CS2013-final-report

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CSCI 1730: Introduction to Programming Languages, Brown University Providence, RI, USA Shriram Krishnamurthi sk@cs.brown.edu http://www.cs.brown.edu/courses/csci1730/ Knowledge Areas that contain topics and learning outcomes covered in the course Knowledge Area Programming Languages (PL) 35 Total Hours of Coverage Where does the course fit in your curriculum The course is designed for third- and fourth-year undergraduates and for PhD students who are either early in their study or outside this research area. Over the years I have shrunk the prerequisites, so it requires only the first year introductory computer science sequence, discrete math, and some theory. The course is not required. However, it consistently has one of the highest enrollments in the department. What is covered in the course The course uses definitional interpreters and related techniques to teach the core of several programming languages. The course begins with a quick tour of writing definitional interpreters by covering substitution, environments, and higher-order functions. The course then dives into several topics in depth: • Mutation • Recursion and cycles • Objects • Memory management • Control operators • Types • Contracts • Alternate evaluation models What is the format of the course Classroom time is a combination of lecture and discussion. We learn by exploration of mistakes. How are students assessed There are about ten programming assignments and three written homeworks. The written ones are open-ended and ask students to explore design alternatives. Advanced students are given a small number of classic papers to read. Students spend over 10 and up to 20 hours per week on the course. Course textbooks and materials The course uses Programming Languages: Application and Interpretation by Shriram Krishnamurthi. All programming is done in variations of the Racket programming language using the DrRacket programming environment. Some versions of the course task students with writing programs in a variety of other languages such as Haskell and Prolog. - 367 -
Why do you teach the course this way My primary goal in the design of this course is to teach “the other 90%”: the population of students who will not go on to become programming language researchers. My goal is to infect them with linguistic thinking: to understand that by embodying properties and invariants in their design, languages can solve problems. Furthermore, most of them, as working developers, will inevitably build languages of their own; I warn them about classic design mistakes and hope they will learn enough to not make ones of their own. The course is revised with virtually every offering. Each time we pick one module and try to innovate in the presentation or learning materials. Independent student feedback suggests the course is one of the most challenging in the department. Nevertheless, it does not prevent high enrollments, since students seem to appreciate the linguistic mindset it engenders. Body of Knowledge coverage KA Knowledge Unit Topics Covered Hours PL Object-Oriented Programming Object representations and encodings, types 3 PL Functional Programming All 3 PL Basic Type Systems All 9 PL Language Translation and Execution Interpretation, representations 3 PL Runtime Systems Value layout, garbage collection, manual memory management 3 PL Advanced Programming Constructs Almost all (varies by year) 6 PL Type Systems All 3 PL Language Pragmatics Almost all (varies by year) 3 PL Logic Programming Relationship to unification and continuations 2 - 368 -
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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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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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