I Am Responsible for Who I Become: Reframing Students' Sense of Responsibility for Their Ethics and Academic Integrity
Patricia Grant et al.
What the paper says
Academic integrity is a key pillar of quality education. Academic integrity scholars believe character development is a must-have for any higher education integrity framework especially with the advent of Gen AI. Moreover, several business ethics education scholars are calling for a return to a curriculum which focuses on the moral growth of students. These researchers converge in holding higher education institutions responsible for the character development of their students. Recent academic integrity and character education scholarship proposes neo-Aristotelian virtue ethics as a workable framework on which to ground character development. According to neo-Aristotelian virtue ethics, life is a task where decisions build or erode one’s character. Inspiring students to pursue excellence throughout their education journey and beyond, presents ethics as an intrinsic aspect of working well. In this way students are helped to reframe ethics and academic integrity as an existential task, of taking responsibility for who they become. This paper contends that higher education institutions should undertake character education because of the potential misuse of Gen AI and to restore relevance to ethics and business ethics courses. It is important to incorporate a neo-Aristotelian approach to character development as a central theme in ethics or business ethics courses, alongside drawing on academic integrity experiences from other subjects as relevant and tangible case studies. This article presents the Character Development-for-Excellence Framework, explores related pedagogical strategies, and outlines how higher education institutions can support and extend character development beyond the classroom.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.