CS2013-final-report

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Williams College Department of Computer Science www.cs.williams.edu Contact: Andrea Danyluk (andrea@cs.williams.edu) Curricular Overview Williams College is a highly-selective liberal arts college of about 2200 students. To complete the requirements for the Bachelor of Arts degree, students must take at least 32 regularly graded one-unit courses, satisfy the requirements for a major, and fulfill distribution requirements (3 courses in each Division – Arts and Languages; Social Studies; Science and Mathematics. Students must also complete 1 Exploring Diversity course, 2 writing-intensive courses, and 1 quantitative/formal reasoning course). In order to ensure that students are free to explore a wide range of academic subjects in the liberal arts tradition, the College places a limit on the number of courses that may be required for a major – typically 9. Students are free to take as many courses in their majors as they’d like, provided they complete the distribution requirements. The Computer Science Department has eight faculty with a wide range of research interests and expertise, including distributed systems, parallel programming, architecture, artificial intelligence, programming languages, algorithms, graph theory, graphics, and networks. Computer Science Major The Williams College Computer Science major has been strongly influenced by LACS (Liberal Arts Computer Science Consortium) model curricula. In all, 10 courses are required for the major. A minimum of 8 courses is required in Computer Science, including Introductory Courses (offered every semester) • CSCI 134: Introduction to Computer Science • CSCI 136: Data Structures and Advanced Programming Core Courses (offered once each year) • CSCI 237: Computer Organization • CSCI 256: Algorithm Design and Analysis • CSCI 334: Principles of Programming Languages • CSCI 361: Theory of Computation Electives Two or more electives (bringing the total number of Computer Science courses to at least 8) chosen from 300- or 400-level courses in Computer Science. At least one of these must be a course designated as a PROJECT COURSE. “Reading”, “Research”, and “Thesis” courses do not normally satisfy the elective requirement. - 503 -
Current electives are • Computer Networks • Digital Design and Modern Architecture • Distributed Systems [PROJECT] • Advanced Algorithms • Computational Graphics [PROJECT] • Artificial Intelligence [PROJECT] • Machine Learning • Operating Systems [PROJECT] • Compiler Design [PROJECT] • Computational Biology • Integrative Bioinformatics, Genomics, and Proteomics Lab Electives are offered, on average, once every other year. Required Courses in Mathematics MATH 200: Discrete Mathematics and any other Mathematics or Statistics course at the 200-level or higher In addition, seniors are required to attend weekly computer science colloquia. Curricular Analysis Here we provide a high level picture of our coverage of <strong>CS2013</strong> Core-Tier1 and Tier2 topics. For this analysis, we consider a typical major to take the introductory sequence, the four core courses, and three electives, as well as Discrete Mathematics. Though only two electives are required for the major, Computer Science students take, on average, 3.6 electives (computed over the last three years). Many students also enroll in Reading, Research, or Thesis courses, but we do not include those in our analysis. We have offered two different versions of our Introduction to Computer Science course over the last several years. The one offered most frequently has been a network-themed course. We use that in our mapping below. The specific electives we have used in the mapping are: • CSCI 337: Digital Design and Modern Architecture • CSCI 373: Artificial Intelligence • CSCI 432: Operating Systems Tier 1 Tier 2 Typical major – Intro, Core, Discrete Math + Architecture, AI, and OS 83% 60% Common CS core – Intro, Core, Discrete Math – not the complete major 70% 40% Typical major from row 1 + either Distributed Systems or Networks 85% 68% - 504 -
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Computer Science Curricula 2013 Cur
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Computer Science Curricula 2013 Cop
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CS2013 Steering Committee ACM Deleg
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Chapter 5: Introductory Courses ...
