Polar Peaks Lesson A Classroom Plan for Ages 11–14

Polar Peaks: A 45-Minute Classroom Lesson Plan. Google AI Quests Polar Peaks gives teachers a practical way to introduce students to the decisions behind an AI system. Instead of asking learners to admire an AI result, the activity encourages them to explore how data is prepared, how models are tested, and why people still need to review the results.

Designed for students ages 11 to 14, Polar Peaks uses a brain-mapping story to introduce AI literacy concepts, including data cleaning, model testing, and human oversight. Google Research and the Stanford Accelerator for Learning developed the quest as part of the AI Quests series. Google’s Polar Peaks announcement describes the activity and its research-inspired storyline.

This Tech4GenZ lesson plan adds a prediction activity, an observation worksheet, a class discussion, and a five-question exit ticket. It is a documentation-based teaching proposal, not a report of a completed classroom trial. The suggested 45-minute schedule is flexible, and students do not need to finish the entire game to meet the lesson’s learning goal.

Key Takeaways

• Focus on reasoning: Students should explain how a data choice or test result relates to an AI system’s limitations.
• Check classroom access: Test the activity on the devices and network students will use.
• Record evidence accurately: Learners should separate what appeared in the activity from what they infer.
• Keep human judgment visible: Discuss what people need to inspect, question, or decide before trusting an AI result.
• Use current teacher resources: Google has published a Polar Peaks Teacher Guide and a dedicated teacher-training module. These are separate resources.

In this article

• Key Takeaways
• What Is Google AI Quests Polar Peaks?
• Prepare Your Polar Peaks Lesson Plan
• A Suggested 45-Minute Polar Peaks Lesson
• Copyable Polar Peaks Lesson Observation Worksheet
• Polar Peaks Lesson Debrief: Discuss Human Oversight
• Polar Peaks Lesson Exit Ticket: Five Questions
• Adapt Your Polar Peaks Lesson for Different Learners
• Your Next Step With the Polar Peaks Lesson
• Frequently Asked Questions

What Is Google AI Quests Polar Peaks?

Polar Peaks is the third activity in Google AI Quests. Google Research and the Stanford Accelerator for Learning created the series to help students understand how AI works and how to use it responsibly.

In Polar Peaks, students follow in-game mentors as they scan and map neurons to investigate a game character’s memory loss. The quest includes tasks such as data cleaning and model testing. Google describes the experience as a way to introduce careful human oversight and critical thinking.

The storyline draws inspiration from connectomics, the science of mapping neural networks in the brain. However, Polar Peaks is an educational simulation. It is not a medical diagnostic tool, and students do not need to share personal health information to participate.

Read the official Polar Peaks announcement for Google’s description of the quest.

Four AI concepts to introduce before the activity

Before students begin, explain these terms in simple language.

AI is also broader than chatbots. Google’s AI Quests FAQ describes the experience as code-free and states that the game itself does not contain generative AI experiences. Therefore, students do not need to write code or use a separate chatbot to complete this lesson.

Learning goal: By the end of the proposed session, students should be able to describe one data-quality problem, explain why a model needs testing, and identify a decision that still requires a person.

For example, a student might explain:

“If an image has the wrong label, a system could learn an unreliable pattern. A person should check the labels and inspect mistakes before accepting the result.”

This is an illustrative explanation, not a captured Polar Peaks game outcome.

Prepare Your Polar Peaks Lesson Plan

1. Check access, devices, and language

First, open the Google AI Quests activity on the same type of device and school network students will use.

Find Polar Peaks and rehearse the opening section. This helps you identify a suitable stopping point and prepare a backup in case the activity loads slowly. A successful test on a teacher’s home computer does not guarantee that every school-managed device will work the same way.

Google’s FAQ describes AI Quests as a free, web-based resource that requires an internet connection. It also provides technical recommendations, including an Intel i5-5250U 1.60GHz processor, 4GB RAM, and Chrome version 139 or later for the best experience. These recommendations are a starting point, not a guarantee of performance on every managed device.

Use the AI Quests FAQ to prepare.

Next, check the language your class needs. Confirm that the quest instructions and teacher resources are usable in that language. A language option in the website menu does not necessarily mean that every resource has been fully localized.

If devices are limited, students can work in pairs with two rotating roles:

• Navigator: Controls the activity.
• Evidence recorder: Records observations and explanations.

Alternatively, you can demonstrate a prechecked section on a classroom display. These are proposed teaching adaptations, not built-in multiplayer features.

2. Follow school approval and privacy requirements

Before using an external learning resource, follow your school’s approval process.

Google’s AI Quests privacy notice states that the game requires no registration and does not collect personal data such as names, email addresses, or IP addresses. It also describes the use of anonymous, aggregated gameplay metrics to improve the experience.

