Computer science is the study of algorithms and software systems: their theory, analysis, design, efficiency, implementation, maintenance, and application. Computers Science Educators seek to advance the fundamental quality of computer science education by having a deeper understanding on how students learn combined with the complexities of the computational mindset that is developed through computer science.

Computer Science Education students will engage in coursework related to both computer science and education, and their intersection, the growing field of computer science education. Through course work, service learning, and student teaching, this degree will prepare students to enter the field as a K-12 teachers. Furthermore, this degree will serve as preparation for admission into advanced degree programs and college level teaching and research in the field of computer science education.

Course work includes the same core foundation expected of all computer science concentrations, and course work specific to computer science education and teaching standards including web development, software engineering, and networking.

Learning Outcomes

Upon completing this program, students will be able to:

  • Demonstrate proficiency in the areas of software design and development, computing systems, and algorithmic analysis. Students will have a thorough grounding in the key principles and practices of computing, and in the mathematical and scientific principles of computation.
  • Work effectively in groups to develop computational solutions to complex problems.
  • Communicate ideas effectively, both generally and specifically, with regard to technology and computing.
  • Demonstrate strong pedagogical practices related to education and computational thinking.
  • Develop lesson plans related to computer science with artifact generation and statistical analysis of artifacts and student performance.
  • Demonstrate the variety of fields in which computer science is applied, with direct knowledge in fields relating to the CO Standards for CS Education (algorithms, data structures, web development, networking and security)

Potential Occupations

Upon completing this program, students can either attend graduate school in computer science, find professional computer-related employment, or directly enter employment as K-12 computer science / technology education teachers.

Students interested in pursuing a teaching license through CSU may refer to the Center for Educator Preparation and the School of Education for general information. 

Effective Fall 2022

A minimum grade of C (2.000) is required in CO 150 and in all CS, DSCI, MATH, and STAT courses which are required for graduation.

Freshman
AUCCCredits
CO 150College Composition (GT-CO2)1A3
MATH 156 or 1601Mathematics for Computational Science I (GT-MA1)
Calculus for Physical Scientists I (GT-MA1)
1B4
Select one group from the following:2 5-9
Group A:
  
Culture and Coding: Java (GT-AH3)
Culture and Coding: Python (GT-AH3)
3B 
CS1--Introduction to Java Programming
CS1--Computational Thinking with Java
  
Group B:
  
Python for STEM  
CS1--Introduction to Java Programming
CS1--Computational Thinking with Java
  
3B 
Group C:
  
CS1---No Prior Programming Experience  
3B 
CS 201/PHIL 201Ethical Computing Systems (GT-AH3)3B3
Select at least two courses totaling a minimum of 7 credits from the following (one course must be or include the sequenced laboratory): 7
Introduction to Astronomy (GT-SC2)3A 
Human Origins and Variation (GT-SC2)3A 
Principles of Animal Biology (GT-SC2)3A 
Principles of Plant Biology (GT-SC1)3A 
Fundamentals of Chemistry (GT-SC2)3A 
General Chemistry I (GT-SC2)3A 
Exploring Earth - Physical Geology (GT-SC2)3A 
The Blue Planet - Geology of Our Environment (GT-SC2)3A 
Geology of Natural Resources (GT-SC2)3A 
Physical Geology for Scientists and Engineers3A 
Honors Seminar: Knowing in the Sciences3A 
Attributes of Living Systems (GT-SC1)3A 
Biology of Organisms-Animals and Plants (GT-SC1)3A 
Introductory Genetics: Applied/Population/Conservation/Ecological (GT-SC2)3A 
Introductory Genetics: Molecular/Immunological/Developmental (GT-SC2)3A 
Fundamentals of Ecology (GT-SC2)3A 
Oceanography (GT-SC2)3A 
General Physics I (GT-SC1)3A 
General Physics II (GT-SC1)3A 
Physics for Scientists and Engineers I (GT-SC1)3A 
Physics for Scientists and Engineers II (GT-SC1)3A 
Diversity, Equity, and Inclusion1C3
Electives3 1-5
 Total Credits 30
Sophomore
 
CS 165CS2--Data Structures 4
CS 220Discrete Structures and their Applications 4
CS 253Software Development with C++ 4
CS 270Computer Organization 4
EDUC 275Schooling in the United States (GT-SS3)3C3
EDUC 340Literacy and the Learner 3
Select one course from the following: 3-4
Linear Algebra for Data Science  
Linear Algebra I  
Select one course from the following: 1-3
Introduction to Applied Statistical Methods  
Statistics Supplement: General Applications  
Introduction to Biostatistics  
Intro to Theory and Practice of Statistics  
Electives 1-4
 Total Credits 30
Junior
 
CS 314Software Engineering4A,4B3
CS 320Algorithms--Theory and Practice 3
CS 370Operating Systems 3
Two CS courses numbered 300- or above, excluding 380-399 and 480-499 6-8
One CS course numbered 400- or above, excluding 480-499 4
EDUC 331Educational Technology and Assessment 2
EDUC 350Instruction I-Individualization/Management 3
EDUC 386Practicum-Instruction I 1
Advanced Writing23
Historical Perspectives3D3
 Total Credits 31-33
Senior
 
