Applications of machine learning in Education

In education, machine learning can support new ways of delivering teaching materials, especially in the online environment, and can help teachers to create personalised learning plans for individual students or carry out some routine tasks.

For example, applications are being developed that use machine learning to help teachers to grade student papers more efficiently. One such application – Gradescope – scans students’ responses to questions, and groups these according to the answers given. The teacher can then review these groups, checking that the system has allocated students to groups correctly, or manually changing who is allocated to which category. Once the teacher agrees to the proposed groupings, marks can be awarded accordingly. This feedback allows the system to improve its future performance. The system can also automatically compare a student’s answer to those of their peers, and direct the student to appropriate resources if they require further study in a particular area.

Machine learning is already used in online education systems; in Massive Open Online Courses (MOOCs) it is used to analyse student inputs, grading tests or other computer-based assignments, and in some computer vision functions. Using machine learning in this way allows course organisers to support a large number of students, and allocate human resources to less routine activities35. Further applications are being developed for the classroom, which will be able to track student understanding and make recommendations for future learning activity personalised to individual students to meet their particular needs.