Select crucial syllabus statements for ethical GenAI use, identify differences between restrictive and enabling policies, and determine which course components require revision first.

Key Topics:

1. Selecting most crucial statement for course syllabus regarding ethical GenAI use in Middle East. 
2. Determining statements that emphasize human agency and ethical citation. 
3. Identifying core difference between restrictive (zero tolerance) and enabling (authorized use) GenAI policies. 
4. Matching policy examples to correct type (Restrictive or Enabling). 
5. Determining which course component (Course Learning Outcomes, Grading Rubric, Attendance Policy) must be revised first. 

Match university stakeholders to their primary responsibilities, classify professional development needs, and identify central goals of institutional GenAI policy.

Key Topics:

1. Matching university stakeholders (IT Department, Faculty Senate, Research Office) to primary responsibilities. 
2. Determining each stakeholder’s role in developing GenAI policy framework. 
3. Classifying professional development needs as ‘technical’ or ‘pedagogical’. 
4. Distinguishing between prompt engineering training and data ethics workshops. 
5. Identifying central goal of institutional GenAI policy as mandated by UNESCO Guidance (fostering human capacity). 

Determine critical factors for long-term validity, select necessary faculty actions against homogenization risks, and classify GenAI advancements as challenges or opportunities.

Key Topics:

1. Determining most critical factor for ensuring long-term ethical and cultural validity of GenAI-integrated pedagogy. 
2. Selecting continuous interdisciplinary review as key factor for sustained validity. 
3. Selecting necessary faculty actions to guard against homogenization of academic thought. 
4. Determining actions like promoting comparative analysis of AI outputs and human texts. 
5. Classifying GenAI advancements (multimodal AI, EdGPT) as immediate challenges or long-term strategic opportunities.