computational thinking for problem solving university of pennsylvania

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Experiences in applied computational thinking, penn gse certificate, you are here, earn your certificate online: learn to incorporate coding, computational thinking, and basic programming in your pedagogy .  .

The certificate program in Experiences in Applied Computational Thinking (EXACT) prepares K-12 educators to implement computational thinking in their teaching and learning spaces. Designed for beginners, this program helps teachers develop their own computational thinking and coding skills as well as those of their students. This certificate is a 30-week part-time program geared toward working professionals.

What Sets Us Apart

About the program.

The Experiences in Applied Computational Thinking (EXACT) program is an online certificate program that provides an introduction to computational thinking and coding for educators who have no prior experience with coding or computing in K-12 classrooms. 

Cost $6660 ($3330 per semester)

Certificate/Licensure offered

• Penn GSE Certificate in Applied Computational Thinking
• Pennsylvania Act 48 credits

Professional development Equivalent of 12 Continuing Education credits

• Certificate

The Experiences in Applied Computational Thinking (EXACT) certificate program is designed by  Penn GSE and Penn Engineering’s renowned  GRASP Lab  to provide educators with an understanding of computational thinking through experiential learning using current theory and practice in the field of computer science. 

We welcome beginners to the program — beginners who would like to incorporate computational thinking in their pedagogy. Computational thinking can enhance students’ problem-solving skills, empowering them to become confident and successful problem solvers in an increasingly complex world. With this program, educators come to understand computational thinking, re-examine how computational thinking can fit into their current lessons, and become part of a community and professional learning network.

EXACT’s program of study develops teacher expertise in computational concepts (coding concepts such as loops, sequences, data), computational practices (problem solving practices that occur in coding such as debugging, reusing, remixing), and computational perspectives (understanding of themselves and their relation to a digital world around them). The program also introduces cutting-edge applications of computers in real-world contexts, such as natural language processing, computer vision, and robotics.

Specifically geared toward educators who have no prior experience with coding or computing in K-12 classrooms, the EXACT program will:

• Help you develop computational thinking skills and basic programming skills
• Serve as a starting point to advanced computer science education courses
• Encourage coding and computational thinking within the K-12 classroom environment.

Program of Study

The program modules follow the sequence below.

EDCE 588 and 589: Introduction to Computational Thinking 

Participants begin the course by understanding the need for computational thinking in the 21st century classroom, and exploring ways in which it can be made explicit in their teaching spaces. Through an introductory coding platform, participants build introductory level computer science skills and explore the basics of coding languages. This develops the thinking skills and language around coding, such as variables, loops, and conditional statements.

EDCE 590 and 591: Introduction to Python and Machine Learning

In these modules, participants will be introduced to programming in Python, and will learn to program the Raspberry Pi. They will need to solve computational thinking problems using computer hardware, peripherals, and machine learning in a guided learning experience.  

EDCE 592 and 593: Project-based Computational Thinking

Building on previous modules, participants use applications such as natural language processing or computer vision to solve a relevant problem. It culminates with an immersive project designed to apply computational thinking processes in a real-world scenario. The final project of the program requires teachers to work collaboratively to create a lesson plan or an extended curriculum that incorporates computational thinking in their subject areas.

*Note: Penn GSE Certificates are awarded as a standalone, non-credit bearing education credential.

Our Faculty

Betty Chandy Director for Online Learning, Catalyst @ Penn GSE Ed.D., University of Pennsylvania

Veena Vasudevan Postdoctoral Fellow, American Museum of Natural History Ph.D., University of Pennsylvania

Shamya Karubaiah Doctoral student, University of Pennsylvania

Our Graduates

The Experiences in Applied Computational Thinking certificate program helps promote:

• Educators who understand the need for computational thinking in the 21st century classroom
• Educators who are comfortable using computational thinking to solve problems and applying computational thinking to real-world scenarios
• Educators who are prepared to incorporate computational thinking into their subject areas

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A center for global education innovation, Catalyst @ Penn GSE connects people and ideas to develop new ways to advance education in novel and meaningful directions.

