Generate Study Flashcards & Questions with AI

The SOJT Framework

Use this Situation, Objective, Knowledge, Task framework to generate comprehensive flashcards. It tells the AI exactly who it is working with, what to achieve, what material to use, and how to structure the output.

The Flashcard Prompt Template

Situation: You are working with an uploaded document that contains
academic material I need to study.

Task: Extract all key concepts from the uploaded document, then generate
comprehensive flashcard questions and answers that cover all key
concepts, topics, and details present in the material.

Objective: Create a complete, exhaustive set of flashcard questions and
answers that can be used for studying and retention.

Requirements:
- Include questions that test different levels of understanding:
  * Definition level — "What is X?"
  * Application level — "How would you use X in scenario Y?"
  * Analysis level — "Compare X and Y. What are the differences?"
  * Evaluation level — "Why is X preferred over Y in context Z?"
- Cover all major topics, concepts, terms, and ideas
- Ensure questions are clear and answers are accurate and concise
- Present in a structured format with clear Q/A separation

How to Run It (Step by Step)

1. Upload your document (PDF, slides, or pasted text) to ChatGPT, Claude, or Gemini
2. Paste the flashcard prompt template and press Enter
3. Review the generated Q/A pairs and delete any that feel trivial
4. Ask for a second pass: "Generate 10 harder application-level questions"
5. Copy the final set into your flashcard app or notes

Four Levels of Understanding

Good flashcards test more than memorization. Include questions at all four levels:

1. Definition: "What is the TDMS?" — Tests basic recall
2. Application: "How would you use Boolean search strings to find papers on climate change?" — Tests practical use
3. Analysis: "Compare Perplexity and Google Scholar for literature reviews. What are the strengths and limitations of each?" — Tests deeper thinking
4. Evaluation: "In what situations would you choose Research Rabbit over direct database searches?" — Tests critical judgment

Processing Tips

• Split large documents — Process one chapter at a time for better coverage
• Include your lecture notes — Upload both the textbook and your notes for comprehensive coverage
• Request frequency markers — Ask: "Flag flashcards covering concepts that are likely to be examined"
• Generate progressively — Start with Definition level, then add harder questions

Worked Example: Sample Card Set

Here is what a small, well-balanced set looks like for a literature-review topic (Boolean search for papers on climate change):

Q1 (Definition): What is the AND operator in Boolean search?
A1: It narrows results — only papers containing BOTH terms return.

Q2 (Application): Build a search string to find empirical papers
    on climate change in Ghana.
A2: "climate change" AND Ghana AND "empirical study"

Q3 (Analysis): Compare AND and OR operators. When is each used?
A3: AND narrows (both terms required); OR broadens (either term
    matches). Use AND to focus, OR to capture synonyms.

Q4 (Evaluation): Why would you use Research Rabbit over a plain
    database search for finding related literature?
A4: It maps the citation network visually, surfacing papers you
    would never discover with keyword searching alone.

Notice the answer lengths: definition cards are short, evaluation cards justify a choice. Keep answers under 15 words where possible.

Organizing Decks by Course

• Create one Anki deck per course: MGMT401, ECON202, COMP151
• Add tags so you can filter: #week3, #formula, #examLikely
• Name each card consistently: "Ch4: Population vs Sample"
• Keep a separate "Syllabus Gaps" deck for topics with zero cards

Common Flashcard Mistakes & How to Avoid Them

• Making every card a "What is X?" card — force Application, Analysis, and Evaluation questions into the prompt so exams don't surprise you.
• Overloading one card — one fact per card. If an answer has two unrelated facts, split it into two cards.
• Copying definitions verbatim — ask the AI to rewrite answers "in the words of a student explaining to a friend" so you actually understand them.
• Building 500 cards in one night — space it out; Anki's algorithm works best with steady daily reviews.
• Never reviewing — cards only help if you open the app daily. Set a 10-minute daily habit instead of weekend marathons.
• Trusting unverified facts — require page references and delete anything you can't find in the source.

The Workshop Method: PASCO Flashcards in One Prompt

The workshop method generates a complete question bank from any uploaded document in a single pass:

1. Get an AI research assistant — DeepSeek, ChatGPT, Grok, Gemini or MiniMax.
2. Activate web search / think longer, then upload your document(s) with this exact prompt:

Generate all possible flashcard questions and answers.
Note: include questions already in the uploaded document.
Don't forget to reference.

Every question set comes out referenced to your source, so you can verify each card.

Flashcard Apps for Mobile

• Android — DeepSeek: Play Store · ChatGPT: Play Store
• iOS — DeepSeek: App Store · ChatGPT: App Store

Using AI for Spaced Repetition

After generating your flashcards, import them into a spaced-repetition tool so the app schedules reviews