11/2018
︎ PAPER
Use of machine learning techniques for online education improvements: student intention and personalised learning path
︎ PAPER
Abstract:
Online education has provided many conveniences for people who are not able to attend conventional courses or programs in academic institutions. Different from the traditional face-to-face classroom method, students control over most elements: place, time, path, or pace. However, online education has not fully detached from the traditional form: lecture, quiz, and assignment, which makes the learning outcomes and efficiency remain insufficient. Meanwhile, huge amounts of data are also collected during the whole process from both teachers and students, which makes interventions with machine learning techniques possible. In this paper, the current situation of online education offered by universities and educational applications of machine learning will be discussed, and possible interventions will be proposed.
Online education has provided many conveniences for people who are not able to attend conventional courses or programs in academic institutions. Different from the traditional face-to-face classroom method, students control over most elements: place, time, path, or pace. However, online education has not fully detached from the traditional form: lecture, quiz, and assignment, which makes the learning outcomes and efficiency remain insufficient. Meanwhile, huge amounts of data are also collected during the whole process from both teachers and students, which makes interventions with machine learning techniques possible. In this paper, the current situation of online education offered by universities and educational applications of machine learning will be discussed, and possible interventions will be proposed.