Developing a design thinking artificial intelligence driven auto-marking/grading system for assessments to reduce the workload of lecturers at a higher learning institution in South Africa

Abstract

This study explores the development and implementation of a design thinking Artificial Intelligence (AI)-driven auto-marking/grading system for practical assessments and accurate feedback aimed at alleviating the workload of lecturers at an Online Distance eLearning (ODeL) institution in South Africa. The study adopts an iterative approach to designing and prototyping the system, ensuring alignment with the unique needs and challenges at an ODeL higher learning institution (HLI). The study outlines a Design thinking framework for developing the AI system, emphasizing empathy with user needs, clear problem definition, ideation, prototyping, testing, and iterative improvements. Integrating such a system promises to enhance operational efficiency, ensure fair and unbiased grading for assessments, and provide students with consistent, timely, personalized feedback. Tapping on theorists such as Michael Foucault and Joseph Schumpeter, this study contributes to the ongoing discourse on innovative solutions for educational challenges in South Africa by employing a design thinking framework and qualitative research methods. It provides insights for developing and implementing AI-driven auto-marking/grading systems in higher education settings. Cognizant of data privacy laws, the study will highlight the essential adherence to ethical guidelines in automated assessment processes and the successful implementation of AI-driven auto-marking/grading systems in ODeL. Additionally, this study aligns with several Sustainable Development Goals (SDGs), such as Good Health and Wellbeing (SDG 3), Quality Education (SDG 4), Decent Work and Economic Growth (SDG 8), Industry, Innovation, and Infrastructure (SDG 9). The study will have a follow-up article that will report on the data collected, and we will conduct another study where we seek the users’ feedback regarding the system.