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CC152: Computer Architecture and En
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Programming Languages and Technique
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Chapter 1: Introduction ACM and IEE
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KA subcommittee Chairs (as members
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Knowledge Areas The CS2013 Body of
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of the implications of social respo
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Manaris (College of Charleston), Sa
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Chapter 2: Principles Early in its
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novel, interesting, and effective w
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Appreciation of the interplay betwe
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to be able to communicate with, and
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● The learning outcomes and hour
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● Many strong computer-science cu
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include appropriate elective materi
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We use three levels of mastery, def
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Parallel and Distributed Computing
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select topics from Tier-2 (to inclu
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common“CS0” courses: precursor
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Tradeoffs: A programming-focused in
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Parallel Processing Traditionally,
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Chapter 6: Institutional Challenges
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Computer Science Across Campus An a
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programs do not have an explicit li
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accessible, building interdisciplin
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provide for assessing the effective
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AL. Algorithms and Complexity (19 C
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[Core-Tier2] 7. Describe various he
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Learning Outcomes: 1. Define the cl
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Architecture and Organization (AR)
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7. Evaluate the functional and timi
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AR/Interfacing and Communication [1
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Computational Science (CN) Computat
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CN/Introduction to Modeling and Sim
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CN/Processing [Elective] The proces
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CN/Data, Information, and Knowledge
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Discrete Structures (DS) Discrete s
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DS/Basic Logic [9 Core-Tier1 hours]
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DS/Graphs and Trees [3 Core-Tier1 h
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Graphics and Visualization (GV) Com
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GV/Fundamental Concepts [2 Core-Tie
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GV/Geometric Modeling [Elective] To
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GV/Visualization [Elective] Visuali
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HCI/Foundations [4 Core-Tier1 hours
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HCI/User-Centered Design and Testin
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Learning Outcomes: 1. Explain basic
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o Game engines o Mobile augmented r
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IAS. Information Assurance and Secu
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OS/Concurrency 1.5 OS/Scheduling an
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SP/Social Context 0.5 SP/Analytical
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11. Discuss the importance of usabi
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Learning outcomes: [Core-Tier2] 1.
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Learning outcomes: 1. Describe the
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Information Management (IM) Informa
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• Design of core DBMS functions (
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3. Demonstrate use of the relationa
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IM/Physical Database Design [Electi
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• Presentation, rendering, synchr
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IS/Fundamental Issues [1 Core-Tier2
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4. Describe over-fitting in the con
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IS/Agents [Elective] Cross-referenc
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Learning Outcomes: 1. Explain the d
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Networking and Communication (NC) T
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NC/Networked Applications [1.5 Core
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NC/Social Networking [Elective] Top
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OS/Overview of Operating Systems [2
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OS/Memory Management [3 Core-Tier2
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OS/File Systems [Elective] Topics:
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Platform-Based Development (PBD) Pl
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Learning Outcomes: 1. Design and im
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Because the terminology of parallel
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PD/Parallelism Fundamentals [2 Core
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• Topologies o Interconnects o Cl
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o Software as a service o Security
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PL. Programming Languages (8 Core-T
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PL/Functional Programming [3 Core-T
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o o o Enforce invariants during cod
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PL/Compiler Semantic Analysis [Elec
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• Metaprogramming: Macros, Genera
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PL/Language Pragmatics [Elective] T
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emphasize formal analysis (e.g., Bi
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Learning Outcomes: 1. Analyze and e
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Software Engineering (SE) In every
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such system are assigned to the cor
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Learning Outcomes: [Core-Tier1] 1.
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SE/Tools and Environments [2 Core-T
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SE/Software Design [3 Core-Tier1 ho
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[Elective] • Potential security p
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o o o o Code segments Libraries and
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Systems Fundamentals (SF) The under
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2. Describe how hardware, VM, OS, a
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2. Describe the scheduling algorith
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Social Issues and Professional Prac
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understanding of our commitment to
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Learning Outcomes: 1. Evaluate stak
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Learning Outcomes: [Core-Tier1] 1.