Nevertheless, treat this as the provider’s stated policy rather than an independent privacy audit or a replacement for local school approval.

Do not ask students to enter personal details, upload real medical information, or share screenshots containing information from other accounts or browser tabs. Keep paper reflections within your school’s approved assessment process.

Because Polar Peaks uses a memory-loss storyline, offer a neutral alternative example if a student prefers not to discuss that theme. Avoid asking learners to connect the story to a family member’s health.

3. Review the Polar Peaks teacher resources

Google’s AI Quests teacher resources page lists a Polar Peaks Teacher Guide.

The dedicated teacher-training module is a separate resource. Google announced on October 26, 2026, that the Quest 3 module would follow the next month. However, Google for Education published the course, Facilitate interactive experiences with AI Quests: Polar Peaks, on October 28, 2026.

The module helps educators facilitate the quest and discuss data accuracy, model performance, and human oversight. It includes learning materials and a short assessment.

Before teaching, review the current teacher guide and training material. They can help you connect the activity to your curriculum and prepare meaningful questions.

A Suggested 45-Minute Polar Peaks Lesson

Use this schedule as a flexible plan. If loading, reading, or discussion takes longer, pause at a useful observation and continue during the next lesson.

Completing every quest stage is not necessary to assess the explanation goal.

Before play: Predict what poor data could do

Start with a fictional example that is separate from the game:

A class is preparing pictures to teach a system the difference between a circle and a triangle. One triangle is incorrectly labeled “circle,” while another picture is too blurry to identify. What should students check before using these examples?

First, give students a moment to make a prediction. Then ask pairs to explain whether they would correct a label, obtain a clearer image, or set an uncertain example aside for review.

Emphasize that the appropriate action depends on the problem. Data cleaning does not mean deleting every difficult example.

Next, ask:

“If the system later makes a mistake, how would you investigate whether the examples contributed?”

Accept reasonable hypotheses without presenting a particular failure as inevitable. Keep the predictions visible so students can revisit them after observing Polar Peaks.

A proposed teaching sequence. Adjust the pacing to suit the class and activity access.

During play: Observe a data-quality choice

Keep the observation task small. Ask students to find one moment involving data preparation or quality.

They should record:

• What information was available?
• What appeared unclear, incomplete, or in need of checking?
• What choice or action did the activity show?
• Why might that action matter?
• What evidence supports the explanation?

However, do not ask students to invent a choice just to complete the worksheet. If they have not reached a relevant moment, they can write “not reached.” If the activity demonstrates an action without giving students a choice, they should describe that demonstration accurately.

During play: Record a model-testing decision

Next, ask students to identify a moment when a result is checked or a model is tested.

They should record what the activity actually shows. A successful animation or example does not automatically mean that a system is reliable in every situation.

Ask:

“What would make you want to run another test?”

Students might suggest checking a different example, inspecting a mistake, or asking whether the test examples represent the intended use. These are discussion possibilities, not controls guaranteed to appear in the game.

Help students distinguish between two statements:

• “It worked on this example.”
• “It will work on every example.”

The first is limited evidence. The second requires much more support.

Copyable Polar Peaks Lesson Observation Worksheet

Use the following worksheet for one observation cycle. Copy it into a document and add writing space beneath each prompt.

A learner code or pair number is enough. Do not require personal or health information.

POLAR PEAKS: PREDICT, OBSERVE, EXPLAIN

Pair or learner code: ____________________

Class date: ____________________

1. Before play: My prediction

If the data includes a wrong label or unclear example, I predict:

Because:

2. Data-quality moment

What I actually saw:

The choice or demonstrated action:

Why that action might matter:

Evidence from the activity:

3. Model-testing moment

What was checked or tested:

The result I actually observed:

One further check I would request, and why:

4. Human decision

A person still needs to:

Because:

5. Revisit the prediction

My prediction was supported / challenged / not yet tested by the observation because:

Evidence rule: Write “not reached” or “not shown” when appropriate. Keep observations separate from inferences.

Polar Peaks Lesson Debrief: Discuss Human Oversight

Bring the class back to one concrete observation before discussing AI in general. Otherwise, the discussion can become a list of broad opinions disconnected from the activity.

Ask these questions in order:

1. What did you actually see, and what did you infer?
2. Which data-quality action could affect a later result?
3. What does a successful test tell us? What remains uncertain?
4. Who should inspect an uncertain result before it is used?
5. What additional evidence would make you more confident?

Then give students this sentence frame:

“We observed __________. This suggests __________. However, we still need __________ before concluding __________.”

For example, a student might explain that one successful test is a reason to investigate further, not proof of universal accuracy.

Likewise, one failure can identify a problem without proving that every use of AI is worthless.

