The joint task force of ACM and IEEE Computer Society released recent guidelines for undergraduate computer science majors late in 2013. Since that time, many computer science departments have reviewed the included recommendations and exemplars from various institutions, and made changes to the programs that they offer. In this panel, we will share the experiences of the panelists from a variety of computer science programs in reviewing and responding to the new curriculum guidelines. The panel hopes to generate additional discussion about new knowledge areas and models for incorporating recommended content into programs at small, liberal arts institutions.

1. Computer Science
Curricula 2013
11/7/15

2. Overview
 Represent 4 different small, liberal arts universities
 University of Mary Washington
 Randolph-Macon College
 Furman University
 Elon University

3. Terminology used in Report
Topics are identified as either “Core” or “Elective” with
the core further subdivided into
“Tier-1” and “Tier-2.”
• A curriculum should include all topics in the Tier-1 core
and ensure that all students cover this material.
• A curriculum should include all or almost all topics in
the Tier-2 core and ensure that all students encounter
the vast majority of this material.
• A curriculum should include significant elective
material: Covering only “Core” topics is insufficient for
a complete curriculum.

4. Mathematics Requirements in
Computer Science
CS2013 only specifies mathematical
requirements that are directly relevant for the
large majority of all CS, for example,
• elements of set theory,
• logic, and
• discrete probability, among others).
These mathematics requirements are
specified in the Body of Knowledge primarily
in the Discrete Structures (DS) Knowledge
Area.

5. Our Required Mathematics
CPSC 125 (4 Credits)
Designed to prepare beginning Computer
Science majors for advanced study
by emphasizing the components of Discrete
Mathematics especially related to Computer
Science. Topics include systems, logic,
methods of proof, counting techniques,
mathematical induction, sets, relations,
functions, vectors, matrices, graphs and
trees.
http://www.allthemath.org/about/

6. Our Required Mathematics
CPSC 326 (4 Credits)
Prerequisites: CPSC 125A and 240. Covers structures and
concepts relating to the underlying theory of computation
and mathematical models of actual physical
processes. Also covers a repertoire of advanced algorithms
for data processing, and the asymptotic analysis of those
algorithms to describe their running time and space
requirements. Topics may include formal languages,
automata theory, Turing machine, the halting problem, NP-
completeness, searching and traversal algorithms, dynamic
programming, compression algorithms, and random
number generation
http://cs.umw.edu/~finlayson/class/fall15/cpsc326/

7. Knowledge Area Breakdown

8. Knowledge Area Breakdown

9. Knowledge Area Breakdown

10. Electives and Math
UMW Courses/Minors Math discussed in course
or minor
Data Science Minor at
UMW
Numerical Analysis
Probability and Statistics
Graphics Linear Algebra
Security Cryptography
Data Mining Linear Algebra
Statistics
Calculus

11. Recommendation for Students
Students considering a career with the
federal government should be aware that
the US Department of Operations and
Personnel Management standards require a
minimum of 15 credit hours of mathematics in
order for employees to be classified as a
“Computer Scientist.” Students interested in
federal employment in this classification are
encouraged to take MATH 121, MATH 122,
MATH 200, and any additional MATH course
numbered 300 or higher. A minor in Applied
Mathematics would also provide appropriate
preparation.

12. Increasing Parallel Programming
Content
Survey conducted to inform the CSC ’13
Two areas most identified to add to Body of Knowledge
security
parallel and distributed computing

13. CSC ‘13 Recommendation
New Parallel and Distributed Computing (PD) knowledge area
Five tier-1 hours and ten tier-2 hours,
Approximately 13 lecture hours for ugrad CS degree

14. UMW’s old model
Some coverage of PD topics in required operating systems
course
Elective course: Parallel Computing

15. UMW’s new model
 Maintain previous coverage
 Add 2-3 week module on parallel programming to
OOA&D course (CS 2 for us)
 Required for all majors (CS major, CS minor, CIS major,
GIS major)

16. Content of Parallelism Module
 Mostly shared memory model of parallelism
 Using materials developed by Dan Grossman at the
University of Washington
 goals of parallelism,
 the need for communication and coordination,
 atomicity,
 data races,
 bad interleavings,
 and deadlock.

