Information Technology Education Standards

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Information TechnologyEducation Standards

• Jaime D.L. Caro, Ph.D.
• President, PSITE
• Project Leader, VCTI-IT
• Associate Professor of Computer Science, UP
  Diliman

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Based on reports from

• Association for Computing Machinery (ACM)
• Institute of Electrical and Electronics Engineers
  (IEEE) Computer Society
• International Federation for Information
  Processing (IFIP)
• Association for Information Systems (AIS)
• Association for Information Technology
  Professionals (AITP)
• We shall also look at policy guidelines from
• Philippines Commission on Higher Education (CHED)

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Standards?

• Standards for teaching IT
• Standards for professional development for IT
  educators
• Standards for assessment in IT education
• Standards for IT content
• Standards for IT education programs
• Standards for IT education systems

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IT Education Standards

• Recommendations versus Standards
• Minimum Standards
• UK benchmarking report recognized that
  establishing a minimum standard may discourage
  both faculty and students from pushing for
  excellence beyond that minimum.
• To avoid this danger, the UK report provides
  benchmarking standards to assess various levels
  of achievement.
• Standards for Achievement
• Benchmarking Standards
• Threshold Standard
• Modal Standard
• etc

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Threshold Standard representing the minimum level

• Demonstrate a requisite understanding of the main
  body of knowledge and theories of computer
  science/computing/information technology.
• Understand and apply essential concepts,
  principles, and practices in the context of
  well-defined scenarios, showing judgment in the
  selection and application of tools and
  techniques.
• Demonstrate the ability to work as an individual
  under guidance and as a team member.
• Discuss applications based upon the body of
  knowledge.

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Threshold Standard representing the minimum level

• Produce work involving problem identification,
  analysis, design, and development of a software
  system, along with appropriate documentation. The
  work must show some problem-solving and
  evaluation skills drawing on some supporting
  evidence and demonstrate a requisite
  understanding of and appreciation for quality.
• Identify appropriate practices within a
  professional, legal, and ethical framework.
• Appreciate the need for continuing professional
  development.

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Modal Standard representing the average level

• Demonstrate a sound understanding of the main
  areas of the body of knowledge and the theories
  of computer science, with an ability to exercise
  critical judgment across a range of issues.
• Critically analyze and apply a range of concepts,
  principles, and practices of the subject in the
  context of loosely specified problems, showing
  effective judgment in the selection and use of
  tools and techniques.

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Modal Standard representing the average level

• Produce work involving problem identification,
  analysis, design, and development of a software
  system, along with appropriate documentation. The
  work must show a range of problem solving and
  evaluation skills, draw upon supporting evidence,
  and demonstrate a good understanding of the need
  for quality.

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Modal Standard representing the average level

• Demonstrate the ability to work as an individual
  with minimum guidance and as either a leader or
  member of a team.
• Follow appropriate practices within a
  professional, legal, and ethical framework.
• Identify mechanisms for continuing professional
  development and life-long learning.
• Explain a wide range of applications based upon
  the body of knowledge.

10
Excellence Standard representing the highest
level

• Demonstrate creativity and innovativeness in
  application of the principles covered in the
  curriculum
• Contribute significantly to the analysis, design,
  and development of systems which are complex, and
  fit for purpose.
• Exercise critical evaluation and review of both
  their own work and the work of others.

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Excellence

• it is important for programs in computer science
  to provide opportunities for students of the
  highest caliber to achieve their full potential.
• programs in computer science should not limit
  those who will lead the development of the
  discipline in the future.
• human ingenuity and creativity have fostered the
  rapid development of the discipline of computer
  science in the past

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Characteristics of IT/CS Graduates

• System-level perspective.
• Graduates must develop a high-level understanding
  of systems as a whole.
• This understanding must transcend the
  implementation details of the various components
  to encompass an appreciation for the structure of
  computer systems and the processes involved in
  their construction and analysis.

