Abstract
Assessment design and implementation to cater for the realities of student use of AI represents one of the most compelling challenges currently facing universities. Principled assessment re-design is required so that universities can be confident that students are able to achieve learning outcomes without over-reliance on AI. Rapid AI developments have outpaced institutional and teacher abilities to redesign assessments and develop broader assessment literacy. Examples of good practice and their underlying principles are needed to frame teachers’ attempts to adapt their assessments to cater for AI realities.
This presentation elaborates and exemplifies three core principles of assessment redesign: flexibility, authenticity, and meaningfulness. Flexibility offers some degree of student choice and autonomy; authenticity is typically seen as relating to real-life uses of the discipline and this presentation complements this perspective with a broader, more social view of authenticity; and meaningfulness involves producing assessment artefacts that carry some personal value to students. The aim of these principles is to align assessment with students’ sense of self and well-being in motivating them to engage productively and ethically in the development of assessment work.
The presentation showcases how these principles are applied in an oral assessment in CAES2004 Communication and Community Engagement through Podcasting, a 6-credit undergraduate elective at the Centre for Applied English Studies. Oral assessment, particularly when it is interactive and developmental, is potentially a suitable assessment for current realities when unsupervised written work can easily be produced by AI. In the course, students form groups, develop podcast themes, then record, edit and distribute their episodes online. Through experiential learning, students reflect on their experience regularly to inform language use and production practices. Podcast submissions from students frequently indicate high student motivation and investment, and course feedback reveals students’ appreciation of the opportunity to exploit the assessment in diverse ways, the transferrable skills acquired, and opportunities to express themselves in meaningful ways. This presentation discusses practical course policies that contribute to positive student feedback and alignment with our assessment principles. Opportunities, challenges and limitations of the course in the context of AI developments are also discussed.
Our example is contextualised around language enhancement, whereas the principles and assessment mechanics are potentially generalisable to other disciplinary courses in HKU. Implications and challenges for broader assessment re-design in HKU are shared. Sustained support for the development of teacher assessment literacy and digital competence in the AI context is recommended.
Presenter(s) / Author(s)
