Comprehensive Course Syllabus

Transcription

1 Comprehensive Course Syllabus Computational Thinking Course Description: The course introduces students to the principles of computational thinking. Computational thinking is a way of solving problems, designing systems, developing algorithms, and understanding human behavior that draws on concepts fundamental to computer science. This course explores making use of different levels of abstraction, decomposition, modularization, and recursion to understand and solve problems more effectively. It uses mathematical concepts such as induction, to develop algorithms and produce more efficient, fair, elegant, and secure solutions. The object-oriented language, Python, will be used to demonstrate simple programming concepts. INSTRUCTOR(S): Name(s): Dr. P. Patankar Office Number(s) (When and where you are available for help.): A157 A/C days: 3:00 4:00 pm Telephone number(s): address(es): ppatankar@imsa.edu Meeting Days, Time and Room(s) 2:15 pm 3:25 pm A/C days Room A133 Text(s) / Materials: There is no required text for this course. A number of online resources will be used extensively including w3schools tutorials.

2 Essential Content: Since IMSA has not adopted Computer Science standards yet, we will follow the guidelines of National Educational Technology (NET) standards for students (see ETS_for_Students_2007.htm) : Creativity and Innovation Students demonstrate creative thinking, construct knowledge, and develop innovative products and processes using technology. Students: a. apply existing knowledge to generate new ideas, products, or processes. b. create original works as a means of personal or group expression. c. use models and simulations to explore complex systems and issues. d. identify trends and forecast possibilities. Critical Thinking, Problem Solving, and Decision Making Students use critical thinking skills to plan and conduct research, manage projects, solve problems, and make informed decisions using appropriate digital tools and resources. Students: a. identify and define authentic problems and significant questions for investigation. b. plan and manage activities to develop a solution or complete a project. c. collect and analyze data to identify solutions and/or make informed decisions. d. use multiple processes and diverse perspectives to explore alternative solutions. Digital Citizenship Students understand human, cultural, and societal issues related to technology and practice legal and ethical behavior. Students: a. advocate and practice safe, legal, and responsible use of information and technology. b. exhibit a positive attitude toward using technology that supports collaboration, learning, and productivity. c. demonstrate personal responsibility for lifelong learning. d. exhibit leadership for digital citizenship.

3 Technology Operations and Concepts Students demonstrate a sound understanding of technology concepts, systems, and operations. Students: a. understand and use technology systems. b. select and use applications effectively and productively. c. troubleshoot systems and applications. d. transfer current knowledge to learning of new technologies. SSLs and Outcomes: I. Developing the Tools of Thought IA, IB, IC, ID II. Thinking about Thinking IIB III. Extending and Integrating Thought IIIA, IIIB V. Thinking and Acting with others VA, VB Instructional Design and Approach: Students will be asked to think about computational thinking. They will have to identify how they are using computational thinking in other disciplines and how would they use this skill to write algorithms. Experts, in the field of computational thinking, will give students first hand introduction to this topic via coolhub. Problem solving skills will be emphasized through out the course. Students will then be introduced to Python, an easy to learn object oriented programming language, which can demonstrate the power of computing using computers. Students will have an opportunity to see their algorithms in action after they write simple code using Python. All students are expected to be involved in class discussions and explorations, both large and small group. attend all the classes and be on time. complete all daily assignments, labs, and projects in a timely manner. take responsibility for learning certain basic skills and relationships. take responsibility for seeking additional help as it is needed. collaborate with each other and contribute to each other s learning follow the guidelines of Students Handbook about ethical behavior and plagiarism. Assessment Practices, Procedures, and Processes: 1 st Quarter 2 nd Quarter Exercises/Labs: 20% 20% Participation/Organization: 5% 5% Quizzes/Exams: 45% 45%

4 Projects/Assignments 30% 30% Weights of components of the semester grade: 3rd Quarter 45% 4th Quarter 45% Final Project/exam/paper 10% Sequence of Topics and Activities: The following is subject to alteration at the discretion of the instructor. Week Topics Covered About the course/go through syllabus. What is Computational thinking (CT)? Discussion of students understanding of CT Examples and articles about CT How do we Integrate computer science concepts into scientific Discovery? Use of computer science mental tools like Abstraction, decomposition, modularization, and recursion to develop algorithms and solutions model scientific processes simulate complex systems Study a given problem (Example) Analyze and abstract the problem Design an effective solution to the problem Develop an algorithm for the solution Summarize the process How CT is implemented in various disciplines COOLHUB assistance for video conferencing about CT Guest speaker from Science or Humanities to demonstrate CT?? Are there problems that have no algorithms? Are there functions that are not computable? Deciding what is computable and what is not. Introduction to Python and its extensive libraries. Why Python? Download Python Python tutorials and examples. Write a simple program Variables and constants in Python Introduction to Functions

5 Developing and implementing solution for a scientific problem Designing a solution using recursion Designing a solution using Iteration Recursion Vs. Iteration Computer science and who Needs CS? Chemists: to predict protein behaviors for drug development. Biologists: to genetically classify species all the way back to the dinosaurs. Economists: to predict the effects of pricing, market trades, and interest rates. Astronomers: to build models of our galaxy and beyond. Geologists: to predict earthquakes and model the earth's structure millions of years ago. More examples.. Computational thinking and computer science Introduction to VPython Connecting computational thinking to visual 3D Graphing and plotting More Python syntax Arrays and Loops Writing a program, executing the program, making it efficient Connecting computational thinking to the programming concepts Math Problem Design a solution and develop an algorithm Transforming the algorithm into a simple program Implement the program and go through the process of debugging Brainstorming Science, Humanities examples Designing solutions and developing algorithms Are they computable? Develop a project using Alice Basic features of Alice Demonstrating computational thinking using Alice project 15 Project presentations

6 16 Course wrap up, final projects/exam