Unit 1, Section 1: Setting the Stage

Section 1: Setting the Stage

Overarching Themes

This section builds a foundational understanding of how to transform raw information into actionable intelligence through the lens of a “Data Detective.” By moving through the early stages of The Data Cycle, students learn that data are not just numbers on a page but a structured representation of real-world variability. A central focus is placed on how data integrity, representation, and organization profoundly impact the “story” we can tell. Ultimately, the curriculum emphasizes that a successful investigation begins with asking the right questions, shifting from simple individual inquiries (survey questions) to broader, group-focused investigations (statistical questions) that account for the variation inherent in any population.

Daily Overview

Lesson Title	Vocabulary	Lesson Activities	GAISE Level B Guidelines
Lesson 1: Meet the DSU Squad (DSU = Data Science Unit)	data science data datum survey questions The Data Cycle Consider Data (phase) primary data	Information Stations: Collecting personal data via survey questions Think-Ink-Pair-Share (TIPS): Defining data	B.II.1: Data as information collected with a purpose B.II.4: Data collection via surveys
Lesson 2: Reconstructing the Scene	representations	Sketch the Scene: Reconstructing a visual based on lists vs. field notes Gallery Walk: Comparing data representations	B.II.1: Organizing and storing data in various structures B.II.6: Interrogating how data are measured
Lesson 3: Compiling the Suspect Dossiers	observations secondary data	Guess Who?: Identifying traits Grouping Suspects: Physically organizing 30 suspect cards based on visual characteristics	B.II.7: Understanding secondary data B.II.2: Describing the population/group from which data are collected
Lesson 4: Acquiring & Organizing Additional Evidence	survey questions	Dossier Creation: Extracting written data from full ID cards to create a one-page team display/briefing poster	B.II.1: Organizing data into structures for analysis B.II.3: Using data to make comparisons between groups
Lesson 5: Structuring the Evidence	data table case attributes variable missing value numerical variable categorical variable	Variable Brainstorm: Identifying 11 suspect variables Data Table Template: Manually entering data and handling missing values	B.II.1: Storing data in spreadsheets/tables B.II.6: Identifying variable types and possible outcomes
Lesson 6: Our Detective Toolkit - CODAP	CODAP case card case table	Digital Entry: Transferring paper data to CODAP Integrity Check: Verifying categorical/numerical types in the software	B.II.1: Understanding data structures in digital platforms B.II.6: Interrogating data collection and measurement in software
Lesson 7: What's in a Question?	Pose Questions (phase) statistical questions	Quick Collection Challenge: "Stand and Share" to show variation Peer Review: Writing and critiquing investigative statistical questions	B.I.1 - B.I.5: Formulating statistical investigative questions that account for context and variability
Progress Check 1: Can You Read the Evidence?		Investigative Task 1: Data Structure Analysis Investigative Task 2: Formulating Questions	B.IV.1: Using evidence to answer investigative questions B.II.6: Interrogating types and sources