Automated Essay Scoring (AES) Systems: Opportunities and Challenges for Open and Distance Education

Abstract

This paper reports on a systematic review of artificial intelligence applications in education (AIEd) with a special focus on automated essay scoring (AES) systems. AES systems may provide enormous time-savings, especially for large-scale distance teaching institutions with massive numbers of students, by reducing marking and freeing up teachers’ resources for individual feedback and personal support of distance learners. After an introduction on how AES systems function, a review corpus of published articles between 2007 and 2021 is synthetised to evaluate critical discussions and research trends in AES. Articles in the corpus generally evaluated either the accuracy of AES systems or the experience of users, and include implementation of AES systems in various settings (i.e., higher education, K-12, and large-scale assessments). Despite the opportunities that AES might afford for educational institutions, many questions related to the feasibility and validity of AES systems, their implementation, and the associated ethical issues are still unanswered. The findings of this research provide a solid foundation for this discussion.