Class 10 · Unit 0: Refresher · Lesson 0.1 · 40 min

Back at the laptop

Last year you got top marks for a model nobody ever tested. Was it any good?

Today you will: Set up your Class 10 folder · Predict a program before you run it · Ask of last year's project: does it work?

Story

Hiba has last year's project printed and folded into her Physics book. The title is underlined twice: An early warning for the Nowgam road.

Bilal: “It was a good proposal. We got the best mark in the class.”

Hiba: “It was a good proposal. Page four. 'Our model would predict which mornings the road floods.' Would. We never built it. We never tested it. We don't know if it's right once in ten.” (She opens it on the desk.)

Bilal: “We said it was rule-based. We wrote the rules.”

Hiba: “We wrote rules. We never checked them against a single real morning. Last year we learned to ask what is the problem? This year the question is harder.” (She taps the page.)

Bilal reads the underlined title again. "Which is?"

Bilal: “Does it work — and how would we know?”

Watch

Back at the laptop — — scan code 10.0.1 in the printed book.

Warm up your fingers

Skill: code symbols, at speed — ( ) [ ] { } : " ' = _ # (5 min)

On typing.com: the symbols lessons your teacher sets.
Two new ones this year: { } for a Python dictionary, and # for a comment.
Type three times, eyes on the screen:

counts = {"good": 3, "bad": 1} # a dictionary
Goal by May: 38–44 WPM at 95%. Beat your own score, not anyone else's.

On the laptop

You need: File Manager · Thonny · LibreOffice Calc · typing.com

Mission 1: Your folder (2 min)

☐1
In the Class-10 folder, open my-work and make a folder named with your roll number only, e.g. 10-roll-12.

Mission 2: Predict, then run (8 min)

☐2

In Thonny, open programs/refresher.py. Don't run it yet.

temps = [4, 7, 2, 9, 3]
total = 0
for t in temps:
   total = total + t
print(total / len(temps))

☐3
Predict: write the exact output on paper.
☐4
Run it. Same as your prediction? If not, find the line where you and Python disagreed.
☐5
Add -2 to the list. Predict again, run again. Save a copy in your own folder.

Mission 3: Does last year's project work? (6 min)

☐6
Open your Class 9 project. In Calc, make one row under these headings, and fill it honestly: Our model · What it predicts · Did we ever test it? · On how many real cases? · Who could it be wrong about?
☐7
Save it as does-it-work.ods. Keep it — it comes back in Unit 3.

Mission 4: Typing baseline (5 min)

☐8
Log in to typing.com with your new card. Take the one-minute test and write your WPM, accuracy and Term 1 goal on the card.

No laptop today?

Copy the program onto paper. Everyone predicts; then one student traces it on the board, keeping total in a box and crossing out each old value. Fill the does-it-work row on paper.

Now you know

Predict, run, compare, then fix your picture of the program and go again.

This year's question: does it work? A model nobody has measured is a hope, not a result. Unit 3 teaches you to measure one.
Ethics first, not last. Should we build this, and for whom? is asked before any data is collected.
Predict, then run. Every program in this book, every time. A wrong prediction isn't a mark against you — it shows exactly which part of your picture needs fixing.
Last year's words still count: the six stages of the cycle, True and False Positives and Negatives, bias and access.
Python is a tool this year, not a topic — used only where it beats a spreadsheet.

Debate it

Hiba's group got top marks for a model nobody ever tested.

Was that mark fair? What was it really a mark for?
If the town had used their flood warning, untested, for one winter — who would have found out whether it worked, and how?

