What do you want students to learn and achieve when they complete assessments?
Are there opportunities for AI to improve how students achieve these learning outcomes?
I coordinate a second-year unit of study, Genetics and Genomics, with ~400 students, and like many science subjects, students write a practical report about their experiments. While these are important skills to develop in science, working with research literature and writing scientifically is more difficult for students and researchers from linguistically diverse backgrounds. This semester, 49% of students enrolled in Genetics and Genomics speak a language other than English at home.
Speaking a language other than English at home and feeling a lack of support in their learning have been associated with contract cheating. Part of the appeal are the quick responses, which are difficult to match in large units of study.
Reminding students of the available support, including generative AI
This semester, I tried to address this by reminding students of the support available to them for their assessments, including generative AI. In my Canvas instructions for the practical report, the first thing students see is a warning about contract cheating, and a reminder about legitimate sources of support, including ‘GeneAI’ (a Socratic tutor that I built in Cogniti that is available to students 24/7), the discussion board, and the Learning Hub.
I built ‘GeneAI’ to be a Socratic tutor for students to discuss concepts related to genetics and genomics. Students learn at different paces and even with the option of anonymity on discussion boards, some students may be reluctant to ask what they think to be ‘basic’ questions. Some science subjects, genetics and genomics included, introduce a lot of new vocabulary that can be difficult for students to learn. I have seen questions about vocabulary asked of GeneAI and in other similar Cogniti agents, so these AI agents can provide students opportunities to ask questions that they would otherwise be too shy to get help for.
As students often ask for practice questions in preparation for quizzes and exams, Bloom’s Taxonomy has also been included in the agent’s design so that students can generate as many practice questions as they need. As a bonus, this approach has also been helpful for me to generate questions that I could select from and edit for quizzes and tutorials.
I embedded this agent in Canvas, which enabled me to scaffold with additional resources to support students’ interactions with AI (Cogniti and Copilot).
Being clear about how to engage with AI: Helpful vs less helpful
The assignment instructions encourage students to work with AI, with examples of where I believe AI may be helpful for this task. Given these suggestions, students are allowed to use AI however they choose, but are warned about properly reading the literature, referencing, and privacy concerns with any data they submit. I made these suggestions based on the assessment instructions, observations of how some (not all) AI tools may make up references, and the understanding that these are language models, so they may not be so helpful with numerical data. However, I am aware that students have different experiences with AI tools and so I avoid suggestions of how to or how not to use it.
At the end of the assessment, students are asked to reflect on how they used AI, or their choice not to use AI. I also provide some real examples of my reflections using it to help write rubrics and quiz questions.
What is stopping students from writing the whole report with AI? Nothing. However, there are parts that may require understanding of the experiments and theory to know what to ask. This is not a perfect solution, but this task is an opportunity to learn these concepts in preparation for the secured final exam.
I have found that giving students this guidance and asking them to reflect on AI use has given me insight into what they need help with, how they are interacting with AI to achieve this, and their proficiency in working with AI. It was interesting to read about what tasks they felt AI could be more helpful for, and their understanding of what they need to be particularly careful of checking. Besides improving their writing, I was pleased to see many students describing a collaborative approach where they used AI to help them understand the concepts, which they would then apply to their report discussions and literature search.
AI tools, such as Cogniti, will improve how we support students – we have already seen this in semester 1 with Dr MattTabolism and Dr NucleicAlice. We are also still learning how to use these tools and we can support students to do the same by guiding them to experiment as we do and observe where the benefits and limitations are.
Things you could try in your units
Things to try:
- Experiment with Cogniti: most of the hard work has been done for us. Some resources, e.g., lecture notes, and a simple prompt is enough to get started. Educational Innovation run regular introductory sessions on Cogniti.
- Suggest uses of AI that may be more helpful or less helpful in your assessments: reflect on your experience, how you use AI and what has worked for you. Reflect also on what areas students may want extra support in and whether AI can support that, e.g., improving succinctness, understanding content. You could even discuss with students to co-design this list. This may help clarify the expectations of the assessment and help students think about how they might use AI.
- Think about all the things you wish you could do, but perhaps do not have the capacity to do: can Cogniti do it? You can check out Teaching@Sydney articles for inspiration.
- Add your Cogniti Agent to Canvas: it is easier for students to access and enables you to add resources that support students’ engagement with AI. Feedback forms can also be added, e.g., SRES, link to Office Forms, so that students can tell you about their experience.
Tips to get started:
- Focus on opportunities: think about what students can achieve with AI, rather than looking for what AI may not do well (yet!).
- Be comfortable with not being the expert: we are all still learning how to use AI and it is still evolving. Take these as opportunities to learn from students.
- Be comfortable with uncertainty: AI may never stop hallucinating, but it does not mean we should avoid it. These are opportunities to develop critical thinking skills and evaluative judgement.
- Talk to colleagues: we have a growing community of practice to share ideas and help each other.
