Intelligent Biofeedback Comprehension Assessment: Theory, Research, and Tools

Abstract

The present paper describes the use of nonintrusive biofeedback sensors (e.g., ECG) and eye-tracker to study the cognitive load (CL) associated with two mental tasks: a) content reading and comprehension b) code review. The paper addresses the theoretical underpinnings of the comprehension assessment included in content reading (for understanding) and code review evaluation using biofeedback sensors and Artificial Intelligence (AI) techniques. Moreover, it demonstrates the current research directions that the authors developed in evaluating these two tasks. Finally, the paper presents the design of one of the tools being developed to use biofeedback sensors and AI to evaluate the code review quality by assessing the code reviewer's comprehension and engagement level.