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[Elective] 8. Discuss ways to influ
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• Differences in access to comput
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Appendix B: Migrating to CS2013 A g
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and are treated as a topic geared t
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GV The storage of analog signals in
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SDF This new knowledge area pulls t
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Table B-3: Core Learning Topics and
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Table B-4: New and Expanded Core Le
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IAS Core-Tier1: • Analyze the tra
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IS NC Core-Tier2: • Translate a n
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• Describe at least one design te
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• Explain why the creation of cor
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• Use refactoring in the process
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• Apply simple algorithms for exp
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Appendix C: Course Exemplars While
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IS U. San Francisco Artificial Inte
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ACM/IEEE-CS CS2013 Course-Exemplar
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CSCI 140: Algorithms, Pomona Colleg
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AL PD advanced data structures algo
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What is the format of the course Th
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CS 256 Algorithm Design and Analysi
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and other applications including Ba
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• Data races and higher-level rac
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CS/ECE 552: Introduction to Compute
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Body of Knowledge coverage KA Knowl
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AR Assembly Level Machine Organizat
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Altruism/Collaboration/Competition,
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everyday lives, and therefore at le
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COSC/MATH 201: Modeling and Simulat
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ehaviors, simplifying assumptions;
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MAT 267: Discrete Mathematics, Unio
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Identify a problem and analyze it i
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CS109 covers: • Counting • Comb
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CS 250 - Discrete Structures I, Por
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CS 251 - Discrete Structures II, Po
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DS Graphs and Trees Tree, tree trav
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The course gives an overview to a v
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CS371: Computer Graphics, Williams
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Texture mapping, including minifica
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Other materials are: R and RStudio
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3. Assignment (20% + 10%) Due in we
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CO328: Human Computer Interaction,
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Human Computer Interaction, Univers
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Human-Computer Interaction, Stanfor
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Human Information Processing (HIP),
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Software and Interface Design, Univ
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Computer Systems Security (CS-475),
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Ullman and Widom, 2 nd edition, Pre
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Technology, Ethics, and Global Soci
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SP Professional Communication These
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Why do you teach the course this wa
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search, probabilistic reasoning, lo
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Students are expected to spend abou
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CS188: Artificial Intelligence, Uni
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Introduction to Artificial Intellig
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Computer Networks, Williams College
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NC Introduction All 1.5 NC Networke
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CSCI 432 Operating Systems, William
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OS Security and Protection Access c
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Assignment Five: Memory management
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Programming Language: C Assignment
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Parallel Programming Principle and
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PD Parallel Algorithms, Analysis, a
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• Grama, A., Gupta, A., Kumar V.
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Body of Knowledge coverage For each
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1: Map-reduce for CS1/WMR 2: Multic
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What is the format of the course Co
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Csc 453: Translators and Systems So
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CSCI 434T: Compiler Design, William
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AR Machine-level representation of
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Languages and Compilers, Utrecht Un
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COMP 412: Topics in Compiler Constr
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separate compilation is the key fea
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programming languages. A major them
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CSCI 1730: Introduction to Programm
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CSC 2/454: Programming Language Des
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PL Runtime Systems Data layout; sto
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How are students assessed Over 10 w
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Programming Languages and Technique
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esults from programming language th
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PL Event-driven and Reactive Progra
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Overall, students learn the followi
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PL Type systems Compositional type
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What is the format of the course Th
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Introduction to Computer Science, H
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PD PD/Parallelism Fundamentals Para
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• Analytical Reasoning: Assertion
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CS1101: Introduction to Program Des
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Finally, the design process from
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documentation activity that occurs
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SE Software Validation and Verifica
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Cloud computing and the shift in th
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SE-2890 Software Engineering Practi
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Software Development, Quinnipiac Un
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• Networking subsystem focusing o
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SF Input/output Programmed data tra
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◦ C preprocessors, multifile prog
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Ethics in Technology (IFSM304), Uni
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Analyze basic logical fallacies in
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Specific topics include: • Capaci
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Additional topics The sustainabilit
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How are students assessed The basic
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Ethics & the Information Age (CSI 1
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SP Intellectual Property Overview a
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privacy. Students are asked to shar
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The Digital Age, Grinnell College G
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AR Digital logic and digital system
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COS 126: General Computer Science,
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Prospective computer science majors
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CSCI 0190: Accelerated Introduction
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An Overview of the Two-Course Intro
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Course textbooks and materials Free
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