Collaboratory for Teacher Education

The Collaboratory for Teacher Education at Penn GSE is a laboratory for the design, implementation, and study of experimental approaches to teacher education.

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Jacquie Panto

Email: [email protected]

Computational Thinking for Problem Solving

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What people are saying.

According to other learners, here's what you need to know

computational thinking in 31 reviews

An in-depth theoretical and practical coverage of the four pillars of computational thinking.

Lots of video and very good explanation of computer science concept and practical problems involving python I learned the methods to solve the problem with computational thinking and the course is really great.

A wonderful program; which seems to have re-ignited a lost fondness for programming The course is very well-designed and it helped me develop understand how to apply computational thinking in solving various types of problems as well as acquire basic skills of programming in Python.

I recommend it for people who are interested in learning the basics of computational thinking, i.e.

An amazing course that teach the way of computational thinking behind our works of programming.

Well Presented Course I loved this course on computational thinking.

Unlike other courses which focused only on a specific programming language (such as Python), this course gave me a deep dive into computational thinking, a foundation learning, behind any types of programming.

Not having a computer science background, but having done some Python experience, I lacked the basic concepts of computational thinking.

It covered pillars of computational thinking, simple algorithms, flowcharts, pseudocode, memory usage in CPU as it relates to programming concepts, and introduction to Python.

Thank you very much for coming up with the idea of creating Computational Thinking course and the degree for people with non-Computer Science background!

Great course, I really enjoyed learning about computational thinking for solving problem and especially, learning Python is fun!

Best computational thinking course and introduction to python that I've ever come across.

To think what a difference just a few weeks can make... thank you for awakening a desire in us propelling us forward into the world as computational thinking evangelists!

Computational Thinking for Problem Solving is one of the best courses I have taken thus far on Coursera.

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If you are new to computer science or need a refresher of the basic concepts you learned in high school / college, this is the perfect course The course offers me a taste of computer science.

Thank you very much for introducing me to the world of Computer Science!

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An excellent bridge into introductory computer science topics.

Professors Susan Davidson and Chris Murphy exposed learners to computer science concepts within everyday problems.

It the best in Computational Thinking, you can also consider as good Introduction to Computer Sciences.

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I was able to understand steps to take before solving problems using code.Thank you This course is extremely helpful for understanding the basics knowledge and skills about computer science.

It was a perfect introduction to computer science and basic programming.

Recommended for anyone interested in learning more about Computer Science and how computers can help us solve problems.

highly recommend in 14 reviews

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Overall, this was a fun, informative, and motivating course that I would HIGHLY recommend to everyone!

Highly Recommended Amazing!

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Highly recommended, I learnt lots.

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I highly recommend this to anyone who is interested in getting started with computer science or computer programming.

Highly recommend for anyone who wants to have some basic understanding of computing:-) The instructors explains the concepts of programming very well.

I would highly recommend this fo anyone.

Highly recommended.

very well in 12 reviews

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Great course for introduction to computer science.

problem solving in 8 reviews

As a programmer by trade these are my thoughts...Week 1 (Problem Solving) - Good for beginners (and scatter brained intermediates).Week 2 (Algorithms) - This was interesting and professionally useful.

By studying the course, I can improve my problem solving skills by adopting a structured method.

Value, conherence content, life-long skill for problem solving.

The teachings that i experience here is way too different from Indian online education system .Coursera is more developed and skill enhancer to the one who is beginner and want to learn with minimum pressure in a different way.Thanks to Coursera (Computational Thinking for problem solving).

This class provides an approach to problem solving that everyone should learn.

Excellent foundational knowledge for problem solving, especially as it pertains to computer science, while not limited to it.

really great in 6 reviews

Really great course.

Really great course in terms of usefulness of material, the way it is presented, and resources available for support.

Really great beginner course for anyone looking to understand CS / programming fundamentals.

