Assessing students in a genAI world
The advent of easily accessible generative AI (genAI) has turned assessment in the higher education sector upside down. GenAI is fundamentally a sophisticated version of the auto correct you might have on text messages on your phone. It predicts text based on 1000s upon 1000s of written items on which it has been trained. So, in higher education, where assignment content is generally repetitious, it can produce acceptable essay responses or other written content in a matter of seconds. This is also true of assignments which might seek to establish a student’s understanding of a Lutheran perspective.
As a confessional church, there is a body of primary and secondary scholarly literature which is well established. This uses generally agreed ways of expressing our biblical, theological and pastoral understandings. GenAI has been trained using this body of literature, and in the main it can reproduce it very well. This has major implications for the way ALC assesses the various units it delivers. Ignoring or banning genAI is not a viable option. Its use has become embedded in workplaces, including those in the church, almost overnight, and there is no reliable way of distinguishing work written by a student from that written using genAI. This means a complex and nuanced response to genAI is necessary.
Before teaching commenced in 2025, the ALC faculty gathered offsite for an extended period to think through how we write assessments which acknowledge the impact of genAI. “How can we ascertain what a student knows, understands and can apply?” is obviously the central question. Short of assessing every unit using only hand-written, supervised exams (which make it harder to misuse genAI, although many educators argue written exams provide only limited insight into what students know and understand, let alone what they can apply in practice), it’s a really hard question to answer. However, after two days of intense conversation, the faculty came away with various ideas for amending the assessment tasks in their units.
The aim is to create academically rigorous, contextualised, practical assessment tasks which encourage students to reflect deeply, analyse critically and provide accurate evidence of what they understand and can do. It was well worth the time spent together sharing ideas and growing our capacity to engage students in valid assessment leading to good vocational practices in a genAI world.
