Data-driven education technology to improve learning in the classroom and at home

The pandemic that originated last year has brought about a significant change in the way we see the world and how we relate to it. As far as the education sector is concerned, students and teachers at all levels have been forced to change the face-to-face teaching and learning methodology for a telematic system.

In this context, within the framework of the Aporta Initiative, the study "Data-based educational technology to improve learning in the classroom and at home", by José Luis Marín, has been developed. This report offers several keys to reflect on the new challenges posed by this situation, which can be turned into opportunities if we manage to introduce changes that promote the improvement of the teaching-learning process beyond simply replacing face-to-face classes with online training.

The importance of data to improve the education sector

Through innovative educational technology based on data and artificial intelligence, some of the challenges facing the education system can be addressed. For this report, 4 of these challenges have been selected:

·      Non-presential supervision of assessment tests: monitoring and surveillance of evaluative tests through telematic resources.

·      Identification of behavioral or attention problems: alerting teachers to activities and behaviors that indicate attention, motivation or behavioral problems.

·      Personalized and more attractive training programs: adaptation of learning routes and pace of students' learning.

·      Improved performance on standardized tests: use of online learning platforms to improve results on standardized tests, to reinforce mastery of a particular subject, and to achieve fairer and more equitable assessment.

To address each of these four challenges, a simple structure divided into three sections is proposed:

1.     Description of the problem, which allows us to put the challenge in context.

2.     Analysis of some of the approaches based on the use of data and artificial intelligence that are used to offer a technological solution to the challenge in question.

3.     Examples of relevant or highly innovative solutions or experiences.

The report also highlights the enormous complexity involved in this type of issues, so they should be approached with caution to avoid negative consequences on individuals, such as cybersecurity issues, invasion of privacy or risk of exclusion of some groups, among others. To this end, the document ends with a series of conclusions that converge in the idea that the best way to generate better results for all students, alleviating inequalities, is to combine excellent teachers and excellent technology that enhances their capabilities. In this process, open data can play an even more relevant role in improving the state of the art in educational technology and ensuring more widespread access to certain innovations that are largely based on machine learning or artificial intelligence technologies.

In this video, the author tells us more about the report: