A scoping review of reinforcement learning in education

Abstract

The use of Artificial Intelligence (AI) and Machine Learning algorithms is surging in education. One of these methods, called Reinforcement Learning (RL) may be considered more general and less rigid by changing its learning through interactions with the environment and specifically the inputs received as rewards and punishments. Given that education has shifted towards a constructivist approach and uses technology such as algorithms in its making (e.g., instructional design, delivery, assessment, and feedback), we are interested in taking stock of the effect RL may play in today's teaching and learning. We conduct a scoping review of the literature on RL in education. This work aims to open discussions on the pedagogical paradigm of RL and various types of bias introduced in teaching and learning.