Session 1 10 October | Chapter 2: A New Era of Work | - How can AI be used to personalize learning experiences for students, and what are the potential benefits and drawbacks of this approach?
- What ethical considerations should instructors keep in mind when implementing AI tools in their classrooms?
- In what ways can AI support diverse learning needs, and how can instructors ensure that these tools are accessible to all students?
|
Session 2 17 October | Chapter 3: AI Literacy | - How can we balance the integration of AI tools with the need to develop students’ critical thinking and problem-solving skills independently of technology?
- In what ways can AI literacy be incorporated into existing curricula without overwhelming students or detracting from other essential subjects?
- What ethical considerations should be addressed when teaching AI literacy, particularly concerning data privacy, algorithmic bias, and the potential for AI to perpetuate existing inequities?
|
Session 3 24 October | Chapter 4: Reimagining Creativity | - How can the integration of AI in creative processes redefine our understanding of originality and authorship in art and literature? Research?
- In what ways can we balance the use of AI as a creative tool with the need to nurture students’ intrinsic creative abilities and critical thinking skills?
- What ethical frameworks should be established to address the challenges posed by AI in creative fields, such as the potential for AI-generated works to infringe on human artists’ intellectual property rights?
|
Session 4 31 October | Chapter 7: Policies | - How can we balance the need for innovation and career readiness with the necessity of maintaining academic integrity in the age of AI? Possible framing: it’s all about your personal credibility!
- What strategies can be implemented to ensure that AI policies promote equity and accessibility for all students, particularly those from underrepresented or disadvantaged backgrounds?
- In what ways can continuous evaluation and stakeholder involvement in AI policy-making help address the ethical challenges posed by rapidly evolving AI technologies?
|
Session 5 7 November | Chapter 8: Grading and (Re-)Defining Quality Chapter 9: Feedback and Roleplaying with AI | - In what ways can the definition of educational quality be reimagined to align with the skills and competencies required in a technology-driven world?
- What ethical frameworks should be established to address the potential biases and limitations of AI in grading, ensuring that all students are assessed fairly and equitably?
- In what ways can immediate AI feedback be integrated into traditional teaching methods to enhance student learning without creating dependency on technology?
|
Session 6 14 November | Chapter 10: Designing Assignments & Assessments for Human Effort | - How can we design assignments that leverage AI to enhance student learning while ensuring that the tasks remain deeply human-centered and promote critical thinking?
- In what ways can authentic assessments be developed to better prepare students for real-world challenges, and how can AI be used to support these assessments without overshadowing human judgment?
- What ethical frameworks should be established to address the potential biases and fairness issues in AI-assisted assignments and assessments, ensuring that all students are evaluated equitably?
|
Session 8 21 November | Chapter 11: Writing and AI | - How can AI tools be used to enhance the writing process without diminishing the writer’s unique voice and creativity?
- What are the potential long-term impacts of AI-assisted writing on students’ ability to develop critical thinking and independent problem-solving skills?
- In what ways can educators ensure that the use of AI in writing instruction promotes equity and inclusivity, rather than exacerbating existing disparities in education?
|
Session 9 28 November | THANKSGIVING DAY | N/A |
Session 10 5 December | Chapter 12: Assignments & Assessments | - How can the integration of AI in assignments and assessments be designed to not only measure student performance but also to enhance their intrinsic motivation and love for learning?
- In what ways can AI-driven assessments be structured to recognize and value diverse forms of intelligence and creativity, rather than reinforcing traditional academic metrics?
- What ethical frameworks should be established to ensure that the use of AI in educational assessments respects student autonomy and privacy, while still providing meaningful insights for personalized learning?
|