Check yourself — practice, not a test

1. What will this print? python nums = [2, 4, 6] print(len(nums))
- ○ 2
- ○ 3
- ○ 6
- ○ 12
2. nums already holds [4, 5, 6]. Put these lines in order so the program prints 15 (in the real program, the line inside the loop is indented):
- 1. for n in nums:
- 2. total = 0
- 3. total = total + n
- 4. print(total)
3. A model that has never been tested on real cases can still be called finished, as long as its rules were written carefully.
- ○ True
- ○ False
4. The stage of the AI project cycle that checks how well a model works is called ______.
5. Which folder name follows our privacy rule?
- ○ bilal-10A-nowgam
- ○ 10-roll-04
- ○ bilal-lone
- ○ bilal10

Remember

A model nobody has measured is not finished. It is a hope.

Story

Hiba has last year's project printed and folded into her Physics book. The title is underlined twice: An early warning for the Nowgam road.

Bilal: “It was a good proposal. We got the best mark in the class.”

Bilal: “We said it was rule-based. We wrote the rules.”

Hiba: “We wrote rules. We never checked them against a single real morning. Last year we learned to ask what is the problem? This year the question is harder.” (She taps the page.)

Bilal reads the underlined title again. "Which is?"

Bilal: “Does it work — and how would we know?”

Warm up your fingers

Skill: code symbols, at speed — ( ) [ ] { } : " ' = _ # (5 min)

On typing.com: the symbols lessons your teacher sets.
Two new ones this year: { } for a Python dictionary, and # for a comment.
Type three times, eyes on the screen:

counts = {"good": 3, "bad": 1} # a dictionary
Goal by May: 38–44 WPM at 95%. Beat your own score, not anyone else's.

On the laptop

You need: File Manager · Thonny · LibreOffice Calc · typing.com

Mission 1: Your folder (2 min)

☐1
In the Class-10 folder, open my-work and make a folder named with your roll number only, e.g. 10-roll-12.

Mission 2: Predict, then run (8 min)

☐2

In Thonny, open programs/refresher.py. Don't run it yet.

temps = [4, 7, 2, 9, 3]
total = 0
for t in temps:
   total = total + t
print(total / len(temps))

☐3
Predict: write the exact output on paper.
☐4
Run it. Same as your prediction? If not, find the line where you and Python disagreed.
☐5
Add -2 to the list. Predict again, run again. Save a copy in your own folder.

Mission 3: Does last year's project work? (6 min)

☐6
Open your Class 9 project. In Calc, make one row under these headings, and fill it honestly: Our model · What it predicts · Did we ever test it? · On how many real cases? · Who could it be wrong about?
☐7
Save it as does-it-work.ods. Keep it — it comes back in Unit 3.

Mission 4: Typing baseline (5 min)

☐8
Log in to typing.com with your new card. Take the one-minute test and write your WPM, accuracy and Term 1 goal on the card.

No laptop today?

Copy the program onto paper. Everyone predicts; then one student traces it on the board, keeping total in a box and crossing out each old value. Fill the does-it-work row on paper.

Now you know

This year's question: does it work? A model nobody has measured is a hope, not a result. Unit 3 teaches you to measure one.

Ethics first, not last. Should we build this, and for whom? is asked before any data is collected.

Predict, then run. Every program in this book, every time. A wrong prediction isn't a mark against you — it shows exactly which part of your picture needs fixing.

Last year's words still count: the six stages of the cycle, True and False Positives and Negatives, bias and access.

Python is a tool this year, not a topic — used only where it beats a spreadsheet.

Check yourself — practice, not a test

1. What will this print? python nums = [2, 4, 6] print(len(nums))

○ 2
○ 3
○ 6
○ 12

2. nums already holds [4, 5, 6]. Put these lines in order so the program prints 15 (in the real program, the line inside the loop is indented):

1. for n in nums:
2. total = 0
3. total = total + n
4. print(total)

3. A model that has never been tested on real cases can still be called finished, as long as its rules were written carefully.

○ True
○ False

4. The stage of the AI project cycle that checks how well a model works is called ______.

5. Which folder name follows our privacy rule?

○ bilal-10A-nowgam
○ 10-roll-04
○ bilal-lone
○ bilal10