A Robust and Non-invasive Strategy for Preserving Academic Integrity in an Open and Distance Learning Environment

Abstract

The aim of this research project is to evaluate a novel approach to providing academic integrity through behavioral pattern analysis for continuous and on-demand assessments. Our objective is to empower instructors with efficient and automated tools that promote accountability and academic integrity, while providing students with an accessible, non-invasive, privacy preserving and convenient validation of the student-generated academic content. The contributions of the proposed study are threefold: (1) the bridged anonymity gap between learners and instructors, (2) an open source learning technology that enhances academic integrity, and (3) understanding of how the behavioral-based biometric technologies are perceived by students and instructors.