Algorithms are a prominent theme in computer science. However, there is little research to improve students’ ability to select which algorithm to use, given an algorithm problem. We aim to analyze student behavior while selecting standard algorithm for a given problem. We did an hour-long think-aloud interview with students at Utah State University to observe their behavior attempting to pick an algorithm. We found 12 common student behaviors where students who can identify the given problem with similar problems seen before, and those who correctly identify the subproblem, have a better chance of solving a given problem. The findings from this study helped us to form a definitive strategy to select an algorithm, which could be beneficial in solving algorithmic problems. We also developed 28 multiple-choice questions that could be used to evaluate students’ ability to pick the correct algorithm design technique. During the question generation process for algorithm problems, we found different strategy that needs to be followed, like asking students to select all possible algorithms for a given problem and not using keywords like path and graph for Graph Modeling problems. The multiple-choice questions help us to scale the assessment for a randomized controlled trial where we will test the effectiveness of educational interventions designed to help students know how to select an algorithm design technique.