Student Investigations — Hands-On Lab Ideas¶

"Follow the evidence!" — Trace the Raccoon

This page is a teacher planning catalog. Each entry turns a key concept from a chapter into a Student Investigation: a hands-on lab where an individual student or a small group solves a crime, cracks a mystery, or completes an investigation. Assign one, run a full "crime lab" rotation, or build a semester-long capstone from several.

Every investigation lists its learning objective, the chapters it ties into, and either a shopping list (physical) or a MicroSim specification (virtual). Where a MicroSim already exists in docs/sims/, it is noted so you can reuse it instead of building from scratch.

How to read each entry¶

Each investigation is tagged with one of three lab types:

Badge	Type	What it means
🧪 Physical	Real bench lab	Solvable with under $50 of supplies per group, purchasable by a teacher from a grocery store, hardware store, or a science-supply vendor (Carolina, Home Science Tools, Amazon).
💻 Virtual	Digital lab	Solved with a combination of the `/story-generator` skill and one or more MicroSims. No consumables.
🔀 Combination	Hybrid	A physical bench step plus a virtual step — typically used to simulate an expensive or slow instrument (DNA sequencer, GC-MS, insect rearing) that a classroom cannot afford or wait for.

Budget & safety ground rules

$50/group cap covers consumables only. Shared classroom equipment (compound microscopes, a UV flashlight, a laptop) is assumed to already be on hand and is called out separately as "Assumes access to…".
No real blood, no real body fluids, no controlled substances, no live flame beyond a supervised candle. Every "blood," "drug," and "accelerant" below is a simulant with the same observable behavior.
Investigations that use chemicals include a one-line safety note; always pair with your district's lab-safety policy and PPE (goggles, gloves, aprons).

1. Locard's Silent Witness — Trace Evidence Transfer 🧪¶

Description. Every group gets a "suspect" object (a fleece glove, a wool scarf, a glitter-dusted folder) and a "crime scene" surface. Students stage a brief contact event, then hunt for the two-way transfer of fibers, glitter, and hairs using tape lifts and a magnifier — proving that every contact leaves a trace. A twist envelope reveals which of three suspect objects actually touched the scene; students must let the recovered evidence, not the story, decide.

Learning objective. Demonstrate Locard's Exchange Principle by documenting bidirectional trace transfer between two surfaces and using it to include or exclude a suspect.

Chapter ties. Ch 01 (Locard Exchange Principle); Ch 02 (Trace Evidence, Evidence Collection); Ch 04 (Class Evidence).

Supplies (per group, ≈ $18). Clear packing tape + index cards for tape lifts; 1 fleece glove; 1 wool scarf; craft glitter; a handful of pet fur or craft-fur; 5× hand magnifiers or loupes; tweezers; a black construction-paper "scene" mat. Assumes access to a classroom microscope for the reveal.

Companion MicroSim. Reuse locard-exchange-visualizer.

2. Map the Scene — Triangulation Documentation 🧪¶

Description. A taped-off "crime scene" on the classroom floor holds 4–5 numbered evidence markers. Groups must produce a scaled sketch that fixes each item's position by triangulating from two fixed reference points (door frame, window corner). A rival group then uses only the sketch to place the items back — accuracy of the reconstruction is the grade.

Learning objective. Produce a scaled crime-scene sketch using the two-point triangulation method and evaluate its accuracy by reconstruction.

Chapter ties. Ch 02 (Crime Scene Sketching, Scaled Sketch Techniques, Triangulation Measurement, Crime Scene Documentation).

Supplies (per group, ≈ $12). 1 tape measure (25 ft); painter's tape; graph paper; ruler/protractor; 5 numbered evidence tent markers (or folded index cards); a few props (toy, key, "weapon").

Companion MicroSim. Reuse triangulation-measurement to practice the method before the floor exercise.

