Mastering Undergraduate Algorithms: Improving Problem-Solving Skills and Fluency through Scaffolding Learning Modules

Author(s) Information

Anissa Soungpanya, California Polytechnic State University, San Luis ObispoFollow

College - Author 1

College of Engineering

Department - Author 1

Computer Science Department

Advisor

Ka Yaw Teo, College of Engineering, Computer Science and Software Engineering Department

Date

10-2025

Abstract/Summary

The primary objective of the undergraduate algorithms course is to equip students with the ability to design and analyze algorithms, prove theorems about computation, and effectively communicate these algorithms and proofs to a human audience. In addition, the course aims to help students foster their fluency in the process of formulating and solving computational problems. Scaffolding exercises and activities that focus on these aspects could serve as useful learning tools in providing targeted feedback and helping students develop their confidence and fluency. To address the challenges that students encounter when solving algorithmic problems -- particularly in regard to problem decomposition and solution structuring -- this proposed project seeks to develop and implement scaffolding exercises that offer structured and adaptive guidance as students progress in their proficiency. The goal is to assist students in breaking down complex problems into manageable components, developing systematic solution approaches, and improving their problem-solving confidence. The research will involve designing and integrating various scaffolding interventions into course assignments, such as structured hints, step-by-step breakdowns, and guided exercises. We will assess the effectiveness of these scaffolding techniques by analyzing student performance metrics, gathering survey responses, and collecting qualitative feedback. A comparative analysis of students’ problem-solving strategies before and after scaffolding implementation will be conducted to measure improvements in understanding and solution quality. By refining and optimizing scaffolding approaches based on the collected data, this project aims to contribute valuable insights to the field of theoretical computer science education. The anticipated outcomes include increased student engagement, enhanced problem-solving skills and fluency, and the development of best practices for incorporating scaffolding exercises into undergraduate algorithms instruction.

October 1, 2025.