The Design and Implementation of PAGE

Personalised Assessment Generative Engine

Abstract

The adoption of online learning has introduced a multitude of opportunities and complexities. This shift poses a challenge in preserving the integrity of digital assessments, which is further accentuated by the increasing accessibility of online resources. Assessment design has emerged as a promising solution to tackle this issue, with a specific focus on creating assessments that are resistant to cheating behaviour. Personalised assessments, in particular, have shown promise in reducing academic dishonesty. This work introduces the Personalised Assessment Generative Engine (PAGE); it is designed and implemented to simplify the process of creating and administering personalised digital assessments for the Canvas Learning Management System (LMS). Following the design science research methodology, PAGE has been developed to efficiently generate personalised assessments with variations in questions, answers, and additional materials. Deploying PAGE in a university course uncovered several benefits and considerations for educators with using such a tool in their classrooms. The strengths and weaknesses of PAGE are analysed, highlighting its application areas and potential avenues for future work.