Gathering learner data
The collection and analysis of individual data may one day lead to benefits for teaching and learning in the form of education that is specifically adapted to individual children, a practice known as ‘precision education’. In gathering detailed information, protection of personal data will be essential, requiring sophisticated and secure data management systems.
Precision education is a possible future avenue for teaching and learning that takes into account many factors about each individual learner, tailoring learning input to suit the child’s needs. Understandably, for this to be possible and effective, it will be necessary to gather vast amounts of data. This process of data collection has already begun, in the form of the many studies that aim to uncover the psychological and neurological processes that underpin learning.
“Individualised educational practices would be for everyone – every learner would receive tailored materials.”
If precision education is to come to fruition, each individual learner will need to provide their own data in order to establish which type of learning materials best suit them. It is important to highlight that individualised education would differ from a learning styles approach, which is not based on evidence. Instead, precision education would draw on the best available evidence from a host of factors which might include test scores, genetic data, the learner’s own interests, and environmental factors.
One of the key anticipated benefits of this approach to learning is the identification of difficulties. Proponents of precision education hope that problems would be picked up on much earlier than current practices can manage. This prospect is appealing because extra assistance is thought to be best given as soon as possible to help each child develop important skills.
“Having an in-depth knowledge of one’s own strengths and weaknesses may allow individuals to choose whether to develop their weak areas or further their abilities in their strong areas.”
But it isn’t only those with difficulties who are set to benefit. Adaptation of materials based on each learner’s needs will also benefit those with no particular difficulties. Individualised educational practices would be for everyone – every learner would receive tailored materials.
Precision education may also lead to greater choice for the learner – in particular, adolescents choosing which subjects to focus on later in school. Having an in-depth knowledge of one’s own strengths and weaknesses may allow individuals to choose whether to develop their weak areas or further their abilities in their strong areas. This would be helpful when making career choices and developing the skills and knowledge needed for certain jobs. This also applies to adult learners, who would be better able to choose which areas need developing, and focus their learning armed with the knowledge of where they are now and where they want to be.
The rate of change in the level of learning input may be more frequent with an individualised approach. Under a tailored learning programme, material would change quickly to adapt to the needs of the student.
The potential benefit of this is seen when contrasted to a conventional educational system where a child might be in the top maths set and move to the middle set after a term of struggling. Under precision education, the child’s learning materials would change constantly based on their performance, helping them to progress rather than leaving them behind. In a similar vein, personalised programmes or strategies that do more harm than good may be dropped more readily. The continual analysis of individual data would highlight where the learning input is not having the anticipated impact.
“Under a tailored learning programme, material would change quickly to adapt to the needs of the student.”
Educators already tailor their practice to the needs of individuals based on the evidence and resources currently available to them. Precision education is not a million miles away from current educational practices. But it does require the gathering of more data, analysis of factors that affect learning, testing of different interventions, and ongoing analysis. It is currently unclear how this process might work in practice.
A very strong scientific understanding of the mechanisms that influence learning will be the first step towards the realisation of precision education. But, it will likely also require continued engagement with researchers, and technologies (such as complex computer programmes) that may prove expensive.
“The continual analysis of individual data would highlight where the learning input is not having the anticipated impact.”
Crucially, precision education will require buy-in from parents who will understandably have concerns about the use of their children’s data. Discussions surrounding privacy and security with policy makers, teachers, and parents will be essential. Data protection will be absolutely critical, requiring secure data management systems.
An ideal precision education would give teachers and learners a greater knowledge of the learner’s needs and ongoing progress. This would lead to increased choice over the skills and knowledge to develop further, leading to a satisfying learning experience and a successful future.