CEH Anki Spaced Repetition Schedule (3-Week Sprint)

Purpose: 21-day spaced repetition plan that pairs with 02-3-week-sprint-plan.md. Tuned for the 133-card ceh-deck.apkg (9 CEH domains, 45 cards already tagged exam-must). Daily commitment: ~15-25 minutes of Anki within your existing 90-min AM block. Labs and reading stay primary; Anki reinforces. Goal: 70-90% recall accuracy on every card by Day 14, with the 45 exam-must cards at >85% by Day 19.

1. Background - Why This Schedule Works

The Ebbinghaus Forgetting Curve

Hermann Ebbinghaus (1885) showed that without review, new information decays exponentially: roughly 40% forgotten within 20 minutes, ~60% within 24 hours, and ~75% within 6 days. The decay is a steep cliff, not a linear slope. The remedy Ebbinghaus discovered: review at the moment you are about to forget. Each successful recall flattens the curve for that item. For a 21-day CEH sprint, the math is brutal - a card studied on Day 1 and never reviewed is near-zero recall by Day 21. The same card reviewed three times in the first 10 days retains ~80% at Day 21 (Ebbinghaus, Memory: A Contribution to Experimental Psychology, 1885/1913).

The SM-2 Algorithm

Anki defaults to SM-2 (SuperMemo 2), designed by Piotr Woźniak in the mid-1980s. Every card carries an E-Factor (ease) starting at 2.5 (250%), an interval (in days), and a repetition count. The four buttons:

Again (forgot) → reset to learning steps, ease drops by 0.20
Hard (recalled with effort) → interval × 1.2, ease drops by 0.15
Good (recalled normally) → interval × E-Factor, ease unchanged
Easy (effortless) → interval × E-Factor × 1.3 bonus, ease rises by 0.15

After two successful recalls, intervals become previous_interval × E-Factor. With E-Factor = 2.5: 1 day → 6 days → 15 days → 38 days. SM-2 schedules a card just before you would forget it, producing the expanding-interval cadence that makes 21 days enough to cover 133 cards (Wozniak, “Optimization of Learning,” 1990).

The 70-90% Recall Target

Spaced repetition is calibrated to a target retention. Karpicke & Roediger (2006) showed that taking a test (recall) dramatically outperforms re-reading for long-term retention, and that the effect compounds when retrieval is repeated. The optimal target is to recall each card at ~80-90% accuracy when Anki surfaces it - high enough to be confident under exam pressure, low enough that you’re not reviewing already-mastered material every day. For the CEH, where the pass threshold is variable (60-85% depending on form), I set the target higher than normal: 70% on Day 7, 85% on Day 14, 90%+ on Day 19. This is conservative but matches the “90% on practice tests” target in the sprint plan.

The Cepeda et al. 2006 Meta-Analysis

Cepeda, Pashler, Vul, Wixted & Rohrer (2006) synthesized 254 studies on distributed practice and concluded that longer inter-study intervals produce better long-term retention when total study time is held constant. Critically, the optimal gap between reviews scales with how long you need to remember - for a 3-week sprint, the algorithm should compress intervals (more reviews per day) rather than stretch them. Anki’s defaults handle this automatically if you start early, which is why Day 1 is the most important day of the sprint.

2. 21-Day Schedule

The 133-card deck is fully introduced by end of Day 7. Days 8-17 are pure review (decks get smaller each day as cards graduate to long intervals). Days 18-19 are last-mile - only exam-must cards. Day 20 = NO Anki (rest). Day 21 = NO Anki (exam day).

Day	New	Reviews	Time	Focus domain
1	15	0	5 min	Recon (D3.A) - Nmap flags, OSINT, enumeration primers
2	20	12	10 min	Recon continued - port scan types, host discovery
3	20	30	14 min	Threats & Kill Chain (D1-D2) - APTs, MITRE ATT&CK, Lockheed
4	20	45	18 min	Web/OWASP intro (D3.C) - Top 10 2021, A01-A05
5	20	60	22 min	Web attacks (D3.C peak) - SQLi, XSS, SSRF, IDOR
6	20	75	26 min	Cryptography (D5) - RSA, ECC, AES, SHA, PKI
7	18	85	28 min	Wireless/IoT/OT (D3.B) - finish new card pool; Set A mock
8	0	110	30 min	All-domain review (highest-volume day; cap is 200)
9	0	100	28 min	Crypto + SG law (CMCA, PDPA, CSA)
10	0	90	25 min	Cloud + Defense (D4) - shared-responsibility, SIEM/SOAR
11	0	85	24 min	Network attacks (D3.B) - DoS, ARP, MITM
12	0	80	22 min	Methodology (D6) - PTES, RoE, pen-test phases
13	0	75	21 min	All-domain; Set B mock in PM block
14	0	70	20 min	Targeted review of cards still <70% accuracy
15	0	65	18 min	D3.C reinforcement (web/app focus)
16	0	60	17 min	D3.B + D4 reinforcement (network + defense)
17	0	55	16 min	Crypto + SG law final pass; Set A re-take
18	0	40 (`exam-must`)	12 min	Last-mile - `exam-must` only
19	0	30 (`exam-must`)	10 min	Last-mile - `exam-must` only + missed-list
20	0	0	0	REST DAY. No Anki. Sleep 8+ hrs.
21	0	0	0	EXAM DAY. No Anki. Light breakfast, walk, exam.

