Computer power in education promises to deliver tailor-made teaching programs that can meet the personal needs of every child. Several so-called blended learning projects have been set up, combining data mining with the insights of teachers to generate personalized competence-based learning. Some predict that the one-size-fits-all model of current education will become history when these programs turn out to be successful and scalable. However, others claim that education is not only about transferring knowledge but also about social processes that cannot be realized by offering individualized curricula.

Our observations

  • The Bill & Melinda Gates Foundation and the Chan Zuckerberg Initiative have joined forces to support research on and development of educational strategies with the help of technology and bring them to the classrooms of primary schools. The focus is on the development of new measures, new ways of teaching, and new technologies for tracking and supporting students’ writing ability, math skills, and “executive functions”, such as self-control and attention.
  • Altschool is an educational startup that was founded in 2014 with locations in New York and San Francisco. Its teaching methodology is intended to respond to individual students’ needs and integrate technology into their course structure. They aim to revolutionize education by offering personalized competence-based learning and unconventional classroom environments where students can move freely through the school building instead of sitting in a classroom. Tuition runs from $ 20.000 to $ 30.000 a year per child.
  • Portfolio School is an initiative that not only uses technology to optimize personalized competence-based learning, but also uses technology to connect children of their primary schools to the outside world. Their young students have reached out to NASA engineers, and New York University music education grad students have guided them in producing a soundtrack for their moviemaking project. Its cofounders Schachtel and Habib claim that children need to know how to find the right means to educate themselves. “They might have to find mentors, and we want them to start getting comfortable with that idea as soon as possible.” Tuition is $ 35.000 a year per child.

Connecting the dots

Personalized Learning has become a broad field, due to the many different possibilities offered by technology in education. It could refer to educational platforms such as Blackboard or Canvas, which offer personalized support to teachers and students throughout their education. These platforms are common in universities already, high schools and primary schools only recently started implementing them. Online tutoring can also offer personalized learning, simply by connecting a tutor to a student for one-on-one additional lessons. Mainly children that attend primary school are making use of this possibility. These forms of personalized learning differ significantly from personalized competence-based learning through technology. For in the latter, the use of data mining is a crucial component. Data mining in this form of personalized learning is used to analyze school performance and social and emotional behavior in order to reply in the most optimal way. It aims to engage the student in the learning process on his/her personal terms.
Several experimental projects have been set up to explore the potential of blended learning, using data to support the teachers in educating their students. This data is collected through video and audio recordings inside the classrooms and through laptops or tablets that are used by students to study. According to these initiatives, increased integration of technology will allow for more data tracking, which could help educators tailor their instruction to individual students’ needs. Well-analyzed data could help teachers identify struggling pupils long before a graded evaluation. Teachers could also improve their own teaching by reviewing their lessons later on. Because these initiatives combine teacher and technology to educate children according to their personal needs, children no longer need to be separated by age, nor do they have to sit still in rows for hours, facing the teacher. This allows for unconventional set-ups with open-plan spaces instead of classrooms, in which children are no longer bound to separate classrooms.

Although these ideas are appealing and it seems to be evident that competence-based learning will deliver content more effectively than a one-size-fits-all approach, it is still far from obvious that personalized competence-based learning by means of data mining is ideal. There are numerous pedagogical reservations that have not yet been properly addressed. The social aspect of learning, for example, is compromised when children spend a huge part of their time on individual learning instead of collective teaching. It is not yet known whether being in the same space will provide an equal or sufficient social learning experience, and if it doesn’t, it is unclear how these shortcomings can be compensated. Another objection might be the unavoidable implementation of tablets and laptops in order to collect data from children’s individual learning development. Other projects, such as the Steve-Jobs schools in The Netherlands, implemented iPads in primary schools to let children get used to technology from an early age. The first results of this experiment were not positive. The test results of children were not optimal and the classes were messy, according to teachers. Practical disadvantages are caused by the large scale on which data needs to be gathered and analyzed, which jeopardizes children’s privacy.. Furthermore, the costs of these teaching methods are still exorbitant, making it impossible to implement in many schools.
Since entire generations of young minds are at stake in education, it is likely that the implementation of personalized competence-based learning through technology is still a long way from becoming reality due to pedagogical and practical obstacles. However, because of the huge advantages it can deliver, it is also likely that this development will continue and finds its way into the education of children one way or another.

Implications

  • Although schoolboards and governments will be hesitant to implement data mining technology into the education of their young, caretakers are free to use them for their own children. Because of the tempting possibilities this new teaching method holds, educational tools that offer personalized competence-based learning might therefore first find their way into the private upbringing of children. This might cause similar concerns to those about shadow education, such as inequality among students because many parents cannot afford it and exposure to learning content and methods that have not been thoroughly tested.
  • Data mining technology comes from commercial companies such as Microsoft, Alphabet and Facebook. The initiatives to explore the possibilities of this new educational method are also carried out with the help of such parties. It is unclear how big a part they will play in this development: To what extent do they influence the content of what will be learned if they are in control of analyzing data about children and provide the interface of the teaching materials?