Using generative AI to make students more human
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The document discusses the integration of generative AI (GenAI) in education, particularly in journalism, highlighting challenges such as lack of critical reflection and feedback from students. It emphasizes the importance of clearly attributing AI usage and provides guidelines for effective use to enhance learning and creativity. Next steps include evaluating teaching objectives, addressing barriers, and assessing the role and risks associated with GenAI in the learning process.
Using generative AI to make students more human
- 1. Using AI to make students more human Bruker AI for å gjøre elevene mer menneskelige
- 2. 3 things ● How I experimented with genAI in teaching ● What it told me ● What to do next
- 3. The challenges ● Students not reflecting critically ● Students not seeking feedback ● Students reading to pass, not to learn ● Not having the ‘codes’ to access industry
- 4. The class ● Using genAI tools to help reflect and improve ● Getting the best marks (and avoiding a zero) ● Writing prompts as a key skill for employability
- 5. Reference: AP. Generative AI in Journalism: The Evolution of Newswork and Ethics in a Generative Information Ecosystem, April 2024, https://drive.google.com/file/d/1rXruz2wQLAXmUtzm1B7lJCpxdWbOHijS/view Industry concerns
- 6. Reference: AP. Generative AI in Journalism: The Evolution of Newswork and Ethics in a Generative Information Ecosystem, April 2024, https://drive.google.com/file/d/1rXruz2wQLAXmUtzm1B7lJCpxdWbOHijS/view Industry practices
- 7. Class themes ● Generating story ideas and data angles ● Chart suggestions ● Identifying sources (+ diversity) ● Technical help: spreadsheet formulae ● Editing: feedback Template prompts > iteration > review
- 8. Li’s high level categories of journalism 1. Gathering information: source types; methods; source maintenance 2. Sensemaking: ideating; newsworthiness; analysis; archival; multimedia 3. Editing: clarity; verification; legality; standards 4. Publication/distribution: engagement; discussion; formats; liveness; analytics 5. Productivity: organisation; CMS; time; planning; coordination 6. Journalism training: general; writing; tech
- 9. 1. Gathering information: source types; methods; source maintenance 2. Sensemaking: ideating; newsworthiness; analysis; archival; multimedia 3. Editing: clarity; verification; legality; standards 4. Publication/distribution: engagement; discussion; formats; liveness; analytics 5. Productivity: organisation; CMS; time; planning; coordination 6. Journalism training: general; writing; tech Li’s high level categories of journalism
- 10. GenAI tool use not mentioned If you’ve used GenAI tools without saying so, this is considered Category A plagiarism and a zero mark 0% ● Attribute any use of AI ● Make it clear what is your work, and what is not ● Include evidence to clarify ● Identify what you did well — and could do better Evaluation includes evidence E.g. “I used ChatGPT to generate ideas around my dataset (see Appendix A)” 52-8% ● Copy and paste the prompt(s) and response(s) in full ● Use a different appendix for each example ● Reflect on them Evidence and references E.g. “I used ChatGPT to generate ideas (see Appendix A) using techniques outlined by Marconi (2023)” 62-8% ● Draw on original sources used in lectures ● Focus on practical literature — don’t quote facts and stats ● Identify next steps + critical reflection and experimentation E.g. “I added prompts to guard against bias in terms of ethnicity, gender etc. (Heikkilä 2023. See Appendix B)” 72%+ ● Read about good practice and try those techniques ● Don’t settle for the first results: experiment ● Reflect on what works and what doesn’t Different levels of use/evaluation Note: grades indicate credit for use of genAI only, not the overall grade
- 11. Evidence this in your evaluation for credit I used ChatGPT to suggest potential chart types for my story (see Appendix C).
- 12. Even better, reference learning too. I used ChatGPT to suggest potential chart types for my story (see Appendix C), ensuring that my prompts asked it for explanations that would help me make a decision (Flourish Webinars 2024)
- 13. What happened?
- 14. View chart ‘story’ at https://public.flourish.studio/story/2594313/
- 15. “Selecting people to interview … is something I've had trouble in the past with.”
- 16. “The suggestions it made helped me consider sources I hadn’t thought of contacting.”
- 17. “I turned to AI for suggestions on suitable story angles, but the outcomes did not align with my expectations. Nevertheless, this experience prompted me to view the data from a different perspective. Subsequently, I opted to explore patterns associated with COVID-19.”
- 18. What happened ● Students used the techniques — but did not admit to using for editing ● Little evidence of iteration ● Bias seen as an AI problem, not a human problem
- 19. “When reviewing the answers I was sure to pay attention to the answers provided to check for any potential bias in its answers”
- 20. What next?
- 21. Reviewing teaching ● What is our objective? ● What barriers are students likely to face in meeting that objective? ● What role can genAI play in helping reduce or remove those barriers? ● Is it practical or realistic to restrict the use of genAI? What might be lost and gained by doing so? ● What risks are there in using genAI for that? ● What steps can be taken to reduce those? ● What opportunities are there for reflection and review?
- 22. Templates, checklists? ● A risk assessment of genAI usage - and measures ● A requirement to ask genAI for feedback ● A requirement to iterate?
- 23. Beyond ChatGPT ● Custom GPTs ● NotebookLM, ● AnythingLLM etc. ● Custom LLMs
- 24. What do you humans think?