As colleges and universities seek to invigorate ethics education, they need methods to identify where and describe how ethics is already present across their curricula. Meeting this need is complicated by the fact that much ethics education occurs in courses not explicitly focused on ethics or morality. In this paper, we review recent methodological advances before presenting a new Ethics Course Identification Tool (ECIT) that combines application of an expert-derived weighted dictionary and natural language processing methods to identify ethics-related courses based on their titles and course catalog descriptions, even when the terms “ethic” or “moral” are not present. Two studies, the second a pre-registered replication, revealed considerable interrater reliability among experts in ethics education regarding the ethical relevance of courses. Critically, both studies revealed strong correlations between expert judgments and ECIT scores. This empirical evidence points to a shared understanding of ethics education among experts, and it supports the valid use of the ECIT to rapidly and reliably identify ethics-related courses. Based on these findings, we propose that the ECIT can be used both to advance research on trends in ethics education and to help target interventions to improve ethics education at colleges and universities.

当学院和大学寻求振兴道德教育时，他们需要方法来确定道德在其课程中的位置和描述方式。由于许多伦理教育发生在没有明确关注伦理或道德的课程中，因此满足这一需求变得复杂。在本文中，我们回顾了最近的方法论进展，然后提出了一种新的道德课程识别工具（ECIT），该工具结合了专家衍生的加权词典和自然语言处理方法的应用，根据课程名称和课程目录描述来识别道德相关课程，即使“伦理”或“道德”等术语不存在。两项研究（第二项是预先注册的复制品）显示，道德教育专家在课程道德相关性方面具有相当大的互信度。至关重要的是，这两项研究都揭示了专家判断与 ECIT 分数之间的密切相关性。这一经验证据表明专家们对道德教育有共同的理解，它支持有效使用 ECIT 来快速、可靠地识别道德相关课程。基于这些发现，我们建议 ECIT 既可以用来推进道德教育趋势的研究，也可以帮助有针对性的干预措施，以改善学院和大学的道德教育。