Chart-Ed | Data Forensics

Advanced audit

DF-TR

Data Forensics

Trust, provenance, construction, and responsible-use audit.

DLL 5-6

The skeptical question is indeed the task.

Students separate what the evidence authorizes from what remains unlicensed, unknown, or responsibly bounded - domain by domain, across eight forensic lenses.

Data Forensics student pack cover

Audience

AP · Honors · Advanced Secondary

Format

PDF student + teacher pack

Price

$13.99

Reading a chart.

Auditing one.

Data Forensics asks a different question than any other product in this line. Not: what does this chart show? But: can this chart be trusted, and for what?

What this is

Eight domains. One question. Should this data artifact be trusted, and for what purpose?

Every other Chart-Ed product works within the chart as given. Data Forensics examines the chart itself: its provenance, construction choices, representation claims, and inference limits. Students produce a bounded trust verdict supported by visible evidence and disclosed metadata.

This is the work of a researcher, journalist, policy analyst, or careful reader who understands that a chart is not a neutral window onto facts. It is an artifact, produced by someone, from somewhere, for some purpose.

Provenance

Where did this chart come from? Who produced the underlying data, who published it, and what can be traced versus what remains unknown at the collection level?

Construction choices

How were the values measured, processed, and visualized? What transformation and framing decisions are disclosed, and what remains opaque?

Inference limits

Which claims does the disclosed evidence license, and which claims go beyond what the artifact can authorize, regardless of how plausible they sound?

Audit layers

Eight domains. Each asks a different forensic question about the same chart.

Students work through every domain using the same three-part structure: Disclosure Gaps, Observed Evidence, Boundary Implications.

Domain 1

Provenance & Incentives

What do we know about where this artifact came from, and what remains unknown about its origin or incentives?

Domain 2

Sampling & Representation

How were observations selected, and can the displayed values be taken as representative of a broader population?

Domain 3

Method & Instruments

How were the displayed values measured or produced before they became a chart?

Domain 4

Transformations & Handling

What happened between raw data collection and the final displayed values, and what of that pipeline is disclosed?

Domain 5

Visualization & Framing Integrity

How does the chart visual form shape what viewers notice, compare, or assume?

Domain 6

Claims & Inference Licensing

Which claims are licensed by the disclosed evidence, and which claims go beyond it?

Domain 7

Contextual & Historical Anchoring

What time frame, historical baseline, or comparative context is disclosed, and what remains unanchored?

Domain 8

Systems & Responsible Use

How can this artifact be used responsibly, and what unknowns must be labeled as unknown before it is shared or cited?

Data Forensics chart artifact page

The chart artifact

The chart is not a given. It is exhibit A.

Every Data Forensics pack is built around a single real-world chart, but students do not begin by reading it for what it shows. They examine it as an artifact: a published object with an origin, a production process, disclosed and undisclosed metadata, and a set of claims it can and cannot authorize.

What is disclosed becomes the evidentiary foundation. What is not disclosed defines the boundary of every claim.

Student audit pages

Three questions per domain. The same rigorous structure across all eight.

Every domain is structured identically so students develop the habit of a professional forensic reader: Disclosure Gaps, Observed Evidence, and Boundary Implications.

Missing information is not a gap in the student's knowledge. It is a documented feature of the artifact's disclosure. Students report what can be verified, then produce bounded claims.

Data Forensics Domain 1 audit page
Data Forensics Domain 3 audit page
Data Forensics Domain 6 audit page
Data Forensics Teacher Edition overview page
Data Forensics assessment guidance page

Teacher Edition

A domain-by-domain audit guide that matches every move students make.

The Teacher Edition opens with the product governance framework: what students are doing, what students are not doing, and the complete Licensed and Unlicensed Claims list for the chart in the pack.

Discussion closer

"Should this data artifact be trusted? Write a bounded answer using the phrase 'trusted for bounded descriptive forensic use' - only if you also state the limits."

These are not discussion starters. They are forensic closing arguments written in language students can use directly.

Claims licensing

Every pack tells you exactly what the chart can, and cannot, be used to support.

The Teacher Edition includes a complete Licensed and Unlicensed Claims list specific to the chart in each pack.

