The education sector is one of the main areas ready to be transformed by data. Public education in the nineteenth century emerged to replace private education, which was exclusive to the elite class. Private education was based on individual abilities and preferences, whereas the public education system reflected the industrial organizations of the time—factories with mass-production guidelines. Students were positioned as outputs in this mass-production line, and education was uniform for everyone. It was hardly possible to conduct public education in any other way.
At that time, data was used in an ad hoc manner, just like now: the result of one exam here, a student’s grade there! However, this data was not collected systematically or continuously, nor was it analyzed to determine the best teaching methods or the appropriate instructional approach for an individual student’s needs. Until recently, finding suitable methods for each student was very costly and exhausting, but these limitations are now being overcome. Consequently, we can imagine how education in the world of the future will look.
Data and information will be continuously analyzed to improve the performance of both students and teachers, enabling the identification of the most effective learning methods. Data will allow us to return to an era when education was individually tailored for each learner—a period that was lost due to the mass production of public education.
The educational environment will also be digital, allowing data to be easily collected under all circumstances. This means classrooms will be completely transformed. For example, students may listen to lessons from their teachers at home (instead of doing homework alone) and attend class primarily for problem-solving activities, when the teacher is present—a method now known as flipped learning.
Online classes are just the starting point. When a textbook becomes an electronic book, the e-reader can determine whether a student is actually studying and at what pace. If the student’s attention drifts (detectable through slower reading speed), the e-book can re-engage them with a question or a video. The e-book can even track whether the student studied on Friday afternoon at home or Saturday morning on the bus to school. It can also help determine whether better grades are correlated with studying after dinner or before dinner.
Therefore, in the world of education, data will transform from a static resource into a continuous flow. Instead of being collected all at once, information will be generated and gathered continuously. This ongoing flow of information enables the use of adaptive learning methods. Adaptive learning is based on analyzing a student’s performance and then selecting the appropriate content and learning pace for that individual.
For example, if a student correctly and quickly answers three math questions on trigonometry, the software recognizes that it should move on to a more challenging topic. If the student struggles with the circumference of a circle or sphere, the software presents additional questions in that area. Even top-performing students today have gaps in their knowledge, and adaptive learning ensures that they master all areas before moving on to the next topic.
By 2050, data will allow the education sector to return to its roots—providing personalized learning tailored to each individual. The current one-size-fits-all approach will no longer suffice. Education will become simpler, more affordable, and more widely accessible, allowing more students to benefit.
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