How can Machine Learning improve the future of education? In the education sector, Machine Learning (ML) and Artificial Intelligence (AI) are very useful and can successfully improve teaching and learning processes. ML in education makes it possible to offer each student a personalised educational experience, guiding them in learning, and allowing them to follow the pace that best suits their potential and inclinations.
Distance teaching in the pandemic period has shown us how students need technological solutions and skills, both in emergencies and for routine activities, but also tutoring, evaluation method, and affectivity that only the comparison with other humans can guarantee.
Instead, what is required of research and educational policies is to question how AI can foster human learning and ensure that educators themselves lead the transformation, addressing requests to technology companies.
There is already a software adopted by some schools and universities that use AI both to increase the accessibility of content – subtitling of videos, transcription of lessons, automatic translation – and to increase the possibilities of learning and definition of teaching.
Adaptive learning analyses student performance in real-time and modifies teaching methods and curriculum based on this data. It helps to have personalised engagement and tries to adapt to the individual for better education.
The software helps to suggest the learning path for the learner that best meets their learning needs, as well as suggestions on materials and other learning methodologies.
Machine learning performs analytics based on individual student data and makes decision making automatic by improving the organisation and management of curriculums and content. It helps to divide the work and to understand each one’s potential, identifying which job is best suited for the teacher and which works the best for the student.
It also increases the efficiency of teachers, supporting them in tasks such as classroom management, scheduling, and such. This way, teachers are free to focus on projects that cannot be done by AI and that require human touch.
Many times, it happens that students fail to correctly understand the fundamental notions and concepts. With learning analytics, the teacher can gain insight into the data and perform insights that would otherwise be impossible. You can analyse millions of contents, interpret them, and then make connections and conclusions. This can have a positive impact on the teaching and learning process.
Furthermore, the learning analysis suggests the paths that the learner should follow. Students can benefit from receiving suggestions on materials and other learning methodologies from this type of software.
Predictive analytics in education is about knowing the mindset and needs of students. It helps to identify shortcomings and unsatisfactory results that the student may have in the future. For example, with class tests and semester results, you can figure out which students will perform well on the exam and which ones will have difficulty. This helps faculty and parents to stay alert and take appropriate measures.
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ML in the form of AI can be used to evaluate homework and exams more accurately than a human can, although some human input is required. However, the software guarantees greater validity and reliability, as there is a low possibility of error.
It will take some time before the Machine Learning is used on a large scale in the education sector but when it does, it will soon be able to revolutionise the entire education sector.