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Characteristics of IT/CS Graduates

• Appreciation of the interplay between theory and
  practice.
• A fundamental aspect of computer science/IT is
  the balance between theory and practice and the
  essential link between them.
• Graduates must understand not only the
  theoretical underpinnings of the discipline but
  also how that theory influences practice.

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Characteristics of IT/CS Graduates

• Familiarity with common themes.
• In the course of an undergraduate program in
  computer science/IT, students will encounter many
  recurring themes such as abstraction, complexity,
  and evolutionary change.
• Graduates should recognize that these themes have
  broad application to the field of computer
  science and must not compartmentalize them as
  relevant only to the domains in which they were
  introduced.

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Characteristics of IT/CS Graduates

• Significant project experience.
• To ensure that graduates can successfully apply
  the knowledge they have gained, all students in
  computer science/IT programs must be involved in
  at least one substantial software project.
• Such a project demonstrates the practical
  application of principles learned in different
  courses and forces students to integrate material
  learned at different stages of the curriculum.

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Characteristics of IT/CS Graduates

• Adaptability.
• One of the essential characteristics of computer
  science over its relatively brief history has
  been an enormous pace of change.
• Graduates of a computer science program must
  possess a solid foundation that allows them to
  maintain their skills as the field evolves.

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Capabilities and Skills of IT/CS Graduates

• Cognitive capabilities relating to intellectual
  tasks specific to computer science/IT
• Practical skills relating to computer science/IT
• Additional transferable skills that may be
  developed in the context of computer science/IT
  but which are of a general nature and applicable
  in many other contexts as well

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Cognitive Capabilities and Skills

• Knowledge and understanding.
• Demonstrate knowledge and understanding of
  essential facts, concepts, principles, and
  theories relating to computer science and
  software applications.
• Modeling.
• Use such knowledge and understanding in the
  modeling and design of computer-based systems in
  a way that demonstrates comprehension of the
  tradeoff involved in design choices.
• Requirements.
• Identify and analyze criteria and specifications
  appropriate to specific problems, and plan
  strategies for their solution.

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Cognitive Capabilities and Skills

• Critical evaluation and testing.
• Analyze the extent to which a computer-based
  system meets the criteria defined for its current
  use and future development.
• Methods and tools.
• Deploy appropriate theory, practices, and tools
  for the specification, design, implementation,
  and evaluation of computer-based systems.
• Professional responsibility.
• Recognize and be guided by the social,
  professional, and ethical issues involved in the
  use of computer technology.

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Practical Capabilities and Skills

• Design and implementation.
• Specify, design, and implement computer-based
  systems.
• Evaluation.
• Evaluate systems in terms of general quality
  attributes and possible tradeoffs presented
  within the given problem.
• Information management.
• Apply the principles of effective information
  management, information organization, and
  information-retrieval skills to information of
  various kinds, including text, images, sound, and
  video.
• Operation.
• Operate computing equipment and software systems
  effectively.

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Practical Capabilities and Skills

• Human-computer interaction.
• Apply the principles of human-computer
  interaction to the evaluation and construction of
  a wide range of materials including user
  interfaces, web pages, and multimedia systems.
• Risk assessment.
• Identify any risks or safety aspects that may be
  involved in the operation of computing equipment
  within a given context.
• Tools.
• Deploy effectively the tools used for the
  construction and documentation of software, with
  particular emphasis on understanding the whole
  process involved in using computers to solve
  practical problems.

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Additional Transferable Skills

• Communication.
• Make succinct presentations to a range of
  audiences about technical problems and their
  solutions.
• Teamwork.
• Be able to work effectively as a member of a
  development team.
• Numeracy.
• Understand and explain the quantitative
  dimensions of a problem.

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Additional Transferable Skills

• Self management.
• Manage one's own learning and development,
  including time management and organizational
  skills
• Professional development.
• Keep abreast of current developments in the
  discipline to continue one's own professional
  development.

