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The planning element of a computational thinking lesson according to the Digital Competence Framework (DCF) in Wales involves designing a lesson that integrates computational thinking skills and aligns with the framework's progression steps. Here are key considerations for planning a computational thinking lesson within the DCF:
1. Identifying Computational Thinking Competencies:
- Clearly define the computational thinking competencies outlined in the DCF. These may include problem-solving, decomposition, pattern recognition, abstraction, and algorithmic thinking. Identify specific skills related to computational thinking that align with the progression steps in the framework.
2. Setting Clear Learning Objectives:
- Establish clear learning objectives for the computational thinking lesson, incorporating digital competencies as essential components. Objectives might include developing algorithms for problem-solving, recognising patterns in data, or applying abstraction to simplify complex tasks.
3. Selecting Appropriate Digital Tools:
- Choose digital tools that support computational thinking. This could involve programming environments (e.g., Scratch, Python), visual coding platforms, online simulations, or data analysis tools. Select tools that are suitable for the students' skill levels and align with the goals of the lesson.
4. Incorporating Coding and Programming:
- If applicable, introduce coding or programming elements into the lesson. Plan activities that involve writing and executing code to solve problems. Emphasise the importance of understanding coding syntax, logical reasoning, and debugging skills.
5. Emphasising Algorithmic Thinking:
- Plan activities that emphasize algorithmic thinking, guiding students to break down problems into step-by-step procedures. Introduce the concept of algorithms and teach students how to create and refine them to solve computational problems.
6. Fostering Problem-Solving Skills:
- Design problems or challenges that require computational thinking for effective solutions. Encourage students to approach problem-solving systematically, considering multiple perspectives and iterating on their solutions.
7. Incorporating Data Analysis:
- If relevant, integrate elements of data analysis into the lesson. Teach students how to collect, analyse, and interpret data using digital tools. This could involve spreadsheet software or data visualization tools.
8. Ensuring Inclusivity:
- Consider how to make the lesson inclusive for all students. Provide alternative activities or tools for those who may face barriers, ensuring that everyone can engage in computational thinking exercises.
9. Assessment Strategies:
- Develop assessment strategies that evaluate both computational thinking skills and the application of digital tools. Consider rubrics that assess problem-solving processes, coding proficiency, and the ability to think algorithmically.
10. Encouraging Reflection:
- Include opportunities for students to reflect on their computational thinking experiences. Encourage self-assessment, reflection on problem-solving approaches, and thoughts on how computational thinking can be applied in various contexts.
By incorporating these considerations into the planning phase of a computational thinking lesson, educators can create a learning experience that not only develops computational thinking skills but also aligns with the objectives of the Digital Competence Framework in Wales.
Computational thinking is a combination of scientific enquiry, problem-solving and thinking skills.
Before learners can use computers to solve problems they must first understand the problem and the methods of solving them.
At progression step 4 The DCF states through these elements learners will understand the importance of data and information literacy; they will explore aspects of collection, representation and analysis. Learners will look at how data and information links into our digital world, and will provide them with essential skills for the modern, dynamic workplace.
Exemplar lesson
Lesson Title: Computational Thinking in Mathematics
Objective:
Students will apply computational thinking principles to solve mathematical problems using digital tools. This lesson is designed to align with the Digital Competence Framework (DCF) for Wales, focusing on progression step 4.
Digital Competence Framework (DCF) Focus: Progression Step 4 - Problem Solving:
- Develop and apply strategies to solve problems in both familiar and unfamiliar contexts.
- Identify and define computational problems and apply computational thinking in solving them.
Lesson Structure:
Introduction (10 minutes):
1. Discuss the concept of computational thinking, emphasising its role in problem-solving and its relevance in mathematics and beyond.
2. Introduce the specific mathematical problem that will be solved using computational thinking.
3. Briefly discuss digital tools that can aid in computational thinking (e.g., programming environments, spreadsheets, online calculators).
Activity - Computational Problem-Solving (30 minutes):
1. Divide the class into small groups and assign each group a mathematical problem that requires computational thinking.
2. Encourage students to break down the problem into smaller steps, identify patterns, and devise algorithms to solve it.
3. Introduce the use of digital tools for computational problem-solving. Depending on the problem, this might involve coding, using a spreadsheet, or utilising a math software tool.
Digital Tools Exploration (15 minutes):
1. Provide a brief tutorial or demonstration of a specific digital tool relevant to computational thinking in mathematics. For example, introduce a coding platform (e.g., Scratch, Python), a spreadsheet application, or a mathematical modeling tool.
2. Allow students to explore the chosen tool, guiding them through the basic functions and features.
Collaborative Application (10 minutes):
1. Encourage groups to collaborate and apply computational thinking using the digital tool to solve a related or different mathematical problem.
2. Emphasise the importance of effective communication within the group and clear documentation of the computational steps.
Reflection and Discussion (10 minutes):
1. Have each group present their computational solutions, explaining their thought processes and showcasing the digital tools used.
2. Facilitate a class discussion on the effectiveness of computational thinking in solving mathematical problems and the advantages of using digital tools.
Homework Assignment (5 minutes):
Assign a homework task that requires students to apply computational thinking to solve a mathematical problem independently, using a digital tool of their choice.
Assessment:
Assess students based on their ability to break down problems, apply computational thinking, and effectively use digital tools for problem-solving. Provide feedback on both the mathematical accuracy and the efficiency of their computational approaches.
Extension Activities:
- Explore more advanced mathematical problems that require algorithmic thinking.
- Introduce additional digital tools for computational thinking, allowing students to choose the most suitable ones for their tasks.
Conclusion:
This lesson aims not only to enhance mathematical problem-solving skills through computational thinking but also to equip students with the digital skills necessary for effective problem-solving, aligning with the Digital Competence Framework progression step 4 in Wales.
Link to a power point - Computational thinking in digital art. This lesson links directly to the Computation Thinking strand of the DCF.
Computational Thinking in Digital Art.pptxReport abuse