Great course Really great course.

think about in 4 reviews

Good start to computer programming and python Well formulated course Great Introduction to thinking about how to think about and structure basic coding structures like loops.

Great for students that think about teaching programming in the future and solve difficult problems.

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how to think about problems using algorithms.

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Computational Thinking for Problem Solving at Penn

Learn to approach problems systematically with the help of computational thinking skills gained from the Computational Thinking for Problem Solving online cours

Quick Facts

Course overview.

Computational Thinking for Problem Solving is a beginner-level course administered by the University of Pennsylvania. The online programme will provide the learners with a deep insight into computational thinking which is used to deal with a problem in a systematic manner and come up with solutions that could be initiated by a computer. Computational Thinking for Problem Solving Certification Syllabus will guide the learners on computation thinking, the development and analysis of algorithms etc that will enable the students to approach the problems from the perspective of computer scientists. 

Offered by Coursera , the Computational Thinking for Problem Solving Certification Course is a programme targeted at beginner-level audiences that could be completed within 17 hours. Computational Thinking for Problem Solving Certification by Coursera is developed by Susan Davidson who is the Weiss Professor at the University of Pennsylvania. 

The Highlights

• Provided by Coursera
• Approximately 17 hours of programme
• Offered by the University of Pennsylvania
• Flexible Deadlines
• Self-Paced Learning Option
• Shareable Certificate
• Financial Aid Available
• Beginner level course 
• 100% Online Course

Programme Offerings

Courses and certificate fees.

The Computational Thinking for Problem Solving Certification Fee will vary depending on how months the learners want to learn the programme. The fee structure is tabulated below: 

Eligibility Criteria

Certification Qualifying Details

The Computational Thinking for Problem Solving Certification will be conferred to the students only if they complete the course proceedings successfully by covering the course readings, videos, assignments and quizzes and paying the Coursera-specified fee. 

What you will learn

After the completion of the  Computational Thinking for Problem Solving Training, the students will be able to make a thorough understanding of the following: 

• Simple Algorithm
• Python Programming
• Problem-Solving
• Computation

Who it is for

Computational Thinking for Problem Solving Classes can be pursued by the professionals such as 

• Python Programmer
• Computer Scientist

Admission Details

Step 1- At first, register and sign in on  https://www.coursera.org/.

Step 2 - Then, find the course ‘Computational Thinking for Problem Solving’ offered by the University of Pennsylvania will appear on the screen. 

Step 3- Kickstart the course by entering the option ‘Enrol’. 

The Syllabus

• Introduction
• Decomposition
• Pattern Recognition
• Data Representation and Abstraction
• Case Studies

Practical exercise

• Finding the Largest Value
• Linear Search
• Algorithmic Complexity
• Binary Search
• Brute Force Algorithms
• Greedy Algorithms
• Binary Search1
• A History of the Computer
• Intro to the von Neumann Architecture
• von Neumann Architecture Data
• von Neumann Architecture Control Flow
• Expressing Algorithms in Pseudocode 
• Expressing Algorithms in Pseudocode
• Introduction to Python
• Conditional Statements
• Classes and Objects
• Course Conclusion
• Programming on the Coursera Platform
• Python Playground
• Variables Programming Activity
• Solution to Variables Programming Activity
• Conditionals Programming Activity
• Solution to Conditionals Programming Activity
• Solution to Lists Programming Assignment
• Solution to Loops Programming Assignment
• Solution to Functions Programming Assignment
• Solution to Challenge Programming Assignment
• Solution to Classes and Objects Programming Assignment
• Solution to Project Part 4
• Programming Assignment
• Loops Programming Assignment
• Functions Programming Assignment
• (Optional) Challenge Programming Assignment
• Classes and Objects Programming Assignment
• Project Part 4: Implementing the Solution in Python

Instructors

Penn frequently asked questions (faq's).

The University of Pennsylvania is offering the programme.

