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Common Algorithms

Ninth graders learn the everyday algorithms behind software, from linear and binary search to sorting and finding a maximum, and match each algorithm to what it does.

Grade 9Common Algorithms50 minutes1 class periodUse → Modify → CreateExplicit teaching4 StandardsCSTA
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Lesson at a Glance

Everything you need before the bell rings

Learning Objectives

Students will be able to…

  • ✓Name common algorithms.
  • ✓Link each to its job.
  • ✓Tell search from sort.
  • ✓Match each pair.
Essential Question

The same problems come up again and again in code. What are the common algorithms that solve them, and how do you pick the right one?

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Lesson Phases
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Vocabulary Terms
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Standards Aligned
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Interactive Task
Match It · Interactive

Match the Algorithm

Project this and match each algorithm to what it does — tap an algorithm, then tap its job.

🧮 Match each algorithm to what it doesTry it
Algorithm
What it does
Tap an algorithm, then tap what it does.
The Lesson · Use → Modify → Create (a coding progression with Unplugged practice)

50 minutes, five moves

Tap any phase to open the teacher moves and student actions.

1

Hook — Same Problems, Solved

5 min

Searching a list and sorting it come up again and again. Rather than reinvent them, coders reuse proven algorithms. Which ones?

👩‍🏫 Teacher Moves

  • Ask how to find a name in a list.
  • List approaches.
  • Set the goal.

🎒 Student Actions

  • Think.
  • Share.
  • Get ready.
2

Use — Match the Algorithm

12 min

Students match each algorithm to its job.

👩‍🏫 Teacher Moves

  • Send students to Match the Algorithm.
  • Match each pair.
  • Note the job.

🎒 Student Actions

  • Match.
  • Say.
  • Note it.
3

Modify — Trace It

13 min

Students trace an algorithm by hand.

👩‍🏫 Teacher Moves

  • Pick an algorithm.
  • Run it on a small list.
  • Record each step.

🎒 Student Actions

  • Pick.
  • Run.
  • Record.
4

Create — Pick the Right One

15 min

Students choose algorithms for tasks.

👩‍🏫 Teacher Moves

  • List three tasks.
  • Choose an algorithm for each.
  • Say why it fits.

🎒 Student Actions

  • List.
  • Choose.
  • Say.
5

Reflect — Reuse What Works

5 min

Students reflect on choosing algorithms.

👩‍🏫 Teacher Moves

  • How is binary search different from linear search?
  • Why reuse known algorithms?
  • Complete the exit ticket.

🎒 Student Actions

  • Say it.
  • Say it.
  • Complete the exit ticket.
Standards Alignment

Built to the standards you report on

Aligned to the CSTA K-12 Computer Science Standards and ISTE Standards for Students.

CSTA
3A-AP-14

Use common algorithms to solve problems.

CSTA
3A-AP-15

Compare algorithms for the same task.

CSTA
3A-AP-13

Trace and explain how an algorithm works.

ISTE
5c

Select and apply algorithms to computing problems.

Differentiation

One lesson, every learner

Multilingual Learners

ELL / EMERGING READERS
  • Algorithm + job cards.
  • Sentence frame: “___ is used to ___ .”
  • Match one pair at a time.

Support & Access

IEP / 504
  • Start with linear search.
  • Trace each on a tiny list.
  • Match one algorithm fully before the next.

Stretch & Extend

GIFTED / EARLY FINISHERS
  • Compare search/sort efficiency.
  • Trace binary search step by step.
  • Code one algorithm from scratch.
Materials

What to gather

  • 📽️Projector / board
  • 🖼️Algorithm + job cards
  • 💻Match the Algorithm
  • 🧮Sample lists to trace
  • ✏️Pencils
  • 🎫Exit-ticket slips
Vocabulary

Key terms — hover for a quick definition

algorithma step-by-step set of instructions to solve a problemlinear searchchecking each item in order to find a targetbinary searchhalving a sorted list each step to find a targetsortingarranging items into ordermaximumthe largest value in a setefficiencyhow much work an algorithm takesinputthe data an algorithm works ontraceto follow an algorithm step by step
Evaluate

Exit Ticket

Preview the three formative checks. Tap “Sample answer” to see what mastery looks like — hide them before you print for students.

QUESTION 1
How is binary search different from linear search?
Linear search checks each item in order; binary search halves a sorted list each step, so it finds the target much faster.
QUESTION 2
Name one common algorithm and what it does.
For example, sorting arranges items into order, or find-maximum scans a list for the largest value.
QUESTION 3
Why do programmers reuse known algorithms?
They are proven, efficient, and save time, so there is no need to reinvent a solution to a common problem.

Create: pick the right one.

Have students list three tasks, choose a fitting algorithm for each, and explain why it fits, so choosing an algorithm becomes a deliberate step. A printable algorithms worksheet is in the Computer Science library.

Study · Flashcards

Study the key terms

Tap a card to flip it, then rate whether you knew it. Built from this lesson’s vocabulary.

🃏 Common AlgorithmsFlip
Card 1
Term
Tap to flip →
Meaning
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Nice work!

Practice · Quiz

Check your understanding

A quick self-check with instant feedback, drawn from this lesson’s key terms.

📝 Common AlgorithmsQuiz
Score: 0
1 / 6
Question 1
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Nice work!

Practice · Worksheet

Printable worksheet

A print-and-go review sheet with a built-in answer key. Tap “Show answer key” to reveal answers, or print the clean version for students.

🖨️ Common AlgorithmsPrint
Name: ________________________
Date: ____________

Part A · Write the word that matches each meaning

Word bank: algorithm, binary search, efficiency, input, linear search, maximum, sorting, trace
  1. arranging items into order
  2. the largest value in a set
  3. the data an algorithm works on
  4. to follow an algorithm step by step
  5. halving a sorted list each step to find a target
  6. how much work an algorithm takes
  7. a step-by-step set of instructions to solve a problem
  8. checking each item in order to find a target

Part B · Show what you learned

  1. How is binary search different from linear search?
  2. Name one common algorithm and what it does.
  3. Why do programmers reuse known algorithms?
Answer key — Part A: 1) sorting · 2) maximum · 3) input · 4) trace · 5) binary search · 6) efficiency · 7) algorithm · 8) linear search
Part B: 1) Linear search checks each item in order; binary search halves a sorted list each step, so it finds the target much faster. 2) For example, sorting arranges items into order, or find-maximum scans a list for the largest value. 3) They are proven, efficient, and save time, so there is no need to reinvent a solution to a common problem.