For a teacher-facing extension, Tech4GenZ’s AI Work Review Checklist applies a related principle to everyday work: outputs need traceable evidence and an accountable reviewer. Use it as an adult planning resource rather than a required reading assignment for this age group.

Polar Peaks Lesson Exit Ticket: Five Questions

Ask students to answer independently and in their own words. Allow a short oral response or a scribed response when appropriate.

Do not require a chatbot-written answer. The purpose is to assess the learner’s reasoning.

1. Data quality: Describe one problem that could occur in data. What would you do about it, and why?
2. Testing: Why is one successful example not enough to show that an AI system will always work?
3. Evidence: Describe one thing you observed in Polar Peaks and one conclusion that the observation does not justify. If you did not reach the activity, use the fictional shape example and label it clearly.
4. Human oversight: Name a decision that should remain with a person. Explain what the person should check.
5. Transfer: Complete this sentence: “Before I trust an AI result in another task, I will __________ because __________.”

Teacher guidance for the Polar Peaks exit ticket

Use these examples to evaluate the quality of students’ reasoning. They are guidance, not answers students must memorize.

For each response, award:

• 0 points: Missing or unrelated reasoning
• 1 point: A relevant idea with little explanation
• 2 points: A relevant idea supported by a reason or example

The possible total is 10 points. This is a proposed formative rubric, not a validated assessment or an official Google scoring system.

For example, “a human checks it” is relevant but incomplete. By contrast, “a human checks unclear examples because a confident result can still be wrong” explains both an action and a reason.

Use partial answers to plan the next explanation rather than label a student’s fixed ability.

Adapt Your Polar Peaks Lesson for Different Learners

If reading is a barrier

Preteach the four key terms. Read task instructions aloud when permitted, and offer the observation worksheet as sentence starters.

Assess the explanation rather than reading speed.

If devices are scarce

Rotate the navigator and recorder roles, or use a teacher-led demonstration that has been checked beforehand.

Nevertheless, each student should contribute an individual exit response.

If the game does not load

Use the fictional circle-and-triangle example for a data-quality discussion.

Label this lesson as an unplugged alternative, not as completion of Polar Peaks. Google’s teacher resources also list a low-connectivity adaptation of Market Marshes, but that is a different quest.

If learners finish early

Ask them to identify what evidence would challenge their explanation.

Alternatively, have them draw a simple flow:

Prepare data → Check a model → Inspect mistakes → Decide what to do next

Explain that real research may loop back through these steps.

If you need a display or handout

Use editable text and shapes so labels can be corrected. If you choose a generated design workflow, Tech4GenZ’s Canva Craft Editability Checks offers a useful reminder to inspect wording, editability, and exports.

No Canva account is required for the Polar Peaks lesson itself.

Fictional warm-up: identify a wrong label and an example that needs review before using the data.

Frequently Asked Questions

What is Google AI Quests Polar Peaks? Polar Peaks is the third activity in Google AI Quests, created by Google Research and the Stanford Accelerator for Learning for students aged 11 to 14. Students follow in-game mentors as they scan and map neurons to investigate a game character’s memory loss, with tasks such as data cleaning and model testing.

How long does the Polar Peaks lesson take? The plan is a 45-minute lesson: Predict (5 minutes), Introduce the task (5 minutes), Play and observe (20 minutes), Debrief (10 minutes), and Exit ticket (5 minutes). The schedule is flexible, and students do not need to finish every quest stage to meet the learning goal.

What should students be able to do by the end of the lesson? By the end of the proposed session, students should be able to describe one data-quality problem, explain why a model needs testing, and identify a decision that still requires a person.

What should I do if the game does not load? Use the fictional circle-and-triangle example for a data-quality discussion, and label the lesson as an unplugged alternative, not as completion of Polar Peaks.

Do students need to share personal information to take part? No. Google’s AI Quests privacy notice states that the game requires no registration and does not collect personal data such as names, email addresses, or IP addresses. The lesson also says not to ask students to enter personal details, upload real medical information, or share screenshots. Polar Peaks is an educational simulation, not a medical diagnostic tool.

Your Next Step With the Polar Peaks Lesson

Before teaching Polar Peaks, rehearse the activity, choose one observation goal, and prepare the worksheet. Then decide where you will pause for discussion, even if some students have not finished.

The most useful closing question is not “Did you beat the game?”

Instead, ask:

“What evidence would you need before trusting this result?”

That question gives students a practical way to carry the lesson beyond a single activity. They can use the same reasoning when evaluating AI-supported research, classroom projects, and other technology-assisted tasks. For a student-facing guide to using AI well for study, see How to Study With AI Without Becoming Dependent on It. For another classroom AI activity, see Gemini Math Worksheets: Create Three Levels Without Changing the Goal.