3. The Dusting Detective — Developing Latent Prints 🧪¶

Description. Students press clean fingertips onto glass, plastic, and paper, then develop the invisible latent prints with a dusting powder and lift them with tape. They compare their own prints to a set of "suspect" exemplar cards to find who handled the ransom note. A second station uses super-glue (cyanoacrylate) fuming in a covered jar to reveal prints on a plastic bag — instructor-run.

Learning objective. Develop latent fingerprints on porous and non-porous substrates and match a developed print to an exemplar using pattern type and minutiae.

Chapter ties. Ch 03 (Latent Fingerprints, Fingerprint Substrates, Cyanoacrylate Fuming, Minutiae Points, Loops/Whorls/Arches).

Supplies (per group, ≈ $22). Cocoa powder or cornstarch + fine cosmetic brush (cheap black-powder substitute) or a real black fingerprint powder jar; clear packing tape; white and black index cards; a drinking glass, a zip bag, a paper strip; ink pad for exemplars. Safety: cyanoacrylate fuming is a teacher demo only, in a ventilated area.

Companion MicroSims. Reuse fingerprint-pattern-explorer and latent-print-development.

4. Cold Case: AFIS Classification Challenge 💻¶

Description. A story-driven whodunit: a latent print is pulled from a museum-heist scene, and students must classify it (loop / whorl / arch), count minutiae, and "search" a six-suspect AFIS database to rank candidates — learning why AFIS ranks rather than matches, and why a human examiner makes the final call. Delivered as a branching story with an interactive search widget.

Learning objective. Classify a fingerprint by pattern and minutiae and explain how an AFIS candidate list is generated and verified.

Chapter ties. Ch 03 (AFIS Database, Fingerprint Individualization, Minutiae Points, Pattern Classification).

MicroSim spec. Reuse afis-search-workflow wrapped in a /story-generator narrative. New optional widget: a minutiae-tagging canvas (p5.js) — student clicks ridge endings and bifurcations on a zoomable print image; the sim scores tagged points against a hidden ground-truth set and returns a ranked candidate list with match scores. Controls: createButton('Reset'), createSelect() for pattern type, createSlider() for zoom.

5. Human or Beast? The Medullary Index Mystery 🔀¶

Description. A hair is found clutched in a victim's hand. Groups mount unknown hair samples (human head hair, dog, cat, wool) on slides, measure medulla and shaft diameter under the microscope, and compute the medullary index to sort human from animal. The physical measurement feeds a MicroSim that plots their value against reference ranges and returns the species verdict.

Learning objective. Measure hair medulla and shaft width, calculate the medullary index, and classify a hair as human or non-human against reference ranges.

Chapter ties. Ch 04 (Hair Medulla Structure, Medullary Index Calculation, Human vs Non-Human Hair, Hair Scale Patterns).

Supplies (per group, ≈ $15). Prepared or self-mounted hair samples (human volunteer + pet fur + wool yarn); blank slides + coverslips; clear nail polish or glycerin as mountant; ocular micrometer or a printed scale bar. Assumes access to a compound microscope.

Companion MicroSim. Reuse medullary-index-calculator for the verdict step.

6. Fiber Under Fire — Burn & Solubility ID 🧪¶

Description. Six unknown fiber snippets (cotton, wool, nylon, polyester, acrylic, silk) are recovered from a suspect's car. Groups run a controlled burn test (flame behavior, smell, ash) and a solubility spot test, then key the fiber to a dichotomous identification chart to match it to the fibers on the victim's sweater.

Learning objective. Distinguish natural from synthetic fibers using burn characteristics and chemical solubility, and use a dichotomous key to identify an unknown fiber.

Chapter ties. Ch 04 (Natural Fibers, Synthetic Fibers, Burn Testing of Fibers, Chemical Solubility Testing, Fiber Microscopy).