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Coping With Change

• teaching methodology that emphasizes learning as
  opposed to teaching
• students continually being challenged to think
  independently
• challenging and imaginative exercises that
  encourage student initiative
• sound framework with appropriate theory that
  ensures that the education is sustainable

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Coping With Change

• up to date equipment and teaching materials
• information resources and appropriate strategies
  for staying current in the field
• cooperative learning and the use of communication
  technologies to promote group interaction
• need for continuing professional development to
  promote lifelong learning

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Principles

• Computing is a broad field that extends well
  beyond the boundaries of computer science.
• Computer science draws its foundations from a
  wide variety of disciplines.
• Development of a computer science curriculum must
  be sensitive to
• changes in technology,
• new developments in pedagogy, and
• the importance of lifelong learning.
• Curricula must include professional practice as
  an integral component.

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Computing Curricula 2001

• December 15, 2001
• Final Report of the Joint ACM/IEEE-CS Task Force
  on Computing Curricula
• joint undertaking of the Computer Society of the
  Institute for Electrical and Electronic Engineers
  (IEEE-CS) and the Association for Computing
  Machinery (ACM)
• Curricular guidelines and set of recommendations
  for undergraduate programs in computing

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IEEE-ACM Computing Curricula 2001

• http//www.computer.org/education/cc2001/final/ind
  ex.htm
• Previous recommendations came out in 1965, 1973,
  1981, 1991, 2001
• Latest December 15, 2001

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ACM-IEEE Computing Curricula
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CS Body of Knowledge
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Pedagogy Focus Groups

• PFG1. Introductory topics and courses
• PFG2. Supporting topics and courses
• PFG3. The computing core
• PFG4. Professional practices
• PFG5. Advanced study and undergraduate research
• PFG6. Computing across the curriculum

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Computing Curricula Topics

• 14 Subject Areas
• 132 topics divided between these 14 subject areas
• 64 out of 132 topics designated as core

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Core vs. Elective

• Core
• Those topics required of all students in all CS
  degree programs
• Minimal, and is not a complete curriculum
• Must be supplemented by additional material
• May be taken as introductory, intermediate, or
  advanced course
• Elective
• Topics that are not part of the core

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Discrete Structures (43 core hrs.)

• DS1. Functions, relations, and sets (6)
• DS2. Basic logic (10)
• DS3. Proof techniques (12)
• DS4. Basics of counting (5)
• DS5. Graphs and trees (4)
• DS6. Discrete probability (6)

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Programming Fundamentals (38)

• PF1. Fundamental programming constructs (9)
• PF2. Algorithms and problem-solving (6)
• PF3. Fundamental data structures (14)
• PF4. Recursion (5)
• PF5. Event-driven programming (4)

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Algorithms Complexity (31)

• AL1. Basic algorithmic analysis (4)
• AL2. Algorithmic strategies (6)
• AL3. Fundamental computing algorithms (12)
• AL4. Distributed algorithms (3)
• AL5. Basic computability (6)

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Architecture Organization (36)

• AR1. Digital logic and digital systems (6)
• AR2. Machine level representation of data (3)
• AR3. Assembly level machine organization (9)
• AR4. Memory system organization and architecture
  (5)
• AR5. Interfacing and communication (3)
• AR6. Functional organization (7)
• AR7. Multiprocessing and alternative
  architectures (3)

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Operating Systems (18)

• OS1. Overview of operating systems (2)
• OS2. Operating system principles (2)
• OS3. Concurrency (6)
• OS4. Scheduling and dispatch (3)
• OS5. Memory management (5)

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Net-Centric Computing (15)

• NC1. Introduction to net-centric computing (2)
• NC2. Communication and networking (7)
• NC3. Network security (3)
• NC4. The web as an example of client-server
  computing (3)

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Programming Languages (21)

• PL1. Overview of programming languages (2)
• PL2. Virtual machines (1)
• PL3. Introduction to language translation (2)
• PL4. Declarations and types (3)
• PL5. Abstraction mechanisms (3)
• PL6. Object-oriented programming (10)

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Human-Computer Interaction (8)

• HC1. Foundations of human-computer interaction
  (6)
• HC2. Building a simple graphical user interface
  (2)

