YEAR 5-7 TECHNOLOGIES

Open Ended

How do you think the way humans learn is different from how computers learn?

Multiple Choice

Why is it important to understand how AI makes decisions in our daily lives?

• Because AI is only used in research labs

• Because AI impacts/affects many things in our lives

• Because AI never makes mistakes

• Because AI cannot be trained

Multiple Choice

Which of the following is an example of how AI can impact society in both positive and negative ways?

• AI-powered medical diagnosis improving healthcare

• AI replacing jobs leading to unemployment

• AI helping in disaster prediction and response

• All of the above

Multiple Choice

According to the CSTA K-12 Computer Science Standards, what is one way data can be used to support a claim?

• By ignoring irrelevant information

• By organizing and presenting collected data visually

• By making random guesses

• By deleting all data

Open Ended

Explain how predictive data models are used in Artificial Intelligence to make decisions. Provide an example from daily life.

Multiple Select

Which of the following are examples of AI?

• Voice Assistants

• Self Driving Cars

• Helper Robots

• All of the above

Open Ended

How do you think the AI robot learned how to perform the task shown in the image?

Multiple Choice

Which of the following best describes the term 'feature' as used in the context of sorting items?

• A characteristic that an item is or has

• A group of items

• A way to organize data

• A prediction made by a computer

Multiple Choice

Which of the following actions is most closely related to making predictions in AI?

• Sorting items into groups

• Collecting information about the world

• Making a guess based on patterns in data

• Describing features of objects

Open Ended

What is the difference between 'data' and 'training data' in the context of AI decision making?

Open Ended

Explain how having more data can lead to more accurate predictions.

Open Ended

What features help us decide how to sort a group of objects?

Open Ended

Which of these doesn’t belong? Why? Explain what feature makes it different.

Open Ended

Why is it important for a computer to have more data from the human before making predictions?

Multiple Choice

What are the steps involved in teaching a computer to make predictions, as shown in the activity?

• A human finds and sorts data, teaches the computer, the computer makes predictions on its own

• The computer finds and sorts data, teaches the human, the human makes predictions

• A human finds and sorts data, the computer makes predictions, the human teaches the computer

• The computer finds and sorts data, makes predictions, the human teaches the computer

Multiple Choice

Based on the training data shown, which items would most likely belong in the 'blue' category?

• Disco ball, blue monster, blue shell

• Red crab, green pear, yellow tennis ball

• Red apple, green lizard, blue monster

• Blue monster, green cactus, red shield

Open Ended

How does the bonus challenge in Level 7 help you understand how computers learn to make predictions?

Open Ended

Which level was the easiest for you to sort? Why?

Multiple Choice

Which of the following is a reason why having more data can lead to more accurate predictions?

• More data reduces the chance of errors in predictions.

• More data makes predictions slower.

• More data always guarantees perfect predictions.

• More data confuses the AI model.

Multiple Select

Which of the following are real-world examples of AI being used to sort data?

• Self-driving cars identifying objects

• BakeryScan AI detecting pastries

• Sorting books by hand

• AI detecting cancer cells

Open Ended

How do the other animals and vehicles know that they are not the little bird’s mother?

Multiple Choice

In the context of AI predictions, what is the main difference between random predictions and AI predictions?

• AI predictions use patterns in data, while random predictions do not.

• Random predictions are always more accurate than AI predictions.

• AI predictions ignore data.

• Random predictions use machine learning.

https://studio.code.org/courses/k5-ai-data-2024/units/1/lessons/2/levels/2

Multiple Choice

According to the AI4K12 National Guidelines, what is a key difference between how humans and computers learn?

• Humans learn only from experience, computers learn only from data.

• Humans and computers both learn in exactly the same way.

• Humans can learn from emotions, computers learn from data.

• Computers learn from stories, humans learn from data.

Open Ended

Reflecting on today's lesson about how AI makes decisions, what is one way you think AI could be used to help people in your school or community?