Computational Thinking

Course Number: CS 160
Transcript Title: Computational Thinking
Created: February 17, 2015
Updated: July 16, 2019
Total Credits: 4
Lecture Hours: 40
Lecture / Lab Hours: 0
Lab Hours: 0
Satisfies Cultural Literacy requirement: No
Satisfies General Education requirement: No
Grading options: A-F (default), P-NP, audit
Repeats available for credit: 0

Prerequisites

WR 115, RD 115 and MTH 20 or equivalent placement test scores

Course Description

Explores the field of computer science. Provides an overview of computer architecture, software development engineering, data organization, problem-solving strategies, ethics and theory of computation. Explores career options and develops rudimentary software developmental skills. Prerequisites: WR 115, RD 115 and MTH 20 or equivalent placement test scores.  Audit available.

Intended Outcomes

Upon successful completion of this course, students will be able to:

  1. Identify career opportunities in computing science and distinguish computing science from related disciplines.
  2. Develop and analyze simple algorithms.
  3. Initiate problem-solving strategies with respect to the operation of computer hardware.
  4. Apply ethical understanding of privacy, professional integrity, and service issues in the computing field.
  5. Compare algorithmsbased on the underlying limitations of computation.
  6. Identify optimal data organization techniques from a variety of methods.

Outcome Assessment Strategies

Homework, observation, class discussion, examination.

Course Activities and Design

The determination of teaching strategies used in the delivery of outcomes is generally left to the discretion of the instructor. Here are some strategies that you might consider when designing your course: lecture, small group/forum discussion, flipped classroom, dyads, oral presentation, role play, simulation scenarios, group projects, service learning projects, hands-on lab, peer review/workshops, cooperative learning (jigsaw, fishbowl), inquiry based instruction, differentiated instruction (learning centers), graphic organizers, etc.

Course Content (Themes, Concepts, Issues and Skills)

  • computing
    • career opportunities
    • real life applications
    • ethics
    • terminology
  • algorithms
    • computation
    • program
    • hardware execution
    • complexity
      • space
      • time
  • problem solving strategies
  • information
    • bits
    • representing real-world entities