Licensed claims

What the disclosed evidence authorizes:

  • The artifact is a grouped bar chart with the disclosed title.
  • The publisher provider, source URL, retrieval timestamp, license, and approved chart source verification metadata are disclosed.
  • All labeled bar-end values are treated by the approved chart source as exact chart points.
  • Descriptive comparison among displayed labeled values is licensed when the comparison stays inside what is directly shown or disclosed.

Unlicensed claims

What goes beyond what the artifact can support:

  • ×Why any displayed difference appears
  • ×Any causal relationship between the chart topic and the displayed values
  • ×Any policy effectiveness conclusion or prediction about future outcomes
  • ×Any exact reading of unlabeled values
  • ×Any claim that displayed values fully represent a broader population
  • ×Any claim about original source quality beyond what is explicitly disclosed
"Trusted for bounded descriptive forensic use - only if you also state the limits."

Six things inside the Teacher Edition built for the forensic classroom.

Overview page

A full governance document: purpose, what students are and are not doing, complete Licensed and Unlicensed Claims, and Discussion Closers.

Discussion closers

Three structured forensic prompts that close the audit with a bounded trust verdict, construction description, and responsible-use statement.

Domain-by-domain teacher goals

For all eight domains, a Teacher Goal paragraph states what the student audit page is correctly doing, so review is focused and consistent.

Licensed vs. Unlicensed Claims

A complete claims framework specific to the chart in each pack, written in language students can quote directly in bounded conclusions.

Evidence needed for stronger claims

Where disclosed evidence falls short, the TE names what additional evidence would be required: sampling documentation, methods, transformations, or historical baselines.

Assessment guidance page

A single-page domain-focus summary that maps Teacher Goals across all eight domains when reviewing student work across a full audit.

Built for courses where source evaluation is the work.

Data Forensics is designed for courses where students are expected to audit evidence, bound their conclusions, and reason about what data can and cannot authorize.

AP & Dual Enrollment

AP Language, AP Environmental Science, AP Government, AP Statistics, and dual-enrollment research writing, where evidentiary weight is a graded skill.

Research Methods & Inquiry Courses

Courses that ask students to design research questions, evaluate existing data, or produce evidence-based arguments from data sources.

Honors & Advanced Secondary

Honors English, social studies, and advanced science electives where students need to distinguish what data shows from what data proves.

"Most critical thinking instruction tells students to question sources. Data Forensics gives them the exact questions, and the forensic framework to answer them with evidence."

The gap is not skepticism. It is structure.

AP and Honors students are not short on critical thinking instincts. What they lack is a protocol for deciding what trust depends on, how to document what they know versus what they are assuming, and how to produce a bounded trust verdict.

Data Forensics provides that protocol: eight domains across every dimension that affects trustworthiness, and a three-part structure for separating what is known from what is assumed.

Not

A source evaluation checklist

It is

A domain-by-domain forensic audit framework that produces bounded, evidence-supported trust verdicts

Not

Critical thinking in the abstract

It is

A structured protocol for distinguishing licensed claims from unlicensed ones, applied to a specific real-world chart artifact

Not

A product for general classroom use

It is

Purpose-built for AP, Honors, dual enrollment, and research-methods courses where source evaluation is a graded competency

Everything in the complete pack.

Student Audit Pages

  • Full-page real-world chart artifact with locked intake record
  • Domain 1 - Provenance & Incentives audit page
  • Domain 2 - Sampling & Representation audit page
  • Domain 3 - Method & Instruments audit page
  • Domain 4 - Transformations & Handling audit page
  • Domain 5 - Visualization & Framing Integrity audit page
  • Domain 6 - Claims & Inference Licensing audit page
  • Domain 7 - Contextual & Historical Anchoring audit page
  • Domain 8 - Systems & Responsible Use audit page
  • Disclosure Gaps / Observed Evidence / Boundary Implications structure

Teacher Edition (TR)

  • Overview page with Purpose, What Students Are Doing / Not Doing, Allowed Claims, Unlicensed Claims, and Discussion Closers
  • Assessment Guidance page with domain-by-domain Teacher Goals
  • Domain Guidance pages for all eight domains
  • Licensed Claims, Unlicensed Claims, and Evidence Needed for Stronger Claims
  • DLS-aligned (Data Literacy Standards v1.0.1, DLL 5-6)
PDFInstant DownloadPrint-ReadyStudent + Teacher Edition

$13.99

Complete pack. One chart artifact. One full-domain forensic audit.

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