Total Anki time across 21 days: ~6 hours. Total exposure per card: 7-10 reps.

3. Recommended Anki Settings

Configure these once before Day 1. These are Anki defaults with two conservative overrides (max reviews = 200; starting ease = 250%).

Setting	Value	Why
New cards/day limit	25 (week 1) → 20 (week 2) → 15 (week 3)	Caps the daily learning cost so the algorithm doesn’t pile up 100+ new cards on a single day
Max reviews/day	200	Hard ceiling so Anki never blocks your morning; you’ll hit ~110 on the worst day
Learning steps	1 min, 10 min	Two-step learning; cards graduate after the second success
Graduating interval	1 day	Cards leaving learning step 2 graduate to a 1-day review
Easy interval	4 days	“Easy” button bypasses learning steps entirely
Starting ease	250% (2.5)	SM-2 default; do not raise - you’ll skip cards that need reinforcement
Max interval	365 days	Irrelevant for 21-day sprint but keeps mature cards from vanishing for a year
Algorithm	SM-2 (default)	Don’t switch to FSRS - the 21-day timeline is too short for FSRS to calibrate its difficulty parameter

Deck-level overrides: Create a sub-deck called Last-Mile containing only exam-must cards. Set its new-card limit to 0 for Days 1-17 and its review limit to 50. Days 18-19, study only this deck. This guarantees no new cards sneak in late and the 45 high-leverage cards get a clean final pass.

4. Card-Tagging Strategy

The deck already uses topic tags (e.g., nmap, owasp, crypto, kill-chain). Add three more tags and apply them in a single 60-minute pass on Day 1:

Tag	Apply to	Count (approx.)	Purpose
`exam-must`	Cards whose content is in the 50% high-leverage list (Nmap flags, OWASP Top 10, ports, tool recognition, crypto algorithms, Kill Chain phases)	~45 (already tagged in the deck CSV)	Last-mile priority on Days 18-19
`quick-review`	Cards you answer correctly on first sight - definitions, simple fact lookups, port numbers	varies	Skim fast (~2 sec/card) on review days; don’t waste time
`tough`	Cards you answer “Again” or “Hard” twice in a row - abstract concepts (PKI chain validation, Diamond Model, MITRE tactic ordering)	varies	Surface these daily until they graduate; consider re-writing the card with a clearer mnemonic

A card can wear multiple tags. The exam-must filter in Days 18-19 is your single most important move - it ensures the highest-yield 45 cards are the freshest in your head on exam morning.

5. Last-Mile Anki (Days 18-21)

The 72 hours before the exam are the highest-leverage hours of the entire sprint. Use them surgically:

Day 18 (~12 min): Study only the exam-must filtered deck (~45 cards × one pass). Do not touch any other cards. Your retention curve on these 45 cards should be ~85%+ by now; this is reinforcement.
Day 19 (~10 min): Same filtered deck. Plus: re-add any card you marked tough and missed in the last 3 days. Total ~30 cards.
Day 20 (0 min): NO ANKI. Sleep 8+ hours. Walk. Pack your bag. Trust the algorithm.
Day 21 morning (0 min): NO ANKI. Light breakfast, water, passport, confirmation email. Arrive 30 min early.

Resist the urge to “cram” on Day 20. SM-2 has already scheduled the review curve. Cramming new information 12 hours before an exam displaces sleep and consolidates the wrong memories (Karpicke & Roediger, 2006).

