Teaching and Research

Decisions to integrate technology into your teaching require reflection and often a degree of experimentation in order to make wise decisions that benefit learners and align with your teaching philosophy. 

This workshop goes into more detail on this.

In the first year, all AUC students are required to take an online self-paced course that provides an introduction to critical AI literacy.

To continue developing students’ AI literacy in your courses, here are some useful resources with activity and assessment ideas:

1. Harvard Metalab’s AI Pedagogy Project Assignment ideas
2. Duke University’s Pressing Prompts
3. Exploring AI Pedagogy
4. Teaching with AI book
5. Towards AI Literacy: 101+ Creative and Critical Practices, Perspectives and Purposes 

There is no straightforward answer to this question, but general guidelines are:

1. Ensure that the way AI is used does not offload the core elements of your essential work or learning outcomes to AI (read about the cake analogy to help you think through which elements are essential and which can be offloaded)
2. Develop students’ critical AI literacy so that they are aware of the possibilities of hallucinations and biases, and are always vigilant about checking the AI output against more credible sources, and trying to avoid passing these AI mistakes into their final work
3. Promote transparency about AI use, where students disclose where and how they have used AI. Here is a sample AI disclosure statement template.
4. If you plan to use AI in your course, ensure all students have access to whatever AI tool you choose (preferably one AUC subscribes to) so that no student has an unfair advantage over others

Consider the ways in which AI is being used in your profession, and what skills students need to develop (whether AI-related, or human skills such as critical and creative thinking).

You are welcome to sign up for a one-on-one CLT consultation.

There are no specific guidelines on this, but CLT encourage the following:

1. Only use AI on something you know very well so that you can revise the output of AI critically
2. Be careful about potential negative consequences of using AI, including AI bias and hallucinations, students’ rights, and your own duties as a professor.
3. Always revise and verify AI output against more credible sources
4. Always be transparent about your AI use by providing an AI statement at the end, even if using AI for small things like image generation and rubric creation
5. Never upload student work into AI tools without their explicit permission as this is a violation of FERPA and their privacy and intellectual property rights

We do not recommend ever using AI to grade student work (read more on dangers of using AI to grade)

CLT conducted a co-design session with students and faculty and these articles show how students responded quite negatively to the use of AI in syllabus creation, feedback generation, and assessment design.

There are many ways in which AI can be used to support researchers. Usually, the person needs to build their own research literacy before using AI tools that can help with efficiency. There are some discipline-specific tools for scientific research and quantitative and qualitative data analysis, and you would need to discuss with your department or peers in the same field. 

For an introduction to AI tools that can support the literature review phase of research, watch this workshop that discusses when you might use AI in your research, highlights limitations, and showcases a variety of available tools.