Departmental Learning Goals
Computer Science Learning Goals
Computer Science is the science of algorithms- theory, analysis, design, and implementation; as well as the design and implementation of physical computer systems. As such it is an interdisciplinary field with roots in mathematics and engineering and applications across all academic disciplines. The program at Bryn Mawr is founded on the belief that computer science should transcend from being a subfield of mathematics and engineering and play a broader role in all forms of human inquiry. It strives to build a strong foundation of computing in our students and prepares them for a life full of learning that extends well beyond their time at Bryn Mawr College. Intrinsically, much of the study of computation revolves around the development of quantitative abilities.
| Computer Science Departmental Learning Goal | Bryn Mawr Learning Outcomes |
|---|---|
| Computational problem-solving: Be able to apply problem solving skills to formalize general problem statements into precise algorithmic solutions. | Critical thinking skills; problem-solving ability; quantitative ability |
| Programming proficiency: Master the fundamental constructs and styles of programming. Knowledge of data structures and algorithms, testing and debugging, tooling and workflow and independent adaptation are also important. | Quantitative ability; problem-solving ability; |
| Theoretical foundations: Have adequate exposure to theoretical foundations of computation such as logic and discrete mathematics, formal models of computation, and complexity analysis of algorithms. | Critical thinking skills; problem-solving ability; Quantitative ability; |
| Computer systems: Gain the fundamental understanding of topics in computer systems such as programming language paradigms, operating systems, compilers, and high-performance computing, and the interdependencies among these topics. | Quantitative ability; problem-solving ability; Ability to view problems from multiple perspectives; |
| Conducting research: Have experience conducting research and completing large projects. | Research skills; quantitative ability |
| Strong oral and written communication skills: Be able to explain and present technical ideas, write about them, and perform critical reflections. | Written skills; oral communication skills; quantitative ability |
| Knowledge transfer: Be able to apply the computational and algorithmic problem solving skills across many disciplines. | Ability to view problems from multiple perspectives; problem-solving ability |