Assess students' understanding of Big O notation as an upper bound and their ability to compare and identify time complexities specifically among O(1), O(n), O(n log n), and O(n^2). The quiz will require concise definitions, ranking growth rates, analyzing short code snippets or pseudocode to determine complexity, explaining why constants and lower-order terms are ignored, and predicting how runtime changes as input size n increases. Appropriate for Grade 9–12 learners to demonstrate conceptual mastery and basic algorithm analysis.