Course Evaluation and Grading
Evaluation Criteria Table
The final grades will be based on the following categories:
CATEGORY WEIGHT
Labs 30%
Assignments 15%
Unit Exam 1 15%
Unit Exam 2 10%
Unit Exam 3 15%
Lab Practicum 15%
Total 100%
Tuesday, December 9, 2008
IT104 Syllabus
Introduction to Computer Programming
Instructor:Mario Perez
Office hours: TBA
Class hours: Tuesday 6:00 PM - 10:20 PM
Course Description
This course serves as a foundation for understanding the logical function and process of
computer programming in a given language environment. Basic computer programming
knowledge and skills in logic and syntax will be covered. Coding convention and
procedures will be discussed relevant to the given programming language environment.
Major Instructional Areas
1. Fundamental concepts of computer programming
2. Memory allocation and variables
3. Problem specification and analysis using flowcharting and pseudocode
4. Conditional statements and repetition structures
5. Coding conventions and procedures
Course Objectives
1. Describe the fundamental concepts in computer programming.
2. Create basic software program designs.
3. Create various modules in computer programs.
4. Create various functions in computer programs.
5. Create computer programs that can make decisions.
6. Create computer programs that can do repetitive processing.
7. Create computer programs that can do input validation.
8. Create program software that incorporates modules (and/or functions), conditional
logic, looping, and input validation.
9. Test program software.
SCANS Objectives
SCANS is an acronym for Secretary’s Commission on Achieving Necessary Skills. The
committee, created by the National Secretary of Labor in the early 1990s, created a list of
skills and competencies that the committee feels are necessary for employees to function
in a high-tech job market.
1. Identify relevant facts and analyze information in a logical manner after locating and
verifying information using resources and computers.
2. Identify common goals and examine all possible options for problem solving.
3. Identify problems, create and implement solutions, and revise solutions, as required.
4. Allocate time and energy for completing projects in a timely manner.
5. Exert a high level of effort and perseverance toward attaining goals.
6. Recognize problems and devise and implement a plan of action.
7. Demonstrate the ability to utilize authentic resources available, including the Internet,
knowledge libraries, or other sources.
8. Locate, understand, and interpret information obtained from a variety of sources.
9. Identify the need for data; select, retrieve, and analyze information; and communicate
the results of information analysis in written, graphical, and pictorial formats.
10. Compare and contrast two theories or alternatives to arrive at the best solution.
11. Apply procedures, tools, and equipment—including computers and related
technologies—whenever required.
12. Evaluate alternatives and choose the best for a situation.
Instructional Methods
The curriculum is designed to promote a variety of teaching strategies that support the
outcomes described in the course objectives and that foster higher cognitive skills.
Delivery makes use of various media and delivery tools in the classroom.
Multiple styles, such as lectures, collaborative learning options, and hands-on laboratory
activities, will be used to deliver content and inspire and engage students. Your progress
will be regularly assessed using various accessible methods and tools. This course uses
various learning strategies such as exams, assignments, lab exercises, and a lab practicum
Introduction to Computer Programming Syllabus to help you understand the concepts. Assignments are based on the concepts covered in different units. Units 4, 6, and 11 each have an exam. These exams will analyze your learning and help you recall the concepts already taught.
Classroom practices will create a climate of high values with respect to both diversity and
inclusiveness. An open communication environment will help to ensure useful
interactions between students and the instructor and among students themselves. Lesson
plans, course materials, notes, or other information resources will be made available and
be made flexible to all students as needed.
Instructional Materials and References
Student Textbook Package
• Gaddis, Tony. Starting Out with Programming Logic & Design. Custom Edition.
Indianapolis: Pearson Custom Publishing, 2008.
• Gaddis, Tony. Lab Manual to Accompany Starting Out with Programming Logic &
Design. Indianapolis: Pearson Custom Publishing, 2008.
• Python/Raptor software CD (included with textbook)
References
ITT Tech Virtual Library
Log on to the ITT Tech Virtual Library at http://www.library.itt-tech.edu/ to
access online books, journals, and other reference resources selected to support
ITT Tech curricula.
Books
You may click “Books” or use the “Search” function on the home page to
find the following books.
ITT Tech Virtual Library> Main Menu> Books> Books24x7>
• Dawson, Michael. Python Programming for the Absolute Beginner.
Boston: Premier Press, 2003.