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Graphics Visual Computing (3)

• GV1. Fundamental techniques in graphics (2)
• GV2. Graphic systems (1)

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Intelligent Systems (10)

• IS1. Fundamental issues in intelligent systems
  (1)
• IS2. Search and constraint satisfaction (5)
• IS3. Knowledge representation and reasoning (4)

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Information Management (10)

• IM1. Information models and systems (3)
• IM2. Database systems (3)
• IM3. Data modeling (4)

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Social Prof Issues (16)

• SP1. History of computing (1)
• SP2. Social context of computing (3)
• SP3. Methods and tools of analysis (2)
• SP4. Professional and ethical responsibilities
  (3)
• SP5. Risks and liabilities of computer-based
  systems (2)
• SP6. Intellectual property (3)
• SP7. Privacy and civil liberties (2)

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Software Engineering (31)

• SE1. Software design (8)
• SE2. Using APIs (5)
• SE3. Software tools and environments (3)
• SE4. Software processes (2)
• SE5. Software requirements and specifications (4)
  
• SE6. Software validation (3)
• SE7. Software evolution (3)
• SE8. Software project management (3)

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Implementation Strategies
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Introductory CoursesImplementation Strategies

• Programming first
• Imperative first
• Objects first
• Functional first
• Breadth first
• Algorithms first
• Hardware first

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Required Topics in Introductory Courses

• Functions, relations, and sets
• Basic logic
• Basics of counting
• Discrete probability
• Fundamental programming constructs
• Recursion
• Overview of programming languages
• Virtual machines
• Declarations and types
• Abstraction mechanisms
• History of computing

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Required Topics in Introductory
CoursesFunctions, Relations, and Sets

• Minimum core coverage time 6 hours
• Topics
• Functions (surjections, injections, inverses,
  composition)
• Relations (reflexivity, symmetry, transitivity,
  equivalence relations)
• Sets (Venn diagrams, complements, Cartesian
  products, power sets)
• Pigeonhole principle
• Cardinality and countability
• Learning objectives
• Explain with examples the basic terminology of
  functions, relations, and sets.
• Perform the operations associated with sets,
  functions, and relations.
• Relate practical examples to the appropriate set,
  function, or relation model, and interpret the
  associated operations and terminology in context.
  
• Demonstrate basic counting principles, including
  uses of diagonalization and the pigeonhole
  principle.

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Required Topics in Introductory Courses Basic
Logic

• Minimum core coverage time 10 hours
• Topics
• Propositional logic Logical connectives
• Truth tables
• Normal forms (conjunctive and disjunctive)
• Validity
• Predicate logic Universal and existential
  quantification
• Modus ponens and modus tollens
• Limitations of predicate logic
• Learning objectives
• Apply formal methods of symbolic propositional
  and predicate logic.
• Describe how formal tools of symbolic logic are
  used to model algorithms and real-life
  situations.
• Use formal logic proofs and logical reasoning to
  solve problems such as puzzles.
• Describe the importance and limitations of
  predicate logic.

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Required Topics in Introductory Courses Basic of
Counting

• Minimum core coverage time 5 hours
• Topics
• Counting arguments
• Sum and product rule
• Inclusion-exclusion principle
• Arithmetic and geometric progressions
• Fibonacci numbers
• The pigeonhole principle
• Permutations and combinations
• Basic definitions
• Pascal's identity
• The binomial theorem
• Solving recurrence relations
• Common examples
• The Master theorem

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Required Topics in Introductory Courses Basic of
Counting

• Minimum core coverage time 5 hours
• Learning objectives
• Compute permutations and combinations of a set,
  and interpret the meaning in the context of the
  particular application.
• State the definition of the Master theorem.
• Solve a variety of basic recurrence equations.
• Analyze a problem to create relevant recurrence
  equations or to identify important counting
  questions.