17. Adding Distributed Computing
 Randolph-Macon College restricts a major <= 42 credit
hours, including those required from other disciplines.
 Program was lacking coverage of the core topics from
 networking,
 operating systems,
 and parallel computing.

18. Modifying Existing Unix Course
 Already required a course that introduces C/C++
programming and the use of UNIX systems.
 Revised to refocus the contents on systems
programming with C/C++ and UNIX as the tools that
will be used instead of being the main focus of the
course

19. Modified Course Content
 Covers core topics from several of the knowledge
areas that our program was previously lacking:
 the use of sockets and network applications (NC
knowledge area);
 memory management, currency and threads (OS);
 an introduction to parallel algorithms and
communication and coordination between
applications (PD)

20. Integrate More With Other Disciplines
 “Big Tent” View of CS: As CS expands to include more cross-
disciplinary work and new programs of the form “Computational
Biology,” “Computational Engineering,” and “Computational X”
are developed, it is important to embrace an outward-looking
view that sees CS as a discipline actively seeking to work with
and integrate into other disciplines.
 Work force: need to prepare students to work in a variety of
potential professions in a rapidly changing field that reaches
across disciplines.
 Graduates: need not only technical skills, but also the ability to
combine these skills with domain knowledge gained by
communicating with and learning from experts in diverse
domains.

21. Computing across the Curriculum
 Thematic approach to the introductory course
 Second-level general education courses
 Interdisciplinary IT major with cognate discipline
 Interdisciplinary teaching

22. Computing across the Curriculum
 Thematic approach to the introductory course
 Second-level general education courses
 Interdisciplinary IT major with cognate discipline
 Interdisciplinary teaching

23. New Introduction to CS Course
 Goal: Introduction to the Computer Science discipline
through the lens of an interdisciplinary problem1
 Expose students to computing approaches to problem solving they would
not normally see until after completing their core courses, while illustrating
the application of computing to diverse fields.
 What do you need to understand about Computer Science
to use computing in an interdisciplinary context?
 Survey of topics in Computer Science
 Audience:
 Entry point to major
 Introduction to CS for non-majors
1 Tartaro, A. & Cottingham, H. 2014. A Problem-based Survey Introduction to Computer Science for
Majors and Non-majors. Journal of Computing Sciences in Colleges.

24. The “Rules”
1. Instructor chooses problem area.
2. Instructor chooses computer science topics.
3. Instructor teaches majors and nonmajors.
24

25. Example Problem Areas
Business Analytics and Data Mining
“The Power of Words”
Social Media
25
(Images from npr.org)

26. Example Problem Areas
“Secret Communication”
Bioinformatics
Creativity & Digital Media
26
(Images from npr.org)

27. Interdisciplinary Information Technology
Major with a Cognate Discipline
 Required core courses:
 CSC-105: Introduction to Computer Science
 CSC-121: Introduction to Programming
 CSC-122: Data Structures and Algorithms
 Elective options:
 Two additional CSC courses numbered 200 or above, with at least
one numbered 300 or above, to be approved at the time of
declaration by the Dept. of CS chair
 Three additional courses numbered 200 or above, with at least one
numbered 300 or above, selected from a cognate department or
course of study (i.e. one leading to a major) to be approved at the
time of declaration by the Dept. of CS chair, in consultation with the
chair of the cognate department
 Capstone Experience (required):
 CSC-475: Seminar in Computer Science, or
 CSC-502: Research in Computer Science
 Synthesize student’s studies in CS and the cognate discipline

28. Relationship to Computer Science
 Designed to offer a complementary balance to our
more theoretically oriented Computer Science major
 CS still the primary option for those students seeking
graduate level degrees in Computer Science proper
 Common core of courses

29. Experience
 Majors declared with a variety of cognates thus far, including:
 Business
 Political Science
 Economics
 Music
 Religion
 Chemistry
 Biology
 Philosophy
 English
 Psychology
 Of 61 declared majors at present, 17 are IT (28%)
 In 2013, 10 of 45 majors were the “old” IT (22%)

30. No Changes
 validate some aspects of our existing curriculum
 Mobile Computing for the past five years (now explicitly
covered as part of the new Platform-Based Development
Knowledge Area)
 Math requirements in computer science reflected our
current concerns and issues in developing
students’ mathematical maturity within the quickly
changing pre-requisite structure from our math
department.