• Goodliffe, Peter. Code Craft: The Practice of Writing Excellent Code.
San Francisco: No Starch Press, 2007.
• Hetland, Magnus Lie. Practical Python. Berkeley, CA: Apress, 2002.
• Shasha, Dennis E. Puzzles for Programmers and Pros. Indianapolis:
Wiley Publishing, Inc., 2007.
Other References
The following resources may be found outside of the ITT Tech Virtual Library,
whether online or in hard copy.
Web sites
• Algorithms
http://courses.cs.vt.edu/~csonline/Algorithms/Lessons/index.html
Self-paced lessons on understanding and using algorithms
• Number Systems
http://courses.cs.vt.edu/~csonline/NumberSystems/Lessons/index.html
Self-paced lessons on understanding and using number systems,
including binary, hexadecimal, and octal
• Programming Languages
http://courses.cs.vt.edu/~csonline/ProgrammingLanguages/Lessons/in
dex.html
Self-paced lessons on understanding and using various programming
languages
• Programming Tutorials
http://www.programmingtutorials.com/python.aspx
A collection of links to online tutorials available on Python software
• Python
http://www.python.org
The official Web site of the Python Software Foundation, with news,
documentation, and downloads
Books
• Downey, Allen B., Jeffrey Elkner, and Chris Meyers. How to Think
Like a Computer Scientist: Learning with Python. Needham, MA:
Green Tea Press, 2002.
Available on FreeTechBooks.com:
http://freetechbooks.com/about134.html&highlight=allen+downey
This downloadable book teaches readers to think like a computer
scientist regarding the use of Python.
All links to Web references outside of the ITT Tech Virtual Library are always
subject to change without prior notice.
Course Evaluation and Grading
Evaluation Criteria Table
The final grades will be based on the following categories:
CATEGORY WEIGHT
Labs 30%
Assignments 15%
Unit Exam 1 15%
Unit Exam 2 10%
Unit Exam 3 15%
Lab Practicum 15%
Total 100%
Note: Students are responsible for abiding by the Plagiarism Policy.
Grade Conversion Table
The final grades will be calculated from the percentages earned in the course, as follows:
A 90–100% 4.0
B+ 85–89% 3.5
B 80–84% 3.0
C+ 75–79% 2.5
C 70–74% 2.0
D+ 65–69% 1.5
D 60–64% 1.0
F <60% 0.0
© ITT Educational Services, Inc. Date: 09/30/08
Instructor:Mario Perez
Office hours: TBA
Class hours: Tuesday 6:00 PM - 10:20 PM
Course Description
This course serves as a foundation for understanding the logical function and process of
computer programming in a given language environment. Basic computer programming
knowledge and skills in logic and syntax will be covered. Coding convention and
procedures will be discussed relevant to the given programming language environment.
Major Instructional Areas
1. Fundamental concepts of computer programming
2. Memory allocation and variables
3. Problem specification and analysis using flowcharting and pseudocode
4. Conditional statements and repetition structures
5. Coding conventions and procedures
Course Objectives
1. Describe the fundamental concepts in computer programming.
2. Create basic software program designs.
3. Create various modules in computer programs.
4. Create various functions in computer programs.
5. Create computer programs that can make decisions.
6. Create computer programs that can do repetitive processing.
7. Create computer programs that can do input validation.
8. Create program software that incorporates modules (and/or functions), conditional
logic, looping, and input validation.
9. Test program software.
SCANS Objectives
SCANS is an acronym for Secretary’s Commission on Achieving Necessary Skills. The
committee, created by the National Secretary of Labor in the early 1990s, created a list of
skills and competencies that the committee feels are necessary for employees to function
in a high-tech job market.
1. Identify relevant facts and analyze information in a logical manner after locating and
verifying information using resources and computers.
2. Identify common goals and examine all possible options for problem solving.
3. Identify problems, create and implement solutions, and revise solutions, as required.
4. Allocate time and energy for completing projects in a timely manner.
5. Exert a high level of effort and perseverance toward attaining goals.
6. Recognize problems and devise and implement a plan of action.
7. Demonstrate the ability to utilize authentic resources available, including the Internet,
knowledge libraries, or other sources.
8. Locate, understand, and interpret information obtained from a variety of sources.
9. Identify the need for data; select, retrieve, and analyze information; and communicate
the results of information analysis in written, graphical, and pictorial formats.