Supplies (per group, ≈ $20). Small fiber/yarn samples of 6 types; long tweezers/forceps; a tea light or Bunsen burner; heat-proof tile; acetone (nail- polish remover) for the solubility test; labeled jars. Safety: burn test in a fume hood or well-ventilated area, one flame per bench, teacher-supervised, goggles required.

Companion MicroSim. Reuse fiber-identification-tree as the digital key.

7. The Broken Window — Refractive Index & Fracture Match 🔀¶

Description. Glass fragments from a suspect's jacket must be tied to a broken window. In the physical step, students immerse glass chips in a series of household liquids (water, oil, glycerin) and watch the Becke line to bracket the refractive index. A MicroSim then lets them fine-tune the simulated immersion oil to an exact match — modeling the pricey oil-gradient instrument a real lab uses.

Learning objective. Explain refractive index and use the Becke line immersion method to compare a glass fragment to a known source.

Chapter ties. Ch 05 (Glass Composition, Refractive Index, Becke Line Test, Immersion Oil Technique).

Supplies (per group, ≈ $16). Clean crushed-glass chips from two "sources" (safety-handled, or use clear-acrylic/glass-bead substitutes); watch glasses; water, mineral oil, corn syrup/glycerin; disposable pipettes; tweezers. Safety: teacher pre-crushes glass; students handle only pre-sorted chips with tweezers, goggles on.

Companion MicroSim. Reuse becke-line-test.

8. Which Blow Came First? Glass Fracture Sequencing 🔀¶

Description. Given photos (or a 3D-printed/acrylic panel) of a pane with two bullet holes and intersecting cracks, students apply the 3R rule and the principle that a fracture terminates at a pre-existing fracture to determine the order of impacts — answering whether the shot from inside or outside came first.

Learning objective. Determine the sequence of impacts on fractured glass using radial/concentric fracture patterns and the rule of terminating fractures.

Chapter ties. Ch 05 (Radial Fracture Lines, Concentric Fracture Lines, 3R Rule for Glass, Glass Fracture Sequence, Glass Fracture Mechanics).

Supplies (per group, ≈ $8). Printed high-res fracture photos, OR a cracked acrylic panel (teacher-prepared by scoring), dry-erase overlay sheet + marker. Mostly an analysis lab — near-zero consumables.

Companion MicroSim. Reuse glass-fracture-sequence.

9. Soil Signatures — Matching the Suspect's Boots 🧪¶

Description. Soil scraped from a suspect's boots must be matched to one of three locations. Groups characterize each soil by color (against a Munsell- style chart), pH, particle-size layering in a settling column, and mineral sparkle, then decide which site the boot sample came from.

Learning objective. Characterize and compare soil samples using color, pH, and particle-size distribution to associate a sample with a source location.

Chapter ties. Ch 05 (Soil Composition Analysis, Soil pH Measurement, Particle Size Distribution, Gradient Tube Density, Sand Mineral Analysis).

Supplies (per group, ≈ $18). 3 labeled soil samples + 1 "boot" unknown (teacher-collected from different spots); clear tall jars for settling columns; universal pH test strips; hand lens; white paper for color comparison; small sieve or coffee filter. Optional: a printed soil-color reference chart.

Companion MicroSim. Reuse soil-analysis-dashboard to log and compare results.

10. Is It Blood? The Kastle-Meyer Presumptive Test 🧪¶

Description. Reddish-brown stains on four items must be screened for blood. Students run a Kastle-Meyer-style presumptive test using a peroxidase simulant (horseradish extract) and hydrogen peroxide, watching for the tell-tale pink color and the fizz of catalase — then reason about false positives (horse- radish, rust, some fruits) and why a presumptive test only screens.

Learning objective. Perform a presumptive blood test, interpret a positive color change, and explain the difference between presumptive and confirmatory tests including false positives.

Chapter ties. Ch 06 (Presumptive Blood Tests, Kastle-Meyer Color Test, Confirmatory Blood Tests); Ch 01 (Scientific Method — screening vs confirmation).

