High School Curriculum Explorer · Grades 9–12

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138 original mini-lessons with video choices23 courses9 subject areas

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Each course has six lessons in three suggested units. Grade ranges guide placement; they are not universal requirements.

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35 minutes

Computer Science and Digital Literacy

Suggested grades 9–12 · Unit 1: Algorithms and decision logic

Trace an Algorithm with an Exception

Follow a written loop precisely and test ordinary, empty and invalid inputs.

▷ 2 teacher video choices: Trace an Algorithm with an Exception
Preview lesson: Trace an Algorithm with an Exception

Goal: Produce a correct trace table and locate a reset bug in a list-processing procedure.

Before this: Basic arithmetic Reading a table

Try together: Trace[−1,2,2,−3,7] and explain each unchanged state.

Supporting literacy connectionRST.9-10.3Grades 9–10
Subject-content alignment not yet verified
Open lesson →: Trace an Algorithm with an Exception
35 minutes

Computer Science and Digital Literacy

Suggested grades 9–12 · Unit 1: Algorithms and decision logic

Translate a Rule into Boolean Logic

Make grouping explicit and test boundary combinations in a fictional access rule.

▷ 2 teacher video choices: Translate a Rule into Boolean Logic
Preview lesson: Translate a Rule into Boolean Logic

Goal: Build a truth table and show how two different groupings change a rule’s result.

Before this: True and false values Reading conditions

Try together: Complete outputs for O=true with(C,P)=(false,false),(false,true),(true,false),(true,true).

Supporting literacy connectionRST.9-10.7Grades 9–10
Subject-content alignment not yet verified
Open lesson →: Translate a Rule into Boolean Logic
35 minutes

Computer Science and Digital Literacy

Suggested grades 9–12 · Unit 2: Data quality and representation

Data Cleaning with a Decision Log

Preserve missingness and document transformations in a fictional data table.

▷ 2 teacher video choices: Data Cleaning with a Decision Log
Preview lesson: Data Cleaning with a Decision Log

Goal: Apply stated cleaning rules and write a reproducible technical report distinguishing missing from zero.

Before this: Tables Mean calculation

Try together: Apply the same rules to 7,“8 min”,blank,−2 and 0. Write the cleaned values and status labels.

Supporting literacy connectionWHST.9-10.2Grades 9–10
Subject-content alignment not yet verified
Open lesson →: Data Cleaning with a Decision Log
35 minutes

Computer Science and Digital Literacy

Suggested grades 9–12 · Unit 2: Data quality and representation

Binary Values and Run-Length Encoding

Follow two explicit representations and check whether compression actually saves space.

▷ 2 teacher video choices: Binary Values and Run-Length Encoding
Preview lesson: Binary Values and Run-Length Encoding

Goal: Encode and decode a short binary sequence and justify its storage comparison under a stated format.

Before this: Place value Counting repeated symbols

Try together: Encode 111100 and decode 0:2;1:1;0:3. Convert binary 1100 to decimal.

Supporting literacy connectionRST.9-10.3Grades 9–10
Subject-content alignment not yet verified
Open lesson →: Binary Values and Run-Length Encoding
35 minutes

Computer Science and Digital Literacy

Suggested grades 9–12 · Unit 3: Digital evidence and privacy decisions

Evaluate a Classifier’s Accuracy Claim

Read a fictional technical report and distinguish a narrow test result from a universal guarantee.

▷ 2 teacher video choices: Evaluate a Classifier’s Accuracy Claim
Preview lesson: Evaluate a Classifier’s Accuracy Claim

Goal: Assess claim support and write a justified revision using test-method details.

Before this: Percentages Claims and evidence

Try together: Assess a second fictional claim:“It works equally well on every layout,”supported only by 20 tests using one layout. Name the gap.

Supporting literacy connectionRST.9-10.8Grades 9–10
Subject-content alignment not yet verified
Open lesson →: Evaluate a Classifier’s Accuracy Claim
40 minutes

Computer Science and Digital Literacy

Suggested grades 9–12 · Unit 3: Digital evidence and privacy decisions

Privacy by Minimizing a Fictional Data Form

Compare stakeholder needs and reduce unnecessary collection before designing a form.

▷ 2 teacher video choices: Privacy by Minimizing a Fictional Data Form
Preview lesson: Privacy by Minimizing a Fictional Data Form

Goal: Produce a minimal-data design and synthesize a discussion’s conflicting claims and unresolved questions.

Before this: Data fields Purpose and evidence Discussion norms

Try together: Discuss whether a public attendance list is necessary to send private schedule updates. Record one viewpoint and an evidence-based response.

Supporting literacy connectionSL.11-12.1.dGrades 11–12
Subject-content alignment not yet verified
Open lesson →: Privacy by Minimizing a Fictional Data Form

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