EdX

Teach computing: moving from Scratch to Python (edX)

Teach computing: moving from Scratch to Python (edX)

Support learners to use the thinking & programming skills they learnt in Scratch in the text-based programming language Python. Block-based programming languages like Scratch make it simple to learn and teach programming. But once your students have mastered it, it's time to move on to a text-based programming language such as Python. This online course will show you how.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

You’ll discover how to transfer the programming and thinking skills learnt while using Scratch to Python. You’ll look at how to help your learners develop basic text-based programming skills, understand error messages and debug code.
The course will show you the power of text-based programming and give you the tools to support your students' transition.

What you'll learn
Over the next four weeks, you will:

  • Think about why it is worth moving from a block-based programming language to a text-based programming language
  • Compare the syntax of Scratch and Python, and turn Scratch programs into Python programs
  • Consider the challenges of introducing Python in your classroom, including the different types of errors that can occur, and explore how you can support your learners to create text-based programs
  • Explore how Python's built-in functions and standard libraries can make writing programs easier
  • Create an action plan for helping your students transition to a text-based language

Syllabus

You will cover:

  • Tools to support children’s transition from block-based to text-based programming
  • Programming and thinking skills in Scratch
  • Basic skills in the Python programming language
  • Simple error messages in Python syntax, and how to debug code
  • Understanding the power of text-based programming and what you can create with it
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Programming for Data Science (edX) EdX
University of Adelaide,AdelaideX

Programming for Data Science (edX)

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems. There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area. Using practical activities you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

Self Paced
Self-Paced
Python Data Structures (edX) EdX
University of Michigan,MichiganX

Python Data Structures (edX)

The second course in Python for Everybody explores variables that contain collections of data like string, lists, dictionaries, and tuples. Learning how to store and represent and manipulate data collections while a program is running is an important part of learning how to program.

Self Paced
Self-Paced
Probability and Statistics in Data Science using Python (edX) EdX
University of California, San Diego,UC San DiegoX

Probability and Statistics in Data Science using Python (edX)

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. The job of a data scientist is to glean knowledge from complex and noisy datasets. Reasoning about uncertainty is inherent in the analysis of noisy data. Probability and Statistics provide the mathematical foundation for such reasoning.

Self Paced
Self-Paced
CS50's Introduction to Computer Science (edX) EdX
HarvardX,Harvard University

CS50's Introduction to Computer Science (edX)

An introduction to the intellectual enterprises of computer science and the art of programming. This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming experience. An entry-level course taught by David J. Malan, CS50 teaches students how to think algorithmically and solve problems efficiently.

Self Paced
Self-Paced
Computing in Python I: Fundamentals and Procedural Programming (edX) EdX
Georgia Institute of Technology,GTx

Computing in Python I: Fundamentals and Procedural Programming (edX)

Learn the fundamentals of computing in Python, including variables, operators, and writing and debugging your own programs. This course starts from the beginning, covering the basics of how a computer interprets lines of code; how to write programs, evaluate their output, and revise the code itself; how to work with variables and their changing values; and how to use mathematical, boolean, and relational operators.

Self Paced
Self-Paced
Introduction to Java Programming: Starting to code in Java (edX) EdX
Universidad Carlos III de Madrid - UC3M,UC3Mx

Introduction to Java Programming: Starting to code in Java (edX)

Learn to program with Java in an easy and interactive way! In this introductory Java programming course, you will be introduced to powerful concepts such as functional abstraction, the object oriented programming (OOP) paradigm and Application Programming Interfaces (APIs). Examples and case studies will be provided so that you can implement simple programs on your own or collaborate with peers.

Self Paced
Self-Paced
Advanced Linear Algebra: Foundations to Frontiers (edX) EdX
University of Texas at Austin,UTAustinX

Advanced Linear Algebra: Foundations to Frontiers (edX)

Learn advanced linear algebra for computing. Linear algebra is one of the fundamental tools for computational and data scientists. In Advanced Linear Algebra: Foundations to Frontiers (ALAFF), you will build your knowledge, understanding, and skills in linear algebra, practical algorithms for matrix computations, and the analysis of the effects of floating-point arithmetic as performed by computers.

Self Paced
Self-Paced
Computing in Python IV: Objects & Algorithms (edX) EdX
Georgia Institute of Technology,GTx

Computing in Python IV: Objects & Algorithms (edX)

Learn about recursion, search and sort algorithms, and object-oriented programming in Python. Complete your introductory knowledge of computer science with this final course on objects and algorithms. Now that you've learned about complex control structures and data structures, learn to develop programs that more intuitively leverage your natural understanding of problems through object-oriented programming. Then, learn to analyze the complexity and efficiency of these programs through algorithms. In addition, certify your broader knowledge of Introduction to Computing with a comprehensive exam.

Self Paced
Self-Paced
Java Programming Fundamentals (edX) EdX
Galileo University,GalileoX

Java Programming Fundamentals (edX)

Your career as a program developer starts here. Gain entry-level programing skills in Java language, and prepare yourself to handle any task that is required in any programming job. Java is one of the most in-demand programming languages today. This course is designed to provide students the basic skills and knowledge on Java.

Self Paced
Self-Paced
SQL for Data Science (edX) EdX
IBM

SQL for Data Science (edX)

Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in the data science field. Much of the world's data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and extracting various data types from databases.

Self Paced
Self-Paced
How to Code: Complex Data (edX) EdX
The University of British Columbia,UBCx

How to Code: Complex Data (edX)

Learn how to design more complex programs, using new data structures, abstraction, and generative recursion. As your program requirements get more complex, you will find that simple additions to the design method make it easy to write well-structured and well-tested code that is easy to maintain. By learning how to capture common data and control structures using abstraction, your programs will get shorter and better tested.

Self Paced
Self-Paced