Supplies (per group, ≈ $14). Phenolphthalein indicator solution (or a teacher-mixed KM reagent kit); 3% hydrogen peroxide; grated horseradish or a peroxidase source as "blood" simulant; rust water, ketchup, and a fruit-juice decoy; cotton swabs; spot plate. Safety: goggles and gloves; no real blood; dispose of peroxide per policy.

Companion MicroSim. New optional presumptive-test decision widget could be specified, or reuse Ch 06's serology content; pairs well with #11 below.

11. Type the Blood — Who Was at the Scene? 🧪¶

Description. Four "suspects" and one crime-scene stain get ABO/Rh typed using a simulated blood-typing kit (synthetic bloods + anti-A/anti-B/anti-Rh sera). Students watch for agglutination, record each type, and match the scene stain to the one suspect whose blood type is consistent — while learning why blood type excludes far more powerfully than it identifies.

Learning objective. Determine ABO and Rh blood type from agglutination reactions and use blood-type evidence to include or exclude suspects.

Chapter ties. Ch 06 (ABO Blood Typing, Rh Factor, Agglutination Chemistry, Blood Composition).

Supplies (per group, ≈ $35). One simulated-blood typing kit (e.g. Carolina / Home Science Tools "simulated ABO/Rh" set covers a class); typing trays; toothpick stirrers. Fully synthetic — no biohazard.

Companion MicroSim. Reuse abo-blood-typing as a pre-lab or verification tool.

12. Reading the Spatter — Angle of Impact 🔀¶

Description. Groups drip a blood simulant onto paper taped at known angles (90°, 60°, 30°, 15°), measure the length and width of each resulting stain, and compute the impact angle with the arcsin(W/L) formula — then compare their calculated angles to the true angles. The MicroSim handles the trig and lets them test angles they didn't drip.

Learning objective. Measure bloodstain dimensions and calculate the angle of impact using the width-to-length ratio, then evaluate measurement error against known angles.

Chapter ties. Ch 07 (Blood Drop Physics, Angle of Impact Formula, Surface Tension of Blood, Passive Bloodstains).

Supplies (per group, ≈ $12). Blood simulant (water + red food coloring + a little corn syrup for viscosity, or a commercial simulated-blood bottle); pipettes/droppers; butcher paper; a protractor-set incline (cardboard + tape); ruler; calculator. Washable, non-staining recipe recommended.

Companion MicroSim. Reuse angle-of-impact-calculator.

13. Stringing the Scene — Finding the Area of Origin 🔀¶

Description. From a set of directional stains on a mock wall, groups run strings back along each stain's flight path to find the area of convergence in 2D, then use the impact angles to project the strings up to the area of origin in 3D — pinpointing where the victim was when struck. The MicroSim provides a clean digital stringing view to check the physical result.

Learning objective. Locate the area of convergence and reconstruct the 3D area of origin of a bloodstain pattern using directionality and impact angle.

Chapter ties. Ch 07 (Area of Convergence, Area of Origin in 3D Space, Stringing Technique, Cast-Off Bloodstains).

Supplies (per group, ≈ $16). Foam board or a cardboard "wall + floor" corner; colored string/yarn; push pins; protractor; the printed stain pattern from #12 (or a supplied pattern sheet). Reusable across classes.

Companion MicroSim. Reuse area-of-origin-stringing.

14. From Strawberry to Suspect — DNA Extraction + STR Match 🔀¶

Description. A two-part crowd-pleaser. Physical: students extract visible DNA from strawberries (or their own cheek cells) using dish soap, salt, and cold alcohol — proving DNA is real, physical stuff. Virtual: because no school can run a $30k sequencer, a MicroSim simulates PCR amplification and produces an electropherogram for the crime-scene sample and three suspects; students compare STR peak positions at CODIS loci to find the match.

