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Similar to KWL (Known, Want to Know, Learned) charts...

AI: Benefits, Risks, Unknowns...

Ask students to outline a quick set of notes on

BENEFITS - ways you could use AI, ways you did use AI - details you would not have thought to include

RISKS - what are the blind spots, are there original thoughts/comparisons that you can come up with that won't be captured, what ethical risks do you want to consider?

UNKNOWN- is it complete data, what bias is included, is the prompt accurate/thorough?

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Flipping everything: Most of the graded work comes from in-class work (great success)

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Assessing quality of GenAI output, rather than focusing on generating the output.

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Using AI more regularly in class for activities, moderating that they are actually using it. One example could be generating interview questions for informational interview assignment, rewriting professional emails

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Economics has an AI tutor.  Should say how the student can use the tutor.

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Economics has an AI tutor.  Should say how the student can use the tutor.

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Peer Tutoring: Students using AI to prepare themselves more using GAI before coming for peer tutoring. Students do not work with peer tutors on a graded homework. Needs to know guidelines for how faculty will use it.

IPD Co-op student: Students understand conceptually how it works. They need to know why and how they are using AI to think deeper about the concepts.

IPD: University policy on AI has gaps.

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Blurb: how AI could be used to edit, but not write the paper.  Not doing all the thinking for them.  It could give specific instructions.  Students are afraid of getting in trouble.  If we go over how to use it makes students feel better.  Giving the assignment the opportunity.  Start somewhere: ethics, rhetorical purposes, etc.  

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Blurb: how AI could be used to edit, but not write the paper.  Not doing all the thinking for them.  It could give specific instructions.  Students are afraid of getting in trouble.  If we go over how to use it makes students feel better.  Giving the assignment the opportunity.  Start somewhere: ethics, rhetorical purposes, etc.  

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AI literacy hard to measure because things change so quickly (e.g., what AI can do, cannot do)

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What AI can do is changing so fast, so what we need to help students learn keeps moving and is difficult to plan for/design around.

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DMSB-Personalization of Case studies so analysis is delivered with LinkedIn Profile as context 

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DMSB-Personalization of Case studies so analysis is delivered with LinkedIn Profile as context 

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Personalization of Case studies so analysis is delivered with LinkedIn Profile as context

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Some students have criticized the use of AI by faculty to create assignments.

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Big differences in AI literacy among students make it difficult to determine what types of assignments would be useful.

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Blend assignments: Compare one with AI to one without AI (ex: job application).

Alternative: Have students guess which assignment is created by AI versus non-AI.

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Using AI to evaluate and test your code.

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DMSB-Case study analyzing responsible AI adoption in an organization 

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DMSB-Case study analyzing responsible AI adoption in an organization 

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Case study analyzing responsible AI adoption in an organization

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Maybe let ChatGPT do some of the response to student essays.

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Maybe let ChatGPT do some of the response to student essays.

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DMSB-Role playing exercise between student and an expert in their field 

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DMSB-Role playing exercise between student and an expert in their field 

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Role playing exercise between student and an expert in their field

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DMSB-Critical thinking assignment to compare and contrast the quality of genAI outputs

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DMSB-Critical thinking assignment to compare and contrast the quality of genAI outputs

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Critical thinking assignment to compare and contrast the quality of genAI outputs

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Identify counterarguments in Op-Eds.  Then, address why they are misguided in revising their Op-Eds.

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Identify counterarguments in Op-Eds.  Then, address why they are misguided in revising their Op-Eds.

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Making sure students understand job expectations re: AI and how to craft a resume without losing your voice.

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Debates and controversies.  Could have an AI present an argument.

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Debates and controversies.  Could have an AI present an argument.

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Working with and evaluating data sets

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Teaching of ML/AI but with high mathematical and programming experience expectations.

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They can also reflect on interview and get professor's feedback.

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They can also reflect on interview and get professor's feedback.

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Can use more for careers and presentations and panels.

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Can use more for careers and presentations and panels.

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Yes.  I have students use AI to brainstorm, if they want.  Ask them to their AI process at the end of the assignment.

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Yes.  I have students use AI to brainstorm, if they want.  Ask them to their AI process at the end of the assignment.

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Coop -- talk through it and have it re-write your resume or use AI to get tips on how well they answered interview questions. Caclulates ummms and eye contact.

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Co-op - Job search process, supporting writing cover letters and LinkedIn "tell me about yourself" statements, Interview prep (asking for questions based on job descriptions)

Physics- conversations are starting at department level meetings, have not used it for assignments yet

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Add your responses to the appropriate columns, using one post per idea:

1. Current AI Literacy Assignments : What assignments or assessments already exist where students demonstrate AI literacy?

2. Potential Assignment Redesigns : Which assignments could be redesigned with minimal effort to incorporate AI literacy?

3. Identified Gaps : Where are there noticeable gaps?