CSCI 240 - Data Structures and Algorithms

The following are the Student Learning Outcomes (SLOs) and Course Measurable Objectives (CMOs) for CSCI 240. A Student Learning Outcome is a measurable outcome statement about what a student will think, know, or be able to do as a result of an educational experience. Course Measurable Objectives focus more on course content, and can be considered to be smaller pieces that build up to the SLOs.

Student Learning Outcomes (SLOs)

1. Students will be able to analyze problems and select the appropriate data structure.
2. Students will be able to estimate running time given an algorithm.
3. Students will be able to implement and use linear data structures including sets, stacks, queues, and lists.
4. Students will be able to implement and use trees including binary tree, binary search trees, and heaps.
5. Students will be able to implement and analyze running time for various sorting algorithms.
6. Students will be able to represent graphs and implement well-known graph algorithms.

Course Measurable Objectives (CMOs)

1. Analyze problems and select the appropriate data structure.
2. Design the most efficient data structure for solving a problem.
3. Utilize effective search, insertion and deletion algorithms.
4. Estimate running time for the algorithm studied in class or new algorithms.
5. Implement sorting algorithms.
6. Implement effective search with search trees and hashing.
7. Understand and implement graph algorithms.
8. Identify main memory access and disk access costs.