PERFECT – Providing Elaborated Response-based FEedback in Computerized Tasks
Feedback is a central aspect of learning. Through automation, computer-based instruction can provide high-quality, personalized, immediate feedback during practice. Nevertheless, most current e-learning products simply provide "verification feedback," i.e., telling whether a response is correct or not. This, despite the fact that research suggests that "elaborated feedback," i.e., explaining why a response is correct or not, can be much more effective. However, no research has been done on best practices for elaboration. Without a better understanding of the most valuable features of elaborated feedback, this kind of feedback may be useless and even harmful.
Our project intends to investigate this question of designing the most effective elaborated feedback. We will do this within the domain of mathematics education, using a Big Data approach, through existing massively-used platforms such as Khan Academy and ASSISTments.
Tomer is an alumni of Tel Aviv University's Interdisciplinary Program for Outstanding Students. He has a B.A. in Mathematics and an M.A. in the History and Philosophy of Science and Ideas. This year Tomer has started his Ph.D. studies in Education.
In the past few years he has been developing digital educational content in mathematics for Khan Academy, a free learning platform used by millions of learners across the globe.