CS Education Standards: Select 2 courses from the following 7-8
Modern Web Applications  
Object-Oriented Design  
Database Systems  
Computer Networks and the Internet  
EDUC 450Instruction II-Standards and Assessment 4
EDUC 486EPracticum: Instruction II 1
EDCT 465Methods and Materials in Technology Education 3
EDCT 485Student Teaching4A,4B,4C11
EDUC 493ASeminar: Professional Relations 1
Electives4 0-1
 Total Credits 27-29
 Program Total Credits: 120
1

MATH 156 recommended for computer science majors who do not already have MATH 160 credit. 

2

Recommended sequence for most incoming students is Group A: CS 150B to CS 164.

3

CS 192 or other seminar course is a recommended elective for incoming, first semester, students. 

4

Select enough elective credits to bring the program total to a minimum of 120 credits, of which at least 42 must be upper-division (300- to 400-level).

Distinctive Requirements for Degree Program:

To prepare for first semester: The curriculum for the Computer Science major assumes students enter college prepared to take calculus. Entering students who are not prepared to take calculus will need to fulfill pre-calculus requirements in the first semester. All students must maintain a C (2.000) or better in CO 150 and in all CS, DSCI, MATH, and STAT courses which are required for graduation.4

Freshman
Semester 1CriticalRecommendedAUCCCredits
CO 150College Composition (GT-CO2)  1A3
First course in Group A, B, or C (See options on Concentration Requirements Tab)   2-4
Diversity, Equity, and InclusionX 1C3
Department Approved Science (See list on Concentration Requirements Tab)  3A3
Electives   2-4
MATH 124 and MATH 126 may be necessary for some students to fulfill pre-calculus requirements.X   
 Total Credits   15
Semester 2CriticalRecommendedAUCCCredits
CS 201/PHIL 201Ethical Computing Systems (GT-AH3)  3B3
MATH 156 or 160Mathematics for Computational Science I (GT-MA1)
Calculus for Physical Scientists I (GT-MA1)
 X1B4
Remaining course(s) from Group A, B, or C (See options on Concentration Requirements Tab)X  2-7
Department Approved Science with Lab (See list on Concentration Requirements Tab)  3A4
Electives   0-2
CO 150 must be completed by the end of Semester 2 with a grade of C or better.X   
 Total Credits   15
Sophomore
Semester 3CriticalRecommendedAUCCCredits
CS 165CS2--Data Structures X 4
CS 220Discrete Structures and their Applications X 4
EDUC 275Schooling in the United States (GT-SS3) X3C3
Select one course from the following:   1-3
Introduction to Applied Statistical Methods    
Statistics Supplement: General Applications    
Introduction to Biostatistics    
Intro to Theory and Practice of Statistics    
Electives   1-3
 Total Credits   15
Semester 4CriticalRecommendedAUCCCredits
CS 253Software Development with C++ X 4
CS 270Computer OrganizationX  4
EDUC 340Literacy and the Learner   3
Select one course from the following:   3-4
Linear Algebra for Data ScienceX   
Linear Algebra IX   
CS 165 and CS 220 and CS 270 must be completed by the end of Semester 4.X   
MATH 156 or MATH 160 and MATH 369 or DSCI 369 must be completed by the end of Semester 4.X   
 Total Credits   15
Junior
Semester 5CriticalRecommendedAUCCCredits
CS 314Software Engineering X4A,4B3
CS 320Algorithms--Theory and Practice X 3
CS 370Operating Systems X 3
EDUC 331Educational Technology and Assessment   2
Historical Perspectives  3D3
Advanced Writing  23
CS 253 must be completed by the end of Semester 5.X   
 Total Credits   17
Semester 6CriticalRecommendedAUCCCredits
Two CS courses numbered 300- or above, excluding 380-399 and 480-499 X 6-8
One CS course numbered 400- or above, excluding 480-499 X 4
EDUC 350Instruction I-Individualization/ManagementX  3
EDUC 386Practicum-Instruction IX  1
CS 314 and CS 320 and CS 370 must be completed by the end of Semester 6.X   
 Total Credits   14-16
Senior
Semester 7CriticalRecommendedAUCCCredits
Two CS Education Standards Courses (See CS Education Standards Course List on Concentration Requirements tab)X  7-8
EDUC 450Instruction II-Standards and AssessmentX  4
EDUC 486EPracticum: Instruction IIX  1
EDCT 465Methods and Materials in Technology EducationX  3
 Total Credits   15-16
Semester 8CriticalRecommendedAUCCCredits
EDCT 485Student TeachingX 4A,4B,4C11
EDUC 493ASeminar: Professional RelationsX  1
ElectivesX  0-1
The benchmark courses for the 8th semester are the remaining courses in the entire program of study.X   
 Total Credits   12-13
 Program Total Credits:   120