Hamilton AI session feedback

Thank you for attending the "Foundational AI" and "Navigating Academic Integrity" workshops. Your feedback is crucial for refining future sessions. This survey is anonymous unless you choose to provide your contact details at the end.

Section 1: Impact on Practice (Pre vs. Post)

Please rate your level of confidence regarding the following areas:

Practical AI Usage

Comparing your ability before the workshop to now, how confident do you feel using generative AI tools (e.g., Gemini, Teachable Machine) to create resources or complete admin tasks? (1 - not confident and 5- very confidents)

AI detection and ethics

Comparing your mindset before the workshop to now, how confident do you feel in recognizing when AI has been used appropriately versus inappropriately in student work? (1 - not confident and 5- very confidents)

Designing AI-resilient assessments

Comparing your mindset before the workshop to now, how confident do you feel in designing assessments that remain valid and reliable, even when students have access to AI? (1 - not confident and 5- very confidents)

Section 2: Workshop Content & Relevance

Which specific topics did you find most valuable for your immediate teaching practice? (Select up to 2)

The workshop discussed shifting focus from "Knowledge Acquisition" to "Knowledge Application". To what extent do you agree that AI will necessitate this shift in your science classroom?

How would you rate the balance between "Theory" (History, Ethics) and "Practice" (Demos, Activities)?

A

Too much theory

B

Good balance

C

Too much practice

D

Other

What topic would you like to see covered in a future "Deep Dive" session?

A

Advanced Prompt Engineering (e.g., Chain of Thought)

B

Customizing AI for Specific Science Curricula (NCEA levels)

C

More Hands-on "Teachable Machine" Projects

D

School-wide Policy Development

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