Untitled Flashcard Set

Big Idea 1: Creative Development

  • Collaboration benefits 

  • Simulation use

Big Idea 2: Data

  • Binary, ASCII, RGB 

  • Data compression 

  • Data storage + metadata 

  • Overflow errors 

Big Idea 3: Algorithms & Programming

  • Procedures, parameters, returns 

  • Iteration & lists 

  • Searching 

  • Algorithm efficiency + growth 

  • Robot / procedural logic 

Big Idea 4: Computer Systems & Networks

  • Parallel computing 

  • Fault tolerance 

  • Network concepts

Big Idea 5: Impact of Computing

  • Cybersecurity 

  • Digital divide 

  • Privacy concerns 



3-Day Review Plan 

✅ DAY 1: Cybersecurity, Networks, & Impact (Big Ideas 4 + 5)

📍 Barron’s Pages: 309–322
📍 Barron’s Pages: 327–344

🔑 Topics to Cover

  • Phishing vs malware vs keylogging

  • Multifactor authentication

  • Data privacy risks (databases, storage)

  • Parallel computing basics

  • Fault tolerance (redundancy)

  • Digital divide + ethics

📘 Key Vocabulary

  • Phishing

  • Malware / Keylogger

  • Multifactor Authentication (MFA)

  • Encryption

  • Fault tolerance

  • Redundancy

  • Parallel processing

  • Digital divide

  • Privacy vs security

🧠 Big Ideas to Emphasize

  • Humans are the weakest link in security

  • More data = more risk

  • Redundancy = reliability

  • Access to tech ≠ equal across populations

⚠ Common Mistakes 

  • Confusing phishing with hacking

  • Thinking MFA = password rules 

  • Not recognizing database storage = privacy risk 

  • Misunderstanding parallel vs sequential time savings

✅ DAY 2: Data + Binary + Compression (Big Idea 2)

📍 Barron’s Pages: 143-178

🔑 Topics to Cover

  • Binary representation (numbers + ASCII)

  • RGB color values

  • Overflow errors

  • Lossy vs lossless compression

  • Metadata + data analysis limits

📘 Key Vocabulary

  • Bit / Byte

  • Binary

  • ASCII

  • RGB

  • Metadata

  • Lossy compression

  • Lossless compression

  • Overflow error

  • Sampling / approximation

🧠 Big Ideas

  • All data = binary underneath

  • Tradeoff: size vs quality

  • Data can answer some questions—but not all

  • Storage limits cause real errors (overflow)

⚠ Common Mistakes

  • Mixing up lossy vs lossless

  • Thinking more bits = worse quality

  • Not recognizing overflow as cause of weird values 

  • Assuming data tells everything 





✅ DAY 3: Algorithms & Programming (Big Idea 3 + 1)

📍 Barron’s Pages: 193-292
📍 Barron’s Pages: 127-140

🔑 Topics to Cover

  • Procedures + parameters

  • Abstraction (black box thinking)

  • Loops + iteration

  • Lists and accumulation

  • Searching (linear vs binary)

  • Algorithm efficiency (growth rates)

  • Simulation & modeling

📘 Key Vocabulary

  • Algorithm

  • Procedure

  • Parameter

  • Abstraction

  • Iteration

  • List

  • Accumulator

  • Binary search

  • Linear search

  • Heuristic

  • Simulation

🧠 Big Ideas

  • Abstraction = use without knowing internals

  • Binary search requires sorted data

  • Efficiency matters as data grows 

  • Programs often follow patterns