CS2013-final-report

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Additional topics Successful course participants will: • Understand the modeling process • Be able to develop and analyze systems dynamics models and Monte Carlo simulations with a team • Understand the concept of rate of change • Understand basic system dynamics models, such as ones for unconstrained and constrained growth, competition, predator-prey, SIR, enzyme kinetics • Be able to perform error computations • Be able to use Euler's and Runge-Kutta 2 Methods • Be able to develop an empirical model from data • Understand basic cellular automaton simulations, such as ones for random walks, diffusion, and reactiondiffusion • Be able to verify and validate models • Understand basic hardware and programming issues of high performance computing • Be able to use a system dynamics tool, such as Vensim, STELLA, or Berkeley Madonna • Be able to use a computational tool, such as MATLB, Mathematica, or Maple. Other comments Wofford College's Emphasis in Computational Science (ECS), administered by the Computer Science Department, is available to students pursuing a B.S. in a laboratory science, mathematics, or computer science. The Emphasis requires five courses—Modeling and Simulation for the Sciences (this course), CS1, CS2, Calculus I, and Data and Visualization (optionally in 2013, Bioinformatics or High Performance Computing)—and a summer internship involving computation in the sciences. Computer science majors obtaining the ECS must also complete 8 additional semester hours of a laboratory science at the 200+ level. Note: Data and Visualization covers creation of Web-accessible scientific databases, a dynamic programming technique of genomic sequence alignment, and scientific visualization programming in C with OpenGL. - 261 -
MAT 267: Discrete Mathematics, Union County College Cranford, NJ Dr. Cynthia Roemer, Department Chair roemer@ucc.edu www.ucc.edu Per College policy, all course materials are password-protected. Instructional resources are available upon email request. Knowledge Areas that contain topics and learning outcomes covered in the course Knowledge Area Total Hours of Coverage Discrete Structures (DS) 42 hours Where does the course fit in your curriculum Union County College offers this course both Fall and Spring semesters. Computer Science majors typically complete the required Discrete Mathematics course as sophomores. Students are eligible to enroll in this course after passing pre-calculus (MAT 143) with a grade of C or better, or scoring well enough on the College Level Mathematics Test to place directly into it. CS majors are also required to complete Calculus I (MAT 171). What is covered in the course This course will develop advanced mathematics skills appropriate for students pursuing STEM studies such as Engineering, Science, Computer Science, and Mathematics. Topics include sets, numbers, algorithms, logic, computer arithmetic, applied modern algebra, combinations, recursion principles, graph theory, trees, discrete probability, and digraphs. What is the format of the course This course earns 3 credit hours and consists of 3 lecture hours per week for 14 weeks. Discrete Mathematics offered at Union County College currently meets twice per week for 80 minutes each. How are students assessed Students are assessed on a combination of homework, quizzes/tests, group activities, discussion, projects, and a comprehensive <strong>final</strong> exam. Students are expected to complete homework assignments/projects on a weekly basis. For a typical student, each assignment will require at least 3 hours to complete. Course textbooks and materials Text: Discrete Mathematics by Sherwood Washburn, Thomas Marlowe, & Charles T. Ryan (Addison-Wesley) A graphing calculator (e.g. TI-89) and a computer algebra system (e.g. MAPLE) are required for completing certain homework exercises and projects. Union County College has a Mathematics Success Center that is available for tutoring assistance for all mathematics courses. Why do you teach the course this way Discrete Mathematics is a transfer-oriented course designed to meet the requirements of Computer Science, Engineering and Mathematics degree programs. Many of the Computer Science majors at Union County College - 262 -
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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/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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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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Body of Knowledge coverage KA Knowl
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Why do you teach the course this wa
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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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programming (scripting) is covered
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One way to document this spiral app
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3. Data types and structures 1. pri
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◦ Comparison of results for small
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Appendix D: Curricular Exemplars Th
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Bluegrass Community and Technical C
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Knowledge Units in a Typical Major
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Notation: < 25% of KU covered # 25-
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Appendix: Information on Individual
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Curricular Analysis The Knowledge U
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management, the Internet, e-mail, t
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Mathematical Foundations (two desig
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Multi-paradigm, Introductory Sequen
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Additional Comments Although the ex
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CSC 312 - Implementation of Program
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• Biocomputation • Unspecialize
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Additional Comments We instituted a
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CS 145: Introduction to Databases T
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Williams College Department of Comp
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Possible Curricular Revisions Note
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CSCI 237 - Computer Organization Th
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surface scattering functions, binar
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A Cooperative Project of
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