Learning objective. Extract DNA from cells and interpret a simulated STR electropherogram to include or exclude suspects at multiple loci.

Chapter ties. Ch 08 (DNA Structure, Short Tandem Repeats, PCR, Capillary Electrophoresis, Electropherogram Interpretation, CODIS Loci).

Supplies (per group, ≈ $10). Strawberries in zip bags; dish soap; table salt; cold isopropyl or ethanol; coffee filter; test tube or clear cup; wooden skewer to spool the DNA. Food-safe and cheap.

Companion MicroSims. Reuse pcr-amplification-simulator then rmp-product-rule for the statistics. New optional widget: an STR electropherogram comparison sim (p5.js / Chart.js) — renders scene vs. suspect peak sets at 4–6 loci; createSelect() picks the locus, a createButton('Overlay') toggles side-by-side vs overlaid traces, and the sim reports matching loci.

15. Beat the Odds — Random Match Probability 💻¶

Description. A defense attorney claims "lots of people share this DNA profile." Students use a MicroSim to multiply per-locus allele frequencies with the product rule, watch the random-match probability plummet as loci are added, and write a short courtroom explanation of what "1 in 7 billion" really means. Framed as a mock-trial prep exercise via /story-generator.

Learning objective. Apply the product rule to calculate a random match probability across multiple loci and interpret its meaning for a jury.

Chapter ties. Ch 08 (Random Match Probability, Product Rule in Statistics, DNA Alleles, Homozygous vs Heterozygous, DNA Database Searching).

MicroSim spec. Reuse rmp-product-rule. Wrap in a two-scene story: (1) collect allele frequencies from an evidence card, (2) argue the probability in a mock cross-examination with branching outcomes.

16. Color-Test Chemistry — Presumptive Drug Screening 🔀¶

Description. An unknown white powder (a safe simulant — baking soda, powdered sugar, cornstarch, chalk) must be screened. Students run color spot tests using household pH-indicator chemistry that stands in for the Marquis / Scott reagents, build a color-key, and reason about why field color tests are presumptive only and must be confirmed by GC-MS. A MicroSim then walks the "confirmatory" GC-MS peak-matching step.

Learning objective. Perform presumptive color spot tests on unknown powders, interpret a color key, and explain why GC-MS confirmation is required.

Chapter ties. Ch 09 (Marquis Reagent Test, Scott Reagent Test, Duquenois- Levine Test, GC-MS Analysis, Gas Chromatography, Mass Spectrometry).

Supplies (per group, ≈ $12). 4–5 harmless white powders as "unknowns"; red-cabbage indicator or universal indicator solution; iodine (from a first-aid kit) for a starch test; spot plates; pipettes; labeled key card. Safety: goggles/gloves; explicitly a simulant lab — no real controlled substances.

MicroSim spec. New optional GC-MS peak-match widget (Chart.js): displays a retention-time chromatogram + a mass-spectrum fragmentation pattern for the unknown and a small reference library; student picks the library match. Or defer to Ch 09's adme-pathway for the pharmacology angle.

17. Point of Origin — Reading a Burn Pattern 💻¶

Description. Arson investigation without the fire hazard. A story-driven scene photo set shows V-patterns, spalling, and pour-pattern char across a room; students trace the burn indicators back to the origin, decide whether the fire was accidental or set, and identify where an accelerant was likely used — then justify it with the fire tetrahedron.

Learning objective. Interpret V-patterns, spalling, and pour patterns to locate a fire's origin and assess indicators of arson.

Chapter ties. Ch 10 (Fire Tetrahedron, Arson Investigation, Accelerant Pour Patterns, Multiple Points of Origin, V-Pattern Burn Indicators, Spalling).

MicroSim spec. New burn-pattern origin explorer (p5.js): a room diagram where students click suspected origin points and drag "burn-severity" probes; the sim scores their origin estimate and flags whether multiple origins (an arson red flag) are present. createButton('Reset'), createSlider() for a time-lapse of fire spread, createCheckbox('Show accelerant trail'). Pairs with the existing headspace-spme-workflow for the accelerant-lab follow-up.

