KS3 Introduction to Python 6 lesson packQuick View
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KS3 Introduction to Python 6 lesson pack

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This Introduction to Python: 6-Lesson Bundle takes students from absolute beginners to writing interactive, logical programs. Designed for Year 9 (KS3), the series transitions students from block-based logic to industry-standard text-based coding, focusing on syntax, data handling, and selection. Lesson 1: Hello Python – An introduction to the Python IDE and high-level languages. Students write their first scripts using the print() function and learn the difference between machine code and interpreted languages. Lesson 2: Storing Data – Introduces Variables as named locations in memory. Students practice assigning and updating values, using the “cardboard box” analogy to understand how data is stored and overwritten. Lesson 3: Inputs & Strings – Focuses on Interaction. Students learn to use the input() function to capture user data, join strings together using Concatenation, and use Comments (#) to document their code. Lesson 4: Numbers & Maths – Introduces Calculations and Casting. Students learn to convert string inputs into Integers or Floats to perform arithmetic operations, building tools like area calculators and age trackers. Lesson 5: Using Logic – The first step into Selection. Using the “Bouncer at the Club” analogy, students learn the syntax of if statements, the importance of Indentation, and the use of colons. Lesson 6: Comparing Data – The series finale covers Boolean Logic and Comparison Operators (>, <, ==, !=). Students expand their programs with else statements and build a functional “Score Checker” and “Number Guesser.” ###Key Features of this pack### Consistent Structure: Each lesson includes clear Learning Objectives, a “Starter” recall task, live coding demonstrations, and independent practical challenges. "Syntax Saboteurs": Integrated debugging tasks help students identify common errors like missing colons, case sensitivity, and indentation mistakes. Extension Challenges: Every lesson contains “Gold” level tasks to stretch high-ability students, such as using modulo operators or nested logic. Assessment Ready: The pack concludes with a plenary review of key vocabulary (Variables, Casting, Concatenation, Selection, Booleans) to prepare students for formal CS assessments.
The Ghost in the Machine: AI Resource packQuick View
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The Ghost in the Machine: AI Resource pack

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The Ghost in the Machine: A Hands-On Guide to AI, Logic, and Ethics Are your students curious about how ChatGPT actually “thinks”? Move beyond the hype with this comprehensive mini-unit designed for A/AS or GCSE Computer Science. This resource pack takes a deep dive into the mechanics of Large Language Models (LLMs) through live Python coding, data-driven experiments, and exam-style evaluation. What’s Included: Slide Deck: “Demystifying the Next Token”: An engaging PowerPoint that breaks down complex concepts like Tokenization, Encoding, and Statistical Prediction into student-friendly analogies. Simple_Python_SLM: A simple, elegant script that demonstrates a “Markov Chain” in action. Perfect for teaching basic list logic and dictionary mapping. Python_SLM_AI: An upgraded script using File Handling (.txt persistence) and Text Pre-processing. Students learn how to build a model that “remembers” what it has been taught over time. The “Bias Lab” Dataset: A specially curated, “synthetic” news report designed to bake specific gender biases into the Python model. This provides a powerful “Aha!” moment when students see their own code generate discriminatory outputs based on the training data. Exam board-Style Assessment Pack: * Four original 8-mark extended response questions covering Ethical, Legal, Cultural, and Environmental impacts. PEEL Writing Frames and Success Checklists to support literacy. Model Answers: Side-by-side “Good” vs. “Poor” examples with marking commentary to help students understand the OCR Level of Response criteria. Key Learning Objectives: Explain how LLMs use tokens and statistical probability to generate text. Implement a functional Markov Chain using Python dictionaries and File I/O. Critically evaluate the impact of algorithmic bias on society (Mortgages, IP law, and the Environment). There is even a keyword Bingo card to help keep the students engaged. Perfect for a 2–3 lesson “Deep Dive” or a high-impact enrichment week!