Computational Thinking and Design:
Getting Started With Digital-Age Problem Solving
In the Information Age, problems look different. Information comes at us faster than ever before, and our ability to solve problems depends on us being able to make sense of and synthesize this information. We must also design new solutions using all available technology and tools.
Digital-age problem solving combines three key skills and concepts essential to understanding and solving problems in the information age: data literacy, design thinking, and computational thinking. Data literacy is the ability to analyze, interpret, and tell stories using complex sets of data. Design thinking is the ability to understand problems and develop creative solutions. Computational thinking is the process of expressing solutions so that humans and computers can understand them.
Throughout this MOOC-Ed, you'll have the opportunity to dig into digital-age problem solving, engage with its component skills and concepts, and learn how to integrate them into your instructional practice. This course will not be heavy on coding, and you won't need to know any code going in - it will focus on how to integrate digital-age problem solving in a practical way into your classroom.
- Understand the components of digital-age problem solving: design thinking, computational thinking, and data literacy;
- Connect digital-age problem solving to existing content and problem-solving processes;
- Engage in the digital-age problem solving process through simulated activities;
- Apply digital-age problem solving in a real-world context;
- View digital-age problem solving in a variety of careers and subject areas;
- Explore connections to computer science, coding, and making.
- Unit 1: What is Digital Age Problem Solving?
In this unit, you'll learn about the course design and course requirements, and have a chance to meet your fellow participants. You'll also learn about the three primary components of digital-age problem solving: computational thinking, design thinking, and data literacy.
- Unit 2: Identifying Problems
In this unit, we'll introduce the first phase of the design process: "Understanding the Context". We'll focus on the computational thinking skills of data collection, analysis, and representation. You'll also have the opportunity to explore these concepts on your own, share with the group, and brainstorm applications to your practice.
- Unit 3: Making Sense of Problems
This unit will transition from identifying problems to breaking them down in order to determine possible solutions. We'll focus on the "Defining the Problem" phase of the design process, with a specific focus on the computational thinking skills of problem decomposition, abstraction, and parallelization. You'll experience these skills by completing a simulated activity with a problem that you select, and you'll have an opportunity to brainstorm how you can use these concepts in your classroom.
- Unit 4: Creating Solutions
Now that we know how to identify contexts and break down problems, the next step is to begin creating solutions. In this unit, we'll focus on the "Creating Solutions" phase of the design process, with a focus on the computational thinking skills of parallelization, algorithm development, automation, and simulation. You'll experience these skills in simulations, and discuss how these concepts can be integrated into your classroom.
- Unit 5: Assessing Solutions
This final unit will transition to the “Evaluate, Reflect, Revise” phase of the design process, with a focus on the computational thinking skills of simulation and automation, along with a revisiting of data collection and analysis. It will also serve as a capstone for the course, allowing you to reflect on what you've learned and connect back to the beginning of the design cycle.
As you engage in supporting your own professional development, there are many ways to demonstrate your learning and earn recognition through this course that can be applied towards continuing education units (CEUs) through your own local educational agency.
Completion of the Computational Thinking and Design course will enable participants to earn between 10 and 32.5 hours of professional development credit by completing the following course requirements:
- 10 hours for completion of the Course Essentials
- Up to 22.5 hours for completing course micro-credentials
To maximize your learning opportunities, we suggest doing the following to earn a certificate for 10 hours of professional development (or 1.0 CEU). While we hope you engage with many of the materials in the course, at a minimum, in each unit (1-5), you must:
- Participate in unit discussions (post at least one original post and one reply in each discussion forum)
- Complete the end-of-course and unit surveys
There are also opportunities to participate in performance assessments to demonstrate your competency with ideas presented in the course and apply them to your educational practices. These performance assessments, called micro-credentials, can allow you to earn additional CEUs. Our Computational Thinking and Design micro-credentials are portable and stackable. Once you demonstrate a competency and earn a micro-credential, you will receive a certificate and a virtual badge recognizing your accomplishment. We have created one stack of micro-credentials that is purposefully stacked to help support you as you deepen your knowledge and competence in the digital-age problem-solving process.
Note that you can earn CEUs by successfully completing any of the five Computational Thinking and Design micro-credentials, even if you choose to not complete the requirements for the 10-hour certificate.
- Self-directed learning, through personalizing your experience by identifying your own goals, selecting among a rich array of resources, and deciding whether, when, and how to engage in discussions and activities to further your own learning and meet your goals.
- Peer-supported learning, through engaging in online discussions, reviewing your colleagues' projects, rating posted ideas, recommending resources, crowdsourcing lessons learned, and participating in twitter chats and other exchanges appropriate to the individual course.
- Job-embedded learning, through the use of case studies, classroom and school related projects; developing action plans; and other activities that center your work on critical problems of practice and data-informed decision-making in your own classrooms, schools or districts.
- Multiple voices, through learning about the perspectives of other teachers and administrators along with those of students, researchers and experts in the field. Our courses are purposefully not designed around one or two experts who present online lectures. They provide exposure to a rich set of perspectives presented within the context of course elements that reflect these core principles.
You will see these design principles implemented in our courses through the following instructional elements:
- Conceptual Frameworks
- Resource Collections
- Asynchronous Discussions and Twitter Chats
- Student Scenarios
- Expert Panels
- Participant Projects and Peer Feedback
- Professional Learning Community (PLC) Guides
Grade 3-12 Teachers
Instructional Technology Facilitators
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