The course is instructed by Susan Davidson who is the Weiss Professor at Computer & Information Science.

Yes, the subtitle is available in the languages of  Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, and Spanish. 

Yes, the students can make the payment of the course fee in installments. 

No, Coursera does not provide job assistance.

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Computational Thinking for Problem Solving

Description.

Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don’t need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact.

In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program.

This course will introduce you to people from diverse professions who use computational thinking to solve problems. You will engage with a unique community of analytical thinkers and be encouraged to consider how you can make a positive social impact through computational thinking.

Price: Enroll For Free!

Language: English

Subtitles : English

Computational Thinking for Problem Solving – University of Pennsylvania

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Coursera Computational Thinking for Problem Solving

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Folders and files, repository files navigation, coursera course at:.

• [Course URL] ( https://www.coursera.org/learn/computational-thinking-problem-solving/home/welcome )

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• Week4_Solutions.py: python solutions to week 4 challenges
• Course_Notes.txt: summary of the course
• Python 100.0%

Computational Thinking for Problem Solving

Computational Thinking for Problem Solving by University of Pennsylvania

Computational Thinking for Problem Solving free videos and free material uploaded by University of Pennsylvania Staff .

Pillars of Computational Thinking

Computational thinking is an approach to solving problems using concepts and ideas from computer science, and expressing solutions to those problems so that they can be run on a computer. As computing becomes more and more prevalent in all aspects of modern society -- not just in software development and engineering, but in business, the humanities, and even everyday life -- understanding how to use computational thinking to solve real-world problems is a key skill in the 21st century. Computational thinking is built on four pillars: decomposition, pattern recognition, data representation and abstraction, and algorithms. This module introduces you to the four pillars of computational thinking and shows how they can be applied as part of the problem solving process.

Expressing and Analyzing Algorithms

When we use computational thinking to solve a problem, what we’re really doing is developing an algorithm: a step-by-step series of instructions. Whether it’s a small task like scheduling meetings, or a large task like mapping the planet, the ability to develop and describe algorithms is crucial to the problem-solving process based on computational thinking. This module will introduce you to some common algorithms, as well as some general approaches to developing algorithms yourself. These approaches will be useful when you're looking not just for any answer to a problem, but the best answer. After completing this module, you will be able to evaluate an algorithm and analyze how its performance is affected by the size of the input so that you can choose the best algorithm for the problem you’re trying to solve.

Fundamental Operations of a Modern Computer

Computational thinking is a problem-solving process in which the last step is expressing the solution so that it can be executed on a computer. However, before we are able to write a program to implement an algorithm, we must understand what the computer is capable of doing -- in particular, how it executes instructions and how it uses data. This module describes the inner workings of a modern computer and its fundamental operations. Then it introduces you to a way of expressing algorithms known as pseudocode, which will help you implement your solution using a programming language.

Applied Computational Thinking Using Python

Writing a program is the last step of the computational thinking process. It’s the act of expressing an algorithm using a syntax that the computer can understand. This module introduces you to the Python programming language and its core features. Even if you have never written a program before -- or never even considered it -- after completing this module, you will be able to write simple Python programs that allow you to express your algorithms to a computer as part of a problem-solving process based on computational thinking.

Computational thinking is the process of approaching a problem in a systematic manner and creating and expressing a solution such that it can be carried out by a computer. But you don't need to be a computer scientist to think like a computer scientist! In fact, we encourage students from any field of study to take this course. Many quantitative and data-centric problems can be solved using computational thinking and an understanding of computational thinking will give you a foundation for solving problems that have real-world, social impact. In this course, you will learn about the pillars of computational thinking, how computer scientists develop and analyze algorithms, and how solutions can be realized on a computer using the Python programming language. By the end of the course, you will be able to develop an algorithm and express it to the computer by writing a simple Python program. This course will introduce you to people from diverse professions who use computational thinking to solve problems. You will engage with a unique community of analytical thinkers and be encouraged to consider how you can make a positive social impact through computational thinking.

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