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Required Topics in Introductory Courses Discrete
Probability

• Minimum core coverage time 6 hours
• Topics
• Finite probability space, probability measure,
  events
• Conditional probability, independence, Bayes'
  theorem
• Integer random variables, expectation
• Learning objectives
• Calculate probabilities of events and
  expectations of random variables for elementary
  problems such as games of chance.
• Differentiate between dependent and independent
  events.
• Apply the binomial theorem to independent events
  and Bayes theorem to dependent events.
• Apply the tools of probability to solve problems
  such as the Monte Carlo method, the average case
  analysis of algorithms, and hashing.

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Required Topics in Introductory Courses Discrete
Probability

• Minimum core coverage time 6 hours
• Topics
• Finite probability space, probability measure,
  events
• Conditional probability, independence, Bayes'
  theorem
• Integer random variables, expectation
• Learning objectives
• Calculate probabilities of events and
  expectations of random variables for elementary
  problems such as games of chance.
• Differentiate between dependent and independent
  events.
• Apply the binomial theorem to independent events
  and Bayes theorem to dependent events.
• Apply the tools of probability to solve problems
  such as the Monte Carlo method, the average case
  analysis of algorithms, and hashing.

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Required Topics in Introductory
CoursesFundamental Programming Constructs

• Minimum core coverage time 9 hours
• Topics
• Basic syntax and semantics of a higher-level
  language
• Variables, types, expressions, and assignment
• Simple I/O
• Conditional and iterative control structures
• Functions and parameter passing
• Structured decomposition

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Required Topics in Introductory
CoursesFundamental Programming Constructs

• Learning objectives
• Analyze and explain the behavior of simple
  programs involving the fundamental programming
  constructs covered by this unit.
• Modify and expand short programs that use
  standard conditional and iterative control
  structures and functions.
• Design, implement, test, and debug a program that
  uses each of the following fundamental
  programming constructs basic computation, simple
  I/O, standard conditional and iterative
  structures, and the definition of functions.
• Choose appropriate conditional and iteration
  constructs for a given programming task.
• Apply the techniques of structured (functional)
  decomposition to break a program into smaller
  pieces.
• Describe the mechanics of parameter passing.

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Required Topics in Introductory Courses Recursion

• Minimum core coverage time 5 hours
• Topics
• The concept of recursion
• Recursive mathematical functions
• Simple recursive procedures
• Divide-and-conquer strategies
• Recursive backtracking
• Implementation of recursion

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Required Topics in Introductory Courses Recursion

• Minimum core coverage time 5 hours
• Learning objectives
• Describe the concept of recursion and give
  examples of its use.
• Identify the base case and the general case of a
  recursively defined problem.
• Compare iterative and recursive solutions for
  elementary problems such as factorial.
• Describe the divide-and-conquer approach.
• Implement, test, and debug simple recursive
  functions and procedures.
• Describe how recursion can be implemented using a
  stack.
• Discuss problems for which backtracking is an
  appropriate solution.
• Determine when a recursive solution is
  appropriate for a problem.

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Required Topics in Introductory CoursesOverview
of Programming Languages

• Minimum core coverage time 2 hours
• Topics
• History of programming languages
• Brief survey of programming paradigms
• Procedural languages
• Object-oriented languages
• Functional languages
• Declarative, non-algorithmic languages
• Scripting languages
• The effects of scale on programming methodology

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Required Topics in Introductory CoursesOverview
of Programming Languages

• Minimum core coverage time 2 hours
• Learning objectives
• Summarize the evolution of programming languages
  illustrating how this history has led to the
  paradigms available today.
• Identify at least one distinguishing
  characteristic for each of the programming
  paradigms covered in this unit.
• Evaluate the tradeoffs between the different
  paradigms, considering such issues as space
  efficiency, time efficiency (of both the computer
  and the programmer), safety, and power of
  expression.
• Distinguish between programming-in-the-small and
  programming-in-the-large.

