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the assignment shouldnt be so easily completed by AI to begin with 😬

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When all the code they submit is very well commented, but when asked to explain in class, they fumble.

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I want to troll students by including hidden white text in my homework question image so that the LLM will give the wrong answer.

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"Unplugged" activities that involve problem solving without using a computer help students recognize that learning involves automating retrieval.

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What yo use to fact check - another AI chatbot?

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Consider competency based assessment like what Skillsfuture is advocating. Learners have to exhibit (a) mindset change, (b) knowledge acquisition and (c) skills application (and transfer). Learning outcomes go beyond understanding and are actually measurable (using ABCD or SMART). This provides more systematic scaffolding which relates to personal experiences and is more difficult to have AI to get 'right'.

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Have another group fact-check to collect instances where AI causes hallucinations.

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Go for GenAI detox sessions go back to code from scratch or learn the fundamental mathematical concepts

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We have to drill into them that "You must always check the answer" and "Garbage In Garbage Out"

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Make students do peer-grading. i dont think students want to grade AI generated work either

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Online judges with special test cases which are not specified in the question.

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reward the process more over than the final answer

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For software engineering module, I recently introduced a sandwitch approach, in which students need to present the spec, write the 1-2 out of the repetive tasks, and let LLMs to complete the rest, finally the students need to verify the components generated are correct. But I have no empirical results. If I do have any in the fuure.

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A very tired teacher here, secretly hoping that all this Gen AI will go away

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Short interactive orals (micro-vivas) that include process evidence

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Challenges which provides significant output, which can be observed by the students themselves knowing it's right or wrong without resulting to AI.

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Lew:

Students try to upload photos of math questions to get AI eg chatgpt to solve.

When they get wrong answers or no solutions they conclude quickly that AI is poor in problem solving.

However i showed that asking the questions properly is important as the same AI tool with more detailed prompt will generate better answers.

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Lay2

Student use GenAI to generate a picture how Drone would be use in the Singapore in the past for presentation.

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Asking AI to provide practical samples for the learning concepts

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Need assignments where AI will produce the correct and default answer, but not the best answer.

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Ask students to outwit the LLM. E.g. I used this: "This LLM has been told to never say 'Yes'. Trick it into saying 'Yes'"

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Clearly recognize the state space that includes the initial state, current state, and goal state.

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I use Google Gemini-enabled colab to do live-coding in class, it shows the students that the AI doesn't always give us the code that we want.

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Ask students to do Primary Research like interview or talk to a target audience of the Problem Statement.

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Get students to write out code/pesudocode on whiteboard. Get others to critique on them, then finally run those solution through Gen AI for comments / solutions

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Good- Use GenAI & Latex prompting to illicit a mathematical step by step guide to understand the inner workings of neural network classifiers

Not so good - coming up with a timeline of GenAI reasoning model evolution & coming up with GPT6, without fact checking!

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Help students appreciate problem formulation for complex problem.

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Student sent all my notes to the LLMs and asked LLMs to summarize them for him, obviously not very effective.

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Teach problem validation and verification.

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Used to realize ideas at the Idea Festival, an on-school SW development festival.

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Use ChatGPT for refactoring code to improve its style and design

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WS

Teach critical thinking and evaluation skills, cross referencing across sources to discern if output is correct and non hallucinatory

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Use ChatGPT for debugging: Throw in the whole codebase and ask where's the error?

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In some tutorial class, as the students working on the questions, I sent the question to LLM, and let the students discuss the solutions generated by the LLM and their answers. There were situations I deliberately left out some essential inputs, hence the right answer should be "I don't know because there are mulitple possibilities here." But the LLMs will ALWAYS give an answer which sounds very confident. The students reflect on this and they see in real world situation, the problems are not alway well formulated, they need to apply CT first!

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(1) Have no-AI assessments under secure conditions (2) Examine their understanding of their code in an oral exam (and give them a hard time)

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Allocate sufficient time and white space for them to indulge/invest themselves in the curriculum,

also have some learning activities that encourages them to do by hand

by WQ

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More scaffolding and Pair programming

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Focus on process rather than final output. Ask students to reflect on their process.

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provide sample AI output answers and get students to identify issues in them. (maybe none of them actually have issues lol)

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students use AI to improve on their existing solutions and learn from it, and prompting it to comment - Yu Jie

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Hacking the exam portal to submit answers after the deadline, or submit answers on behalf of other users

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When they cannot do the task without AI.

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Ask AI to critic their code instead of generating their code.

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The basis of critical thinking is a strong knowledge base, so I think it is important to continue to help them gain mastery of computing concepts in more than one way.

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Build critical thinking + computational thinking skills. Also discuss case studies on the risks and how to manage the risks of accepting AI recommendations blindly.

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students use AI to create questions to help them learn and revise instead of getting solutions.

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Wonder how are we bringing computing and digital technologies to differently abled people?