Determine appropriate group activities using GenAI for diverse viewpoints, identify ethical support for diverse learners, and match learning styles to personalized GenAI resources.

Key Topics:

1. Determining appropriate group activities where GenAI generates diverse viewpoints for student debate. 
2. Selecting collaborative tasks that maximize human-to-human interaction based on AI input. 
3. Identifying how GenAI supports diverse learners and non-native speakers ethically. 
4. Matching learning needs to appropriate GenAI support functions (real-time translation, language support). 
5. Matching student learning styles (visual, auditory) to personalized GenAI output types (mind maps, audio). 

Identify essential components of robust prompts, evaluate student prompts for ethical transparency, and sequence steps for ethical GenAI use in research.

Key Topics:

1. Identifying three essential components of robust prompts (Role, Task, Format/Constraints). 
2. Evaluating sample student prompts for ethical transparency criteria. 
3. Determining if intended use is clear in student-generated prompts. 
4. Sequencing steps for ethical GenAI use in postgraduate literature reviews. 
5. Ordering ethical workflow: Outline, Generate, Fact-Check, Refine. 

Determine effective methods for communicating GenAI policies, classify student questions by concern type, and select phrases summarizing faculty’s role in AI age. 

Key Topics:

1. Determining the most effective method for communicating GenAI policies to large classes. 
2. Selecting transparent and accessible communication strategies (syllabus statements, in-class discussions). 
3. Classifying student questions as policy/integrity concerns or technical/procedural concerns. 
4. Matching student questions to appropriate response categories. 
5. Selecting key phrases summarizing faculty’s role: ‘augmenter of human potential’.