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Required Topics in Introductory Courses Virtual
Machines

• Minimum core coverage time 1 hour
• Topics
• The concept of a virtual machine
• Hierarchy of virtual machines
• Intermediate languages
• Security issues arising from running code on an
  alien machine
• Learning objectives
• Describe the importance and power of abstraction
  in the context of virtual machines.
• Explain the benefits of intermediate languages in
  the compilation process.
• Evaluate the tradeoffs in performance vs.
  portability.
• Explain how executable programs can breach
  computer system security by accessing disk files
  and memory.

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Required Topics in Introductory Courses
Declarations and Types

• Minimum core coverage time 3 hours
• Topics
• The conception of types as a set of values with
  together with a set of operations
• Declaration models (binding, visibility, scope,
  and lifetime)
• Overview of type-checking
• Garbage collection
• Learning objectives
• Explain the value of declaration models,
  especially with respect to programming-in-the-larg
  e.
• Identify and describe the properties of a
  variable such as its associated address, value,
  scope, persistence, and size.
• Discuss type incompatibility.
• Demonstrate different forms of binding,
  visibility, scoping, and lifetime management.
• Defend the importance of types and type-checking
  in providing abstraction and safety.
• Evaluate tradeoffs in lifetime management
  (reference counting vs. garbage collection).

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Required Topics in Introductory Courses
Abstraction Mechanisms

• Minimum core coverage time 3 hours
• Topics
• Procedures, functions, and iterators as
  abstraction mechanisms
• Parameterization mechanisms (reference vs. value)
  
• Activation records and storage management
• Type parameters and parameterized types
• Modules in programming languages
• Learning objectives
• Explain how abstraction mechanisms support the
  creation of reusable software components.
• Demonstrate the difference between call-by-value
  and call-by-reference parameter passing.
• Defend the importance of abstractions, especially
  with respect to programming-in-the-large.
• Describe how the computer system uses activation
  records to manage program modules and their data.

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Required Topics in Introductory Courses History
of computing

• Minimum core coverage time 1 hour
• Topics
• Prehistory -- the world before 1946
• History of computer hardware, software,
  networking
• Pioneers of computing
• Learning objectives
• List the contributions of several pioneers in the
  computing field.
• Compare daily life before and after the advent of
  personal computers and the Internet.
• Identify significant continuing trends in the
  history of the computing field.

66
Other Topics in Introductory Courses

• Proof techniques
• The structure of formal proofs
• proof techniques direct, counterexample,
  contraposition, contradiction mathematical
  induction
• Algorithms and problem-solving
• Problem-solving strategies
• the role of algorithms in the problem-solving
  process
• the concept and properties of algorithms
  debugging strategies

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Other Topics in Introductory Courses

• Fundamental data structures
• Primitive types arrays records
• strings and string processing
• data representation in memory
• static, stack, and heap allocation
• runtime storage management
• pointers and references
• linked structures
• Basic algorithmic analysis
• Big O notation
• standard complexity classes
• empirical measurements of performance
• time and space tradeoffs in algorithms

68
Other Topics in Introductory Courses

• Fundamental computing algorithms
• Simple numerical algorithms
• sequential and binary search algorithms
• quadratic and O(N log N) sorting algorithms
• hashing
• binary search trees
• Digital logic and digital systems
• Logic gates
• logic expressions

69
Other Topics in Introductory Courses

• Object-oriented programming
• Object-oriented design
• encapsulation and information-hiding
• separation of behavior and implementation
• classes, subclasses, and inheritance
• polymorphism
• class hierarchies
• Software design
• Fundamental design concepts and principles
• object-oriented analysis and design
• design for reuse

70
Other Topics in Introductory Courses

• Using APIs
• API programming
• class browsers and related tools
• programming by example
• debugging in the API environment
• Software tools and environments
• Programming environments
• testing tools
• Software requirements and specifications
• Importance of specification in the software
  process
• Software validation
• Testing fundamentals
• test case generation

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Intermediate CoursesGoal

• To present the fundamental ideas and enduring
  concepts of computer science that every student
  must learn to work successfully in the field. In
  doing so, these intermediate courses lay the
  foundation for more advanced work in computer
  science.

