MACHINE LEARNING BASED REAL-TIME AND NON-DIGITAL FEEDBACK E-LEARNING TOOL

n our previous paper entitled “REAL-TIME AND NON-DIGITAL FEEDBACK E-LEARNING TOOL” that will be presented in the International Symposium on Educational Technology in Osaka, Japan July/Aug 2018, we demonstrated a new method for enhancing feedback to a lecturer while teaching in real-time. It is well accepted that interactive teaching enhances learning and critical thinking. However, by communicating to the lecturer what is not understood, the lecturer can provide a direct answer as well as other answers to issue(s) that may cause the student not to understand in the first place. But, in a practical situation, the lecturer cannot continually ask if the students have any question(s). Various e-Learning tools that provide feedback are available, but these tools are digital in the sense that these feedbacks are limited to a yes or no or a multiple choice. With this new method, the student can highlight on their devices the part(s) that he/she does not understand, and the system provides real-time analysis and feedback. In this talk the author will show an enhancement of this system by introducing a machine learning algorithm in the feedback system. This technology has the potential to improve radically the way lectures are delivered and student learning.