AP Prep Checkpoint

• 6 min read

How I’ve Been Studying

  • To prepare effectively, I’ve developed a consistent study routine that focuses on both practice and review. One of my main strategies has been actively engaging with the multiple-choice questions (MCQs) provided by College Board. These questions help me get familiar with the style and rigor of the questions that may appear on assessments, and they also highlight areas where I need to improve.

  • After each lesson, I make it a point to go back and thoroughly review the content we’ve covered in class. I also complete the lesson “hacks” that we’ve been assigned throughout the trimester. These hacks have been especially useful for reinforcing the key concepts and making sure I understand the different ways the material can be applied. They often provide a deeper look into the topic and help me retain the information more effectively.

  • Once I feel comfortable with a topic, I return to the College Board MCQs I’ve already done and focus specifically on the ones related to that lesson. This targeted practice allows me to test my understanding in a more focused way and see how well I can apply what I’ve learned. It’s also helpful for identifying patterns in the types of questions I tend to miss, so I can revisit those concepts and strengthen my skills further.

  • Overall, this approach—combining review, structured practice, and reflection—has significantly improved my understanding of the material. It’s helped me become more confident in tackling different types of questions, and it’s reflected in the strong scores I’ve been getting on my multiple-choice assessments.

Big Idea 5 Summaries

Beneficial and Harmful Effects

  • Learned how computing innovations can have both positive and negative impacts.
  • Explored examples like social media and its influence on mental health and communication.
  • Reflected on the responsibility of developers in innovation.

Digital Divide

  • Understood disparities in access to technology and the internet.
  • Discussed real-world implications like education and economic inequality.

Computing Bias

  • Learned how bias can enter algorithms through data and design choices.
  • Discussed examples like facial recognition and hiring algorithms.
  • Explored ways to reduce bias through testing and diverse data sets.

Crowdsourcing

  • Understood how data and solutions can be collected from a large group of people online.
  • Explored platforms like Wikipedia and open-source projects.
  • Recognized the power and potential drawbacks of public collaboration.
  • Studied laws related to computing like copyright and privacy regulations.
  • Reflected on ethical concerns in data use, AI, and user consent.
  • Practiced identifying ethical dilemmas in tech scenarios.

Safe Computing

  • Learned best practices for personal digital security (e.g., strong passwords, two-factor authentication).
  • Discussed risks like phishing, malware, and social engineering.
  • Emphasized responsible online behavior and digital citizenship.

Big Idea 3 Summaries

Binary Search Algorithms

  • Learned how binary search efficiently finds elements in sorted lists. Cuts list in half repeatedly until it finds the target.
  • Compared binary search to linear search in terms of performance (O(log n) vs O(n)).
  • Practiced implementing binary search using conditionals and loops.

Lists and Filtering Algorithms

  • Practiced using lists and filtering to process and extract data.
  • Understood how to apply selection and iteration concepts.
  • Used algorithms to solve problems involving search and data handling.

Big-O

  • Learned how to analyze algorithm efficiency using Big-O notation. O(1), O(log n), O(n), O(n^2), O(n log n), O(n!).
  • Compared different algorithms in terms of performance and scalability.
  • Recognized the importance of writing optimized code.

Random Algorithms

  • Explored how randomness is used in computing (e.g., simulations, games).
  • Discussed unpredictability and fairness in randomized solutions.

Simulations

  • Understood how computer models simulate real-world systems.
  • Applied simulations to problems like climate models or traffic patterns.
  • Learned how assumptions and limitations affect accuracy.

Undecidable Problems

  • Discovered that some problems cannot be solved by any algorithm.
  • Studied examples like the Halting Problem.
  • Understood the boundaries of what computing can and cannot do.

Graphs and Heuristics

  • Graphs model relationships using nodes (vertices) and edges (connections); used in pathfinding (Google Maps), web ranking (PageRank), and network routing.

  • Complete Graph: Every pair of nodes is directly connected.

  • Adjacency Matrix (2D array of 0s/1s) vs. Adjacency List (each node stores a list of neighbors).

  • Heuristics are smart shortcuts for solving complex problems when exact solutions are too expensive.

  • Examples of heuristics: Nearest Neighbor (TSP), Greedy Algorithms (Coin Change), and Heuristic Search (using distances like Manhattan or Euclidean).

MCQs Scores Reflection

  • I mastered a majority of the skills during the MCQs.

Topics I need to improve on:

  • Computing Bias (0/1)
    • I can look through the team teach provided by my peers and analyzing how algorithms can reflect human bias, and learning about ways to design more fair and ethical computing systems.
  • The Internet (1/4)
    • I can improve my understanding of how the internet works by studying how data travels through networks, learning about protocols like TCP/IP and DNS, and exploring how devices communicate using IP addresses and routers.

Skills I can Imporve on

  • However one skill I missed out on multiple MCQs was skill 5.A: Explain how computing systems work.
    • I can improve on this skill understanding
      • The flow of information in a computing system:
      • Input → Processing → Storage → Output
      • How data is represented and manipulated:
      • Binary representation, bits and bytes, how data moves between components
      • Interactions between components:
      • The CPU fetches instructions from memory, executes them, and interacts with input/output systems

Skills that weren’t present in the test:

  • Skill 4.A: Explain how a code segment or program functions.
  • Skill 6.A: Collaborate in the development of solutions.
  • Skill 6.B: Use safe and secure methods when using computing devices.
  • Skill 6.C: Acknowledge the intellectual property of others.
    • I can improve these skills by practicing other MCs by collegeboard.

How I Plan to Continue Studying for the AP Exam

  • Continue practicing more multiple-choice questions to build speed and accuracy.
  • Review specific topics missed in the MCQs
  • Start answering Free Response Questions (FRQs), and practice with FRQ wording, escepicially with my topics.
  • Review key vocabulary/ CPT Wording
  • Work with peers to review MCQs to learn what I was making mistakes on.
  • Form study groups with other student in the same place or above me to study with one another and imrpove together.

Daily Study Plan:

Date Topic Time Done
Apr 22 Beneficial / Harmful Effects 6:00 [ ]
Apr 23 Digital Divide 6:00 [ ]
Apr 24 Computing Bias 6:00 [ ]
Apr 25 Crowdsourcing 6:00 [ ]
Apr 26 Practice MC 6:00 [ ]
Apr 27 Safe Computing 6:00 [ ]
Apr 28 Binary Search Algorithm 6:00 [ ]
Apr 29 Lists and Filtering 6:00 [ ]
Apr 30 Simulations / Random 6:00 [ ]
May 1 Big O / Efficiency 6:00 [ ]
May 2 Undecidable Problems + Graphs 6:00 [ ]
May 3 Practice MC 6:00 [ ]
May 4 Images / Base64 / Color Codes 6:00 [ ]
May 5-9 FRQ Wording and practice prep 6:00 [ ]
May 10 Final Review 6:00 [ ]