72
Intermediate CoursesImplementation Strategies

• Traditional approach in which each course
  addresses a single topic
• Compressed approach that organises courses around
  broader themes
• System-based approach
• Web-based approach that uses networking as its
  organizing principle

73
Intermediate CoursesTopic-Based Approach

• CS210T. Algorithm Design and Analysis
• CS220T. Computer Architecture
• CS225T. Operating Systems
• CS230T. Net-centric Computing
• CS260T. Artificial Intelligence
• CS270T. Databases
• CS280T. Social and Professional Issues
• CS290T. Software Development
• CS490. Capstone Project

74
Intermediate CoursesCompressed Approach

• CS210C. Algorithm Design and Analysis
• CS220C. Computer Architecture
• CS226C. Operating Systems and Networking
• CS262C. Information and Knowledge Management
• CS292C. Software Development and Professional
  Practice

75
Intermediate CoursesSystems-Based Approach

• CS120. Introduction to Computer Organization
• CS210S. Algorithm Design and Analysis
• CS220S. Computer Architecture
• CS226S. Operating Systems and Networking
• CS240S. Programming Language Translation
• CS255S. Computer Graphics
• CS260S. Artificial Intelligence
• CS271S. Information Management
• CS291S. Software Development and Systems
  Programming
• CS490. Capstone Project

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Intermediate CoursesWeb-Based Approach

• CS130. Introduction to the World-Wide Web
• CS210W. Algorithm Design and Analysis
• CS221W. Architecture and Operating Systems
• CS222W. Architectures for Networking and
  Communication
• CS230W. Net-centric Computing
• CS250W. Human-Computer Interaction
• CS255W. Computer Graphics
• CS261W. AI and Information
• CS292W. Software Development and Professional
  Practice

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General Requirements

• Mathematical rigor
• The scientific method
• Familiarity with applications
• Communications skills
• Working in teams
• The complementary curriculum

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Advanced Courses

• Advanced courses courses whose content is
  substantially beyond the material of the core.

79
Sample CurriculaMinimum Requirements

• Cover all 280 hours of core material in the CS
  body of knowledge
• Require sufficient advanced coursework to provide
  depth in at least one area of computer science
• Include an appropriate level of supporting
  mathematics
• Offer students exposure to "real world"
  professional skills such as research experience,
  teamwork, technical writing, and project
  development

80
Thesis vs Final Project

• Thesis is research-oriented
• Thesis must have original contribution to
  knowledge.
• Project is development-oriented
• Project may be software development, information
  systems development, or web application
  development

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ACM Recommendation

• CS390. Capstone Project
• Course Description Offers students the
  opportunity to integrate their knowledge of the
  undergraduate computer science curriculum by
  implementing a significant software system as
  part of a programming team.
• Prerequisites CS261, CS262, or CS360

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ACM Syllabus

• Using APIs
• Human-centered software evaluation
• Human-centered software development
• Graphical user-interface design
• Graphical user-interface programming
• Software requirements and specifications
• Software design
• Software validation
• Software project management
• Software tools and environments
• Effective team management
• Communications skills

83
ACM Approach

• This course is different in flavor and concept
  from most of the earlier courses in the
  curriculum in that it is focused primarily on a
  project.
• There may be lecturesparticularly if the earlier
  courses do not cover the full set of required
  units in the core but the overall idea is that
  students should have a chance to apply all the
  skills they have learned in the curriculum toward
  the completion of a team project.
• Thus, this course has the effect of reinforcing
  concepts that have been learned earlier in a more
  theoretical way.

