Hands-On Exploration: Testing Generative AI Tools for Research Applications
Contents
Key terms
What We'll Do
This session provides practical activities to help you explore generative AI tools and understand their potential applications in research contexts. Working through the exercises gives you direct experience with what these tools can and cannot do.
Work through the three activities below, complete the core readings, and write the weekly reflection journal entry before the Week 2 session.
Activity 1 — Hands-On Exploration
Task: Interact with at least three different generative AI tools:
- Claude or ChatGPT for text
- A free image generator (e.g. Craiyon, Bing Image Creator)
- A code assistant, if applicable to your work
For each tool, try a task relevant to your research and consider:
- What did it do well?
- What surprised you?
- What went wrong?
Activity 2 — Timeline Exercise
In small groups:
- Construct an annotated timeline of AI milestones from 1950 to 2025
- Each group focuses on a different era and presents back to the class
Discussion question
What patterns do you notice? Why were there “AI winters”? What changed to enable the current revolution?
Activity 3 — Research Relevance Mapping
Individual reflection, then class discussion:
- Write down three tasks from your own research workflow
- The class collectively maps these to AI tool categories
Consider these questions:
- Which tasks are likely to benefit from AI assistance?
- Which are not?
- What are the risks?
Core Readings (All Freely Accessible)
Wolfram, S. (2023). What Is ChatGPT Doing… and Why Does It Work?
Intuitive explanation; no equations required. writings.stephenwolfram.com
3Blue1Brown (2024). But What Is a GPT? Visual Intro to Transformers
~27 min video; best visual introduction. youtube.com
Mollick, E. (2023). What Just Happened? Catching Up on the AI Revolution
Clear, non-technical orientation. One Useful Thing (Substack)
See the full reading list for five supplementary readings.
Weekly Assessment
Reflection Journal Entry (500 words)
Address the following in your reflection:
- Describe your prior experience with AI tools, if any
- What are your expectations and concerns about using AI in your research?
- What do you most want to learn from this course?
Due: before the Week 2 session.
Next Week: How Modern AI Systems Work
Topics we'll explore: next-token prediction at enormous scale; what the model “knows” (and doesn't); tokenization and linguistic equity. Come ready to experiment with prompts!
Drafted with Claude (Anthropic) and reviewed by Jonathan Shock before publication. AI-generated errors are possible — if you spot one, please email jonathan.shock@uct.ac.za. Full detail: AI Content Disclaimer.
© 2026 Jonathan Shock · MAM5020F: Generative AI for Research · CC BY 4.0