Author: Anika2317 Exam: AP CSP 2018 Practice MCQ Total time: 2:10:14

Overall Score

College Board score report

Score Percent Correct Missed
55 / 66 83% 55 11 
pie showData
    title Overall Score: 55/66
    "Correct" : 55
    "Incorrect" : 11

The Story

  • Going in: Prepared from recent Python work and logic practice.
  • Went smoothly: Logic gates, flowcharts, compression, and ethics/impact questions.
  • Found hard: Questions that needed step-by-step calculating or tracing.
  • Pattern: Some misses were miscalculations, and others I got stuck on for over 3 minutes.
  • Takeaway: My concepts are somewhat stronger. My weak spot is tracing.

Glows and Grows

Glows Grows
Impact of Computing (100%): ethics, digital divide, safe computing Binary limits: bit requirements and overflow
Data compression and Boolean logic (100%) Tracing loops, coordinates, and edge cases
Evaluating solutions and iterative design Search algorithms and unequal probabilities

Category Statistics

The 5 Big Ideas

Big Idea Exam Weight Questions Performance
Big Idea 1: Creative Development 10–13% 5 80%
Big Idea 2: Data 17–22% 16 81%
Big Idea 3: Algorithms and Programming 30–35% 34 79%
Big Idea 4: Computing Systems and Networks 11–15% 4 75%
Big Idea 5: Impact of Computing 21–26% 11 100% 
xychart-beta
    title "Performance by Big Idea (%)"
    x-axis ["1: Creative Dev", "2: Data", "3: Algorithms", "4: Systems", "5: Impact"]
    y-axis "Percent correct" 0 --> 100
    bar [80, 81, 79, 75, 100]

Big Idea 3: Algorithms and Programming is over half the exam (34 of 66), so improving there matters most.

Computational Thinking Practices

Practice Questions Performance
P5: Investigate computing innovations 19 89%
P1: Design and evaluate solutions 17 88%
P2: Develop and implement algorithms 11 82%
P3: Develop programs with abstractions 9 78%
P4: Evaluate and test algorithms 10 70%

My lowest practice (P4) and lowest skill (4.B, determine the result of code segments, 67%) both point to tracing as my main gap.

Topics to Review

Topic Performance
3.1 Variables and Assignments 67%
4.1 The Internet 67%
3.17 Algorithmic Efficiency 50%
3.15 Random Values 50%
2.1 Binary Numbers 50%
3.10 Lists 0% (1 question)

Timing

Missed questions averaged 2:11, compared to 1:33 on correct ones.

flowchart LR
    A[11 Missed] --> B[Quick: 5 answered < 1:30]
    A --> C[Stuck: 4 > 3:00]
    B --> D[Fix: check answer choices]
    C --> E[Fix: retry concepts]

In-Depth Concept Analysis

Metadata vs. Data

  • KNOW: I can identify descriptive details like genre and author.
  • Don’t KNOW: Metadata is “data about data”: tags used to sort and search (title, author, date, genre). The content itself, like the file or its old versions, is data, not metadata.

Binary Numbers

  • KNOW: Characters are stored as binary.
  • Don’t KNOW: n bits give 2^n values. Pick the smallest power of 2 that covers what’s needed.
Bits Values Max integer
4 16 15
7 128 127
8 256 255

200 characters need 8 bits. With 4 bits, anything over 15 is an overflow error.

Open Standards and Protocols

  • KNOW: Open content licensing (Creative Commons).
  • Don’t KNOW: Open protocols (TCP/IP, HTTP) are public communication rules that let different manufacturers’ devices work on the same network. They are not about sharing content.

Swapping Values

  • KNOW: A temp variable prevents losing a value.
  • Don’t KNOW: The swap needs all three steps:
temp   ← first
first  ← second
second ← temp

Coordinate Math in Loops

  • KNOW: Basic grid movement and loop counts.
  • Don’t KNOW: Moving down and to the right means x increases and y decreases each loop.

Unequal Probabilities

  • KNOW: RANDOM(a, b) simulates chance.
  • Don’t KNOW: A 1:1:4 ratio is 6 parts, so use RANDOM(1, 6) and give the largest range (4 of 6) to the largest section.

Boolean Comparisons

  • KNOW: How to calculate 0.5 * total.
  • Don’t KNOW: A majority means counter > 0.5 * total (the part is strictly greater than half).

Algorithmic Efficiency

  • KNOW: Loops process each list item.
  • Don’t KNOW: Total time = calls before the loop + calls inside the loop × items. One setup call plus 4 loop calls = 5.
  Linear Binary
How it works Checks every item in order Cuts the list in half each step
Needs sorted list? No Yes

Edge Cases and Infinite Loops

  • KNOW: Repeating until a target is reached.
  • Don’t KNOW: If count starts at 0 and only goes up, REPEAT UNTIL (count = y) never ends when y is negative.

Two Right / Two Wrong

Got Right Got Wrong
Boolean logic and data compression Binary limits and overflow
Computing impacts and ethics Step-by-step code tracing

Next Steps

flowchart TD
    A[Week 1: Binary] --> B[Week 2: Tracing]
    B --> C[Week 3: Random Values and Search]
    C --> D[Every test: check edge cases and key words]
  • Memorize 2^1 through 2^8 and practice overflow problems.
  • Trace every code-result question on paper with a variable table.
  • Code a 1:1:4 spinner simulation in Python.
  • Code linear and binary search and compare their steps.
  • Re-check answers made in under 30 seconds. Skip and return after 3 minutes.

Overall in Class

What I’m Enjoying What I Want to Improve
Independence to work on passion projects Technical code
Collaborating with the group we created Binary and data representation
Building the Poway Recovery Center website Lists and search algorithms
Learning new skills through the lessons Pacing on longer problems

Overall, this class has been a really positive experience so far. I’ve especially enjoyed the independence to work on projects I care about, the collaboration within our group, and building the Poway Recovery Center website for a real organization. I’m learning new skills through the lessons and projects, and this reflection showed me exactly what to focus on next.

Goal: Get Algorithms and Programming and Practice 4 above 85% by doing more practice tests and practicing technical concepts.