With the progressive adoption of machine learning, the education sector will soon witness a major transformation.
Over the years, digital technologies have modified the education landscape drastically. The recent breakthroughs in Artificial Intelligence (AI) build even more anticipation. Machine learning, usually seen as a part of AI, is anticipated to become a critical factor in education innovation.
Simply put, Machine learning is the development of computer algorithms. It learns from input data to identify common patterns and automate the decisions accordingly. When applied to education, machine learning processes the data of student profiles and administrative records to provide game-changing solutions.
This enormous power of machine learning is present within both classrooms and institutions as a whole, respectively taking the forms of personalized learning and automated administrative tasks.
For students and teachers: Personalized learning
The new technology aids teachers and students by actively promoting personalized learning. It is a model that allows relevant learning experiences to suit individual interests, needs, and strengths.
Machine learning realizes this principle by suggesting customizing programs or materials that address students’ weaknesses or maximize their strengths.
The system first consumes, aggregates, and analyzes massive volumes of input student data; including but not limited to:
- Attendance records
- In-class participation
- Assignment for each subject
- Exam grades
As the patterns in the database are identified, the tool will generate relevant student academic profiles and suitable recommendations for teachers or tutors.
One such use case is a writing-to-learn tool that aims at helping struggling students. It is built on the premise that writing assignments better reflect a learner’s understanding of a certain material, compared to multiple-choice quizzes. With automated text analysis (ATA), the tool pinpoints the submitted assignments’ strengths and weaknesses. Thus, identifying which individual has difficulty.
In short, with machine learning, students enjoy a tailored, self-paced learning experience that is based on their strengths, needs, skills, and interests.
Meanwhile, teachers receive considerable assistance in forming a suitable teaching approach that encourages students’ progress.
For educational administrators: Automation that facilitates greater values
In the future, with machine learning, we can fully automate a wide variety of administrative operations within schools and academic institutions. Based on the mentioned principles, machine learning makes highly-educated decisions to ensure effective operations.
As a result, educators soon will enjoy speedy and satisfactory completion of essential; yet usually mundane tasks, such as:
- Logging exam scores
- Scheduling classes
- Processing students’ tuition
More importantly, machine learning can provide enormous assistance in promoting core education values; such as substantial moral development or equal education access.
By determining vital patterns and suggesting the most sensible teaching methods, machine learning enables educators and administrators to make informed, considerate decisions to realize these ideals.
To illustrate, when implemented in predictive analytics, machine learning helps provide highly reliable predictions of the risk of school dropout in a certain area. It can generate forecasts based on large-scale administrative data, such as demographic characteristics. They then serve as important references for future plans, interventions of local educators and administrators to reduce the dropout risk.
In conclusion, with prospective applications that promise efficiency and empowerment, machine learning will become a key player in the education sector. We can expect to see the technology growing continuously in both popularity and sophistication.