10. Compare and contrast two theories or alternatives to arrive at the best solution.
11. Apply procedures, tools, and equipment—including computers and related
technologies—whenever required.
12. Evaluate alternatives and choose the best for a situation.
Instructional Methods
The curriculum is designed to promote a variety of teaching strategies that support the
outcomes described in the course objectives and that foster higher cognitive skills.
Delivery makes use of various media and delivery tools in the classroom.
Multiple styles, such as lectures, collaborative learning options, and hands-on laboratory
activities, will be used to deliver content and inspire and engage students. Your progress
will be regularly assessed using various accessible methods and tools. This course uses
various learning strategies such as exams, assignments, lab exercises, and a lab practicum
Introduction to Computer Programming Syllabus to help you understand the concepts. Assignments are based on the concepts covered in different units. Units 4, 6, and 11 each have an exam. These exams will analyze your learning and help you recall the concepts already taught.
Classroom practices will create a climate of high values with respect to both diversity and
inclusiveness. An open communication environment will help to ensure useful
interactions between students and the instructor and among students themselves. Lesson
plans, course materials, notes, or other information resources will be made available and
be made flexible to all students as needed.
Instructional Materials and References
Student Textbook Package
• Gaddis, Tony. Starting Out with Programming Logic & Design. Custom Edition.
Indianapolis: Pearson Custom Publishing, 2008.
• Gaddis, Tony. Lab Manual to Accompany Starting Out with Programming Logic &
Design. Indianapolis: Pearson Custom Publishing, 2008.
• Python/Raptor software CD (included with textbook)
References
ITT Tech Virtual Library
Log on to the ITT Tech Virtual Library at http://www.library.itt-tech.edu/ to
access online books, journals, and other reference resources selected to support
ITT Tech curricula.
Books
You may click “Books” or use the “Search” function on the home page to
find the following books.
ITT Tech Virtual Library> Main Menu> Books> Books24x7>
• Dawson, Michael. Python Programming for the Absolute Beginner.
Boston: Premier Press, 2003.
• Goodliffe, Peter. Code Craft: The Practice of Writing Excellent Code.
San Francisco: No Starch Press, 2007.
• Hetland, Magnus Lie. Practical Python. Berkeley, CA: Apress, 2002.
• Shasha, Dennis E. Puzzles for Programmers and Pros. Indianapolis:
Wiley Publishing, Inc., 2007.
Other References
The following resources may be found outside of the ITT Tech Virtual Library,
whether online or in hard copy.
Web sites
• Algorithms
http://courses.cs.vt.edu/~csonline/Algorithms/Lessons/index.html
Self-paced lessons on understanding and using algorithms
• Number Systems
http://courses.cs.vt.edu/~csonline/NumberSystems/Lessons/index.html
Self-paced lessons on understanding and using number systems,
including binary, hexadecimal, and octal
• Programming Languages
http://courses.cs.vt.edu/~csonline/ProgrammingLanguages/Lessons/in
dex.html
Self-paced lessons on understanding and using various programming
languages
• Programming Tutorials
http://www.programmingtutorials.com/python.aspx
A collection of links to online tutorials available on Python software
• Python
http://www.python.org
The official Web site of the Python Software Foundation, with news,
documentation, and downloads
Books
• Downey, Allen B., Jeffrey Elkner, and Chris Meyers. How to Think
Like a Computer Scientist: Learning with Python. Needham, MA:
Green Tea Press, 2002.
Available on FreeTechBooks.com:
http://freetechbooks.com/about134.html&highlight=allen+downey
This downloadable book teaches readers to think like a computer
scientist regarding the use of Python.
All links to Web references outside of the ITT Tech Virtual Library are always
subject to change without prior notice.
Course Evaluation and Grading
Evaluation Criteria Table
The final grades will be based on the following categories:
CATEGORY WEIGHT
Labs 30%
Assignments 15%
Unit Exam 1 15%
Unit Exam 2 10%
Unit Exam 3 15%
Lab Practicum 15%
Total 100%
Note: Students are responsible for abiding by the Plagiarism Policy.
Grade Conversion Table
The final grades will be calculated from the percentages earned in the course, as follows:
A 90–100% 4.0
B+ 85–89% 3.5
B 80–84% 3.0
C+ 75–79% 2.5
C 70–74% 2.0
D+ 65–69% 1.5
D 60–64% 1.0
F <60% 0.0
© ITT Educational Services, Inc. Date: 09/30/08
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