18. Bones Tell Tales — Sex & Stature Estimation 🔀¶

Description. Skeletal remains (a set of 3D-printed or cast bones, or scaled printed photos with scale bars) arrive at the lab. Groups measure pelvic and cranial features to estimate biological sex, then measure a long bone and apply a stature regression equation to estimate height — building a biological profile to compare against three missing-person reports.

Learning objective. Estimate biological sex from pelvic/cranial morphology and estimate stature from long-bone measurements using regression equations.

Chapter ties. Ch 11 (Pelvic Morphology, Subpubic Angle, Biological Sex Estimation, Long Bone Measurements, Stature Regression Equations).

Supplies (per group, ≈ $25). Printed high-resolution bone photos with scale bars (near-free), or a set of plastic-cast/3D-printed pelvis + femur models (one shared class set amortizes well); calipers or a metric ruler; calculator. Chicken/turkey leg bones (cleaned) work as a cheap long-bone stand-in for the regression math.

Companion MicroSim. Reuse skeletal-sex-indicators and the stature step of the anthropology chapter.

19. The Bug Clock — Estimating Time of Death 🔀¶

Description. A body is discovered; the largest blowfly larvae on it are 9 mm long. Given a temperature log and a development chart, groups compute Accumulated Degree Hours to back-calculate the minimum post-mortem interval. An optional multi-day physical extension rears mealworms or observes a chicken-liver-in-a-jar succession sequence (well-sealed, outdoors) to see real instar changes.

Learning objective. Use larval length, a development chart, and accumulated degree hours/days to estimate the minimum post-mortem interval.

Chapter ties. Ch 12 (Larval Instar Stages, Accumulated Degree Hours, Accumulated Degree Days, Minimum Post-Mortem Interval, Blowfly Lifecycle, Insect Succession).

Supplies (per group, ≈ $10; optional rearing). Printed temperature log + development chart + a metric ruler for the core math (near-free). Optional physical extension: mealworms from a pet store, a ventilated container, oats — observed over 1–2 weeks. Safety: if using meat/liver for succession, seal in mesh, keep outdoors, dispose responsibly.

Companion MicroSim. Reuse adh-mpmi-calculator.

20. Toolmarks & Impressions — Matching the Instrument 🧪¶

Description. A pry mark is found at the point of entry. Each suspect tool (screwdriver, chisel, bolt cutter) is pressed into modeling clay to make a known impression; students then compare the class characteristics and unique striations/compression marks of the crime-scene impression to the knowns under magnification to identify the tool — a hands-on model of comparison microscopy.

Learning objective. Compare toolmark impressions by class and individual characteristics to associate a tool with a mark.

Chapter ties. Ch 13 (Toolmark Analysis, Compression Marks, Sliding Marks, Comparison Microscope, Class vs Individual Characteristics).

Supplies (per group, ≈ $15). Modeling clay or plasticine; 3–4 hardware tools (screwdriver, flat-blade, serrated edge); hand lens or USB microscope; a "crime-scene" impression the teacher makes with one hidden tool.

Companion MicroSim. New optional striation-overlay widget could be specified, or reuse the firearms chapter's ballistic-pathway for the trajectory angle.

21. Which Pen Wrote the Ransom Note? Ink Chromatography 🧪¶

Description. A ransom note was written in black ink. Six suspect pens are seized. Groups spot each pen's ink on chromatography paper (or a coffee filter), run it with a solvent, and compare the pigment separation patterns — the note's ink fingerprint reveals which pen wrote it.

Learning objective. Separate ink pigments using paper chromatography and compare separation patterns to identify the pen used to write a document.

Chapter ties. Ch 14 (Ink Chemistry Analysis, Paper Chromatography, Thin- Layer Chromatography, Document Examination).

