The Use of Machine Learning in Personalizing Education

Hero Williams

My research is focused on machine learning and its application in the field of personalization of education. A personalized education system tailors curriculum for students based on their individual needs and preferences. Utilizing machine learning may improve data collection and help create more accurate categorization of students. The issue with traditional education is that teachers cannot always accommodate every students’ learning speed and their unique ways of learning. With machine learning algorithms, data can be collected about students learning, which can inform personalized curriculum. The tradeoff between a human teacher and an algorithm-based assessment of a student is often the students’ emotional and mental needs. This can be fixed if a hybrid model is employed - the teacher and student work together to determine the student’s goals and motivation while an algorithm fine-tunes the rest. This research can help students learn at their own pace and hopefully be more motivated in the process. Education is the foundation for an individual. I am hoping to continue with the Research Practicum and find a mentor who focuses on machine learning biases at the Space Telescope Science Institute (STScI).