AI and Rubrics-driven Assessments in Research-based Courses for SDG#4 and 9 - Yeung, Shirley Mo Ching (Journal of Ecohumanism, 2025)
The purpose of this paper is to review the ways of developing sustainable self-learning mindset via rubric-based skills development to become a self-learner with self-assessed rubrics on AI adoption for research-based courses in higher education. This paper draws conclusions from a qualitative nvivo analysis of selected nine papers on AI and rubrics-driven assessment on qualification framework (QF) level 5 in last five years. Based on the qualitative analysis on text search, the key elements in rubrics design of research-based courses in higher education (HE) at QF level 5 for sustainable development are: Rubrics on AI Tools for Skills Development’, ‘Ethical Thinking Development on AI’ (1,343 references), ‘Assessment on AI Argumentative Thinking’ (651 references), 'Evaluation on AI Creativity in Tasks’ (550 references), ‘Critical Thinking on AI in Social Inclusion’ (491 references) while ‘Declaration on AI Tools’ is found with 267 references compared with the top four elements. The findings are of managerial relevant to sustainable self-learning mindset, responsible management education curriculum design. It is recommended to validate the model proposed with on-going quantitative and qualitative data for a holistic view of rubrics on AI for competency building in research thinking and self-learning. It is time for academics, industry practitioners, NGOs and policy makers to consider these findings when exploring the ways of establishing a self-learning mindset via rubric-based skills development.