Teacher login →NextBridge AI Lab · Grade 7

Sort, Guess and Group

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Teacher steps

  1. Explain the made-up fruit data: weight, sweetness, price.
  2. Classification: move the slider to set the “sweet” rule. Watch accuracy.
  3. Regression: see the best-fit line; move weight to predict price.
  4. Clustering: press Step until groups stop moving.
  5. Bias: tick “Remove green fruits”. What changes?
  6. Discuss: AI is only as fair as its data.

Time: 40 min · Maps to: CBSE Computational Thinking & AI, Class 7 (classification, regression, clustering, charts, bias)

Activity

1. Classification

Truth label: sweetness 6 or more = sweet.

2. Regression

3. Clustering (k-means)

Levels

  1. Try it: find the slider value with the best accuracy.
  2. Train it: predict the price of a 200 g fruit, then compare with a real shop.
  3. Break it & fix it: remove green fruits and see the line and groups change. How would you fix the data?

Badges:

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How AI works

  1. Classification puts things into labelled groups using a rule.
  2. Regression draws a line to predict a number; clustering finds groups without labels.
  3. If data is missing or one-sided, results become unfair.

What we learned: Classification puts things into labelled groups using a rule. If data is missing or one-sided, results become unfair.

Aligned with AI4K12 Big Idea 3: Learning & Big Idea 5: Societal Impact; mapped to CBSE Computational Thinking & AI, Class 7 (classification, regression, clustering, charts, bias).

Teacher guide

Goal: Classification puts things into labelled groups using a rule. Time: 40 min. CBSE unit: CBSE Computational Thinking & AI, Class 7 (classification, regression, clustering, charts, bias).

Discussion questions

  1. Which is classification, regression, clustering?
  2. Why did removing green fruits matter?
  3. Where could biased data hurt people?

Exit quiz

  1. Finding groups without labels is ___.
  2. Predicting a number with a line is ___.
  3. Missing data can cause ___.

Answers

  1. Finding groups without labels is ___. clustering
  2. Predicting a number with a line is ___. regression
  3. Missing data can cause ___. bias

Safety: Teacher-led. Use only the teacher's device. Camera is off until the teacher turns it on. Do not show children's faces; use objects. No student personal data. No class codes, dashboards or galleries are used.

Class certificate

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← AI Lab AI practicals

Aligned with NEP 2020 and mapped to CBSE’s Computational Thinking & AI curriculum (Classes 3–8). Big Ideas follow the AI4K12 framework. NextBridge is independent and not affiliated with CBSE or AI4K12.

NextBridge AI Lab · Grade 7 · Sort, Guess and Group — Worksheet

Name: ______________ Class: ____ Date: ______

  1. Make a table of 5 fruits with weight and price.
  2. Plot them and draw a best-fit line by hand.
  3. Write one example of bias in data.

Exit quiz:

  1. Finding groups without labels is ___.
  2. Predicting a number with a line is ___.
  3. Missing data can cause ___.

Teacher answer key · Sort, Guess and Group

  1. Any 5 rows.
  2. Line passes through the middle of the points.
  3. e.g. a dataset with no green fruits.

Exit quiz:

  1. Finding groups without labels is ___. clustering
  2. Predicting a number with a line is ___. regression
  3. Missing data can cause ___. bias

Maps to: CBSE Computational Thinking & AI, Class 7 (classification, regression, clustering, charts, bias)

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