AP CSP Day 8 - Extracting Information from Data
AP CSP Day 8 - Extracting Information from Data
Course Information
- Course: AP Computer Science Principles
- Unit: Big Idea 3 - Data & Information (DAT)
- Lesson: Day 8 (50 minutes)
- Learning Objective: DAT-1.D - Extract information from data
Learning Objectives
Primary Goals
Students will be able to:
- Explain methods for extracting information from data
- Identify common data extraction techniques
- Apply extraction techniques to datasets
- Analyze the impact of data extraction on decision-making
AP Exam Alignment
- Big Idea 3: Data & Information (27-36% of AP Exam)
- Essential Knowledge: DAT-1.D.1, DAT-1.D.2, DAT-1.D.3
- Computational Thinking Practice: 3.A - Extract information from data using queries
Lesson Structure (50 minutes)
Opening Hook (10 minutes)
8.1 Welcome & Lesson Preview (5 minutes)
Teacher Activities:
- Welcome students to Day 8
- Review previous lesson's key concepts
- Introduce today's focus on extracting information from data
Student Activities:
- Review previous lesson's materials
- Think about: "How can we extract useful information from data?"
8.2 Quick Extraction Challenge (5 minutes)
Activity: "Extract Data Insights"
Instructions:
- Groups of 4-6 students
- Extract insights from a given dataset
- Discuss the process
Purpose: Activate thinking about data extraction
Core Content Instruction (20 minutes)
9.1 What is Data Extraction? (10 minutes)
Definition (DAT-1.D.1):
Data extraction involves retrieving specific information from large datasets.
Key Concepts:
- **Queries: Asking questions of data
- **Filters: Selecting relevant data
- **Aggregates: Summarizing data
Case Study: The extraction of sales data in an e-commerce app
- Extraction process: Using queries and filters
- Outcome: Insights into sales trends
9.2 Common Extraction Techniques (5 minutes)
Techniques:
- **SQL queries: Structured Query Language
- **Filtering: Selecting subsets of data
- **Summarization: Creating aggregates
Examples:
- E-commerce app: Extracting sales data using SQL
- Social media app: Filtering user posts by topic
9.3 Importance of Data Extraction (5 minutes)
Why is it important?:
- Decision-making: Informed choices based on data
- Efficiency: Faster access to relevant information
- Insights: Discovering hidden patterns
Discussion Questions:
- How do SQL queries work?
- What are the benefits of filtering data?
- Why is data extraction important for informed decisions?
Hands-On Activity (15 minutes)
10.1 Group Project: Data Extraction Practice (15 minutes)
Activity: "Extract and Analyze Data"
Instructions:
- Groups of 3-4 students
- Extract insights from datasets using queries and filters
- Discuss the process and its applications
- Present findings
Materials:
- **List of datasets to extract from
- **Extraction worksheet
- **Access to coding environment
Learning Goals:
- **Understand data extraction
- **Identify extraction techniques
- **Apply extraction methods
- **Present ideas effectively
Assessment:
- **Group participation
- **Extraction accuracy
- **Use of extraction tools
- **Presentation clarity
Closure & Preview (5 minutes)
11.1 Key Concepts Review (2 minutes)
Today's Learning Highlights:
- ✅ Understanding data extraction
- ✅ Identifying extraction techniques
- ✅ Applying extraction methods
- ✅ Analyzing extraction impact
AP Exam Connection:
- These concepts will appear in AP exam multiple choice questions
- Understanding data extraction is crucial for the Explore Performance Task
11.2 Next Class Preview (3 minutes)
Day 9 Topic: "Using Programs to Process Data"
- Learning Objective: DAT-1.E - Use programs to process data
- Activity: Practicing data processing techniques
- Homework: Think about a recent program you used. What data extraction techniques did it use? What could be improved?