Supplies (per group, ≈ $10). Chromatography paper or coffee filters; 6 black water-based markers/pens (deliberately different brands); rubbing alcohol or water as solvent; clear cups; pencils to suspend strips. Safe, colorful, high-success.

Companion MicroSim. Reuse tlc-ink-separation.

22. Forged or Genuine? Handwriting Examination 🔀¶

Description. A contested signature on a check must be evaluated. Students collect requested exemplars from classmates, then examine line quality, slant, spacing, and letter formation to distinguish a person's natural writing from a simulated forgery — and rank three questioned signatures by likelihood of forgery. The MicroSim overlays and measures slant/spacing for precision.

Learning objective. Compare questioned and known handwriting using line quality, slant, and spacing to assess authenticity.

Chapter ties. Ch 14 (Handwriting Analysis, Line Quality, Slant and Spacing Analysis, Requested Writing Exemplars, Simulated Forgery, Traced Forgery).

Supplies (per group, ≈ $6). Exemplar collection sheets; the "questioned" document set (teacher-prepared with one genuine + forgeries); ruler/protractor; magnifier. Almost all paper.

Companion MicroSim. Reuse handwriting-comparison.

23. Hash It Out — Digital Evidence Integrity 🔀¶

Description. Students learn why investigators hash a drive before and after imaging. Using a simple hashing tool (or a browser MicroSim), they compute the MD5/SHA-256 hash of an evidence file, then change a single character and watch the hash change completely — proving tamper detection. They then match hashes to prove which of three "seized" files is the untouched original.

Learning objective. Compute and compare cryptographic hashes to verify digital-evidence integrity and detect tampering.

Chapter ties. Ch 15 (MD5 Hash Function, SHA-256 Hash Function, Hash Verification, Forensic Imaging Process, Bit-Stream Copy, Write-Blocker Hardware).

Supplies. None — a laptop and a browser. Assumes access to one computer per group.

MicroSim spec. New in-browser hashing widget (HTML/JS): a text box + createButton('Hash') computing MD5 and SHA-256 live; a "tamper" toggle flips one byte and highlights the avalanche effect; a compare mode checks two files' hashes and reports match/mismatch. Reuse forensic-imaging-workflow for the chain-of-custody framing.

24. Metadata Detective — EXIF Geolocation 💻¶

Description. A suspect claims they were home all day. Students inspect the EXIF metadata of a set of provided photos (timestamps, GPS coordinates, device model), plot the coordinates on a map, and build a timeline that contradicts the alibi. A MicroSim provides the metadata viewer and timeline builder so no personal photos are needed.

Learning objective. Extract and interpret EXIF timestamp and geolocation metadata to reconstruct a timeline and test an alibi.

Chapter ties. Ch 15 (EXIF Metadata Recovery, Digital Timestamp Analysis, Geolocation from Metadata); Ch 18 (Image Metadata in Social Media, Geolocation from Social Posts).

MicroSim spec. Reuse metadata-timeline-builder. New optional map-plot step (Leaflet/plotly): drops EXIF GPS points on a map and animates the timeline; createSlider() scrubs time, and a createCheckbox toggles the suspect's claimed location.

25. Locate the Phone — Cell Tower Triangulation 💻¶

Description. Call Detail Records place a suspect's phone on three towers during the crime window. Students use signal-strength/timing data to triangulate the phone's probable location, then compare it to the suspect's claimed whereabouts — learning both the power and the uncertainty (sector, not point) of tower geolocation.

Learning objective. Estimate a mobile device's location from cell-tower records using triangulation and describe the precision limits of the method.

Chapter ties. Ch 17 (Cell Tower Records, Call Detail Records, Tower Triangulation, IMEI Device Identification, GPS Location Data).