6. Common Anki Pitfalls

The “Again” trap. Don’t press Again just because the card took 8 seconds. If you recalled it with effort but produced the answer, press Hard. Over-using Again inflates the queue and triggers a death-spiral where the same 20 cards recycle for hours. The rule: Again only if you could not have produced the answer under exam pressure.
Reviewing on autopilot. Mindless clicking through cards during a Zoom call is worse than no review - it inflates your “Good” count without consolidating memory. Either give Anki full attention or close the app.
Skipping the “Hard” button. Anki’s default 4-button layout tempts users to only use Again/Good/Easy. The Hard button is your friend: it bumps the interval modestly without tanking the E-Factor. Use it generously on cards that took >5 seconds.
Re-reading instead of recalling. When you flip the card, the answer appears. Close your eyes and recite it aloud before reading. Silent recall builds the testing-effect pathway; visual reading does not (Roediger & Karpicke, 2006).
Adding too many new cards on Day 1. The Day 1 cap is 15, not 25. Binge-loading 50 new cards on Day 1 will drown you in reviews by Day 4 and you’ll abandon the schedule. Ramp gradually.
Editing cards instead of answering them. If a card is ambiguous, mark it and move on. Edit cards in a single 30-min session on Day 8, not in the middle of a review session. Editing breaks the algorithm’s calibration.

7. What If I Fall Behind

Gap	Action
Miss 1 day	Skip it. Don’t double up. The algorithm handles one missed day cleanly. Resume at the original pace.
Miss 2-3 days	On return, halve the new-card limit (15 → 7, 20 → 10) until reviews drop below 100/day. Don’t reset; just slow the front-loading.
Miss 4+ days	Reset. `Forget all cards` on the deck, restart with `exam-must` only (~45 cards). Add the remaining 88 cards at 15/day starting Day 1 of the new schedule. This is brutal but better than carrying 200+ overdue reviews into exam week.
Behind on Day 14 score (<75%)	Drop the new-card introduction entirely. Pure review of `exam-must` + your weakest domain from the sprint plan’s 50% high-leverage list. Consider rescheduling the exam by 7 days ($0 if ≥48h ahead of Pearson VUE slot).

The single most important rule: never try to “catch up” by doing 300 reviews in one sitting. The retention curve rewards consistency, not binge-reviewing. Cepeda et al. (2006) show distributed practice outperforms massed practice even when total study time is equal - and binge-reviewing is massed practice.

8. Anki Alternatives (If Anki Feels Heavy)

If the desktop Anki client feels like too much friction (it does for some learners), here are alternatives - with an honest recommendation:

Tool	Free?	Algorithm	Tradeoff
Quizlet	Freemium	Basic SRS (confidence-based)	Worse algorithm; less control; their free tier is limited
RemNote	Free tier	Built-in SM-2 variant	Better for note-taking; weaker for pure flashcards
SuperMemo	Paid (~$30)	SM-17 / SM-18 (ancestors of SM-2)	Original algorithm; steeper learning curve; no AnkiWeb sync
Mochi	Freemium	Custom	Beautiful UI; smaller user base; weaker mobile app
Paper index cards	Free	You run the algorithm manually (1d, 3d, 7d, 14d)	Zero friction; portable; but no automatic scheduling - you’ll skip days

Recommendation: stick with Anki. Free, correct algorithm, solid mobile app, AnkiWeb sync for commute reviews. Switching tools mid-sprint costs more than the friction saves. If Anki feels too heavy, the fix is fewer cards per day, not a different tool.

Sources

Ebbinghaus, H. (1885/1913). Memory: A Contribution to Experimental Psychology. Teachers College, Columbia University. Original forgetting-curve experiments: ~40% retention at 20 min, ~60% at 24 hr, ~75% at 6 days without review.
Roediger, H. L., & Karpicke, J. D. (2006). Test-Enhanced Learning: Taking Memory Tests Improves Long-Term Retention. Psychological Science, 17(3), 249-255. DOI: 10.1111/j.1467-9280.2006.01693.x. Four experiments showing retrieval practice (testing) outperforms repeated study for long-term retention, even when total time is equated.
Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed Practice in Verbal Recall Tasks: A Review and Quantitative Synthesis. Psychological Bulletin, 132(3), 354-380. DOI: 10.1037/0033-2909.132.3.354. Meta-analysis of 254 studies - distributed practice consistently beats massed practice; optimal inter-study interval scales with retention window.
Wozniak, P. (1990). Optimization of Learning. Internal SuperMemo publication. SM-2 algorithm specification: ease factor starts at 2.5, intervals multiply by E-Factor on Good answer, ease decreases by 0.20 on Again. Available at https://super-memory.com/english/ol/sm2.htm.
Karpicke, J. D., & Blunt, J. R. (2011). Retrieval Practice Produces More Learning than Elaborative Studying with Concept Mapping. Science, 331(6018), 772-775. DOI: 10.1126/science.1199327. (Supplementary - supports the 70-90% recall target and validates test-based learning over re-reading.)

Aligned with 02-3-week-sprint-plan.md. The Anki block fits inside the 90-min AM session as the first 15-30 minutes, leaving the remainder for reading and lab work. Total Anki time across the sprint: ~6 hours. The rest of the ~65-70 study hours goes to labs, mocks, and reading.