84
UNESCO Informatics Curriculum Framework 2000 for
Higher Education

• http//www.ifip.or.at/pdf/ICF2001.pdf

85
ACM

• The ACM Computing Classification System 1998
  Version
• http//www.acm.org/class/1998/homepage.html

86
Association for Information Systems

• AIS is actively involved in the development and
  ongoing update of curriculum at both the
  undergraduate and graduate levels.
• IS97 Model Curriculum and Guidelines for
  Undergraduate Degree Programs in Information
  Systems
• http//www.acm.org/education/curricula.htmlIS97
• http//aisnet.org/Curriculum/index.htm

87
Association for Information Systems

• IS 2002 Model Curriculum and Guidelines for
  Undergraduate Degree Programs in Information
  Systems
• IS 2002 is the latest undergraduate model
  curriculum and is the first update of the
  curriculum effort of the AIS, ACM and AITP
  societies since IS'97.
• IS'97 has been widely accepted and has become the
  basis for accreditation of undergraduate programs
  of information systems.
• This report has been endorsed by seven
  organizations including SIM.
• http//aisnet.org/Curriculum/index.htm

88
Association for Information Systems

• MSIS 2000 Model Graduate Curriculum
• MSIS is a Model Curriculum and Guidelines for
  Graduate Degree Programs in Information Systems.
• It was jointly prepared by representatives from
  AIS and ACM.
• http//aisnet.org/Curriculum/index.htm

89
ECDL Foundation

• The European Computer Driving Licence standard of
  competence since 1997
• the ECDL is an internationally recognized
  standard of competence certifying that the holder
  has the knowledge and skills needed to use the
  most common computer applications efficiently and
  productively
• http//www.ecdl.com/

90
National Science Foundation (NSF)

• ISCC99 An Information Systems-Centric
  Curriculum 99. Program Guidelines for Educating
  the Next Generation of Information Systems
  Specialists, in Collaboration with Industry
• http//www.iscc.unomaha.edu/TableOfContents.html

91
IEEE Computer Society/ACMComputing Curriculum -
Computer Engineering

• Computing Curricula Volume on Computer
  Engineering Computer Engineering Body of
  Knowledge http//www.eng.auburn.edu/ece/CCCE/

92
National Science Education Standards

• http//books.nap.edu/html/nses/html/index.html
• outlines what students need to know, understand,
  and be able to do to be scientifically literate
  at different levels.
• describes an educational system in which all
  students demonstrate high levels of performance,
  in which teachers are empowered to make the
  decisions essential for effective learning, in
  which interlocking communities of teachers and
  students are focused on learning science, and in
  which supportive educational programs and systems
  nurture achievement.

93
CHED

• CHED MEMORANDUM ORDER (CMO) NO. 25 Series of
  2001
  
• SUBJECT Revised Policies And Standards For
  Information Technology Education (ITE)
• http//www.ched.gov.ph/policies/CMO2001/CMO_25.doc
  

94
CHED Basic Core Topics

• Basic Non-ITE Core Topics
• Communication skills
• Technical writing / presentation skills
• Algebra /trigonometry
• Values Formation
• Probability / Statistics

95
CHED Basic Core Topics

• Basic ITE Core Topics
• Professional Ethics / Code of Ethics for the
  Filipino IT Professional
• Mathematical Logic / Discrete mathematics
• Problem Solving
• Quality Processes
• Fundamentals of programming / program logic
  formulation
• Introduction to the Internet / Web-based
  programming
• IT Fundamentals
• Computer Systems Organization

96
Implementation Factors and Strategies

• There is no single ideal model curriculum.
• need for a considerable degree of freedom for
  implementation
• account for specific needs, restrictions,
  preconditions and circumstantial opportunities,
  such as
• cultural and societal setting
• institutional size and scope
• specific disciplines and educational programs
  offered by the educational institution
• available budget, personnel and resources
• background and potential of the faculty

97
Implementation Factors and Strategies

• culture among faculty and management
• management commitment to informatics
• willingness to change
• student-body characteristics
• access to informatics expertise in general
• access to collaborative or transfer options with
  other institutes
• access to collaborative or transfer options with
  industry
• level of informatics penetration in the region.

98
Curriculum Review

• review whole curriculum and compare with
  recommendations, guidelines and policies.
• compare curricula with actual teaching practice
• review each syllabi
• identify problems areas
• concentrate faculty development efforts on
  problem areas
• Ensure that introductory courses are taught
  properly
• prioritize core courses over electives