MicroSim spec. Reuse cdr-tower-triangulation. Frame with a /story-generator narrative that hands students a CDR table and asks them to place the phone and write a probable-location statement with an explicit uncertainty radius.

Description. From seized call logs and social-media connections, students build a network graph of a suspected crew, then use degree and betweenness to identify the ringleader and the key broker connecting two cells — an OSINT investigation that shows how structure, not just content, reveals roles.

Learning objective. Construct a social network from communication records and use centrality measures to identify key actors in a criminal network.

Chapter ties. Ch 18 (Social Network Analysis, Social Media Forensics, OSINT, Open-Source Intelligence); Ch 17 (Call Detail Records).

MicroSim spec. Reuse social-network-analysis. Provide an edge-list evidence card; students enter connections, the sim renders the graph and highlights the highest-centrality node as the "person of interest."

27. Reconstructing the Debris Field — Aviation Forensics 💻¶

Description. A capstone-scale investigation. Students examine a debris-field scatter plot from a crash, classify the pattern as an in-flight breakup vs. intact impact, sequence the wreckage to infer break-up order, and combine it with radar/ADS-B path data to propose a probable-cause hypothesis — running the NTSB party-system workflow end to end.

Learning objective. Interpret a debris-field distribution to distinguish in-flight breakup from intact impact and integrate flight-path data into a probable-cause hypothesis.

Chapter ties. Ch 19 (Debris Field Analysis, In-Flight Breakup vs. Intact Impact, Wreckage Reconstruction, Radar/ADS-B Path Reconstruction, Probable Cause, NTSB Party System).

MicroSim spec. Reuse debris-field-pattern-explorer, ntsb-investigation-workflow, and aviation-crash-investigation-timeline in a three-stage story: field analysis → workflow roles → timeline synthesis.

28. Face in the Crowd — Recognition & Algorithmic Bias 💻¶

Description. Students step through a facial-recognition pipeline (detect → landmark → encode → match) on sample faces, then run a short "audit" scenario where the system's confidence differs across demographic groups — surfacing algorithmic bias and why a face match is investigative lead, not proof. A discussion-and-decision story caps it with an admissibility judgment.

Learning objective. Trace the stages of a facial-recognition pipeline and evaluate the reliability and bias limitations of face-match evidence.

Chapter ties. Ch 16 (Facial Recognition Overview, Facial Landmark Detection, Face Detection Algorithms, Algorithmic Bias in Facial Recognition, Facial Recognition Admissibility, CCTV Surveillance Analysis).

MicroSim spec. Reuse facial-recognition-pipeline. Add a /story-generator scenario where students receive candidate match scores with per-group error rates and must decide whether the match justifies an arrest — with branching consequences that teach the bias lesson.

Suggested rotations & capstones¶

Mix and match by course goal:

One-day crime-lab carousel (intro): #1 Locard, #3 Prints, #21 Ink Chromatography, #11 Blood Typing — four cheap physical stations, ~20 min each.
BPA deep-dive block: #12 Angle of Impact → #13 Stringing the Scene.
DNA week: #14 Extraction + STR → #15 Random Match Probability (mock trial).
Digital-forensics unit: #23 Hash Integrity → #24 EXIF Metadata → #25 Tower Triangulation → #26 Social Network Analysis.
Semester capstone: a single staged "cold case" that requires evidence from #3, #5, #9, #14, and #24 to convict — students rotate roles as the lab team.

Lab type	Investigations
🧪 Physical	#1, #2, #3, #6, #9, #10, #11, #20, #21
💻 Virtual	#4, #15, #17, #24, #25, #26, #27, #28
🔀 Combination	#5, #7, #8, #12, #13, #14, #16, #18, #19, #22, #23

Trace's advice for teachers

Start every investigation with the question, not the procedure. Hand students the mystery — "Which of these three suspects was at the scene?" — and let the evidence answer it. That's when forensic science stops feeling like a worksheet and starts feeling like the real thing. Follow the evidence!