtainable, realistic goals for students to work toward before the next test. I can adjust the learning and support accordingly. I also use the data to decide on student grouping and seating charts. For example, I placed a struggling student in front of the class to provide her with extra support when needed. Classes with lower overall test scores also receive targeted support from the administration to ensure student success.
Utilising personal data has always been a critical ingredient to a successful education. With the appropriate interpretation of data, educators make informed decisions that positively affect student outcomes. How student accomplishment data is gathered and applied determines how well it supports administrator and teacher instructional decision-making.
A new era of data in technology has transformed learning in education. The interest in AI EdTech is at its peak, with venture capitalists and private equity firms pouring more money into developing online learning tools. As educators recognise the need for advanced learning solutions, advancements in educational concepts, technologies, and learning content are moving increasingly fast.
Let’s leverage AI resources to enhance data collection in our education system. It’s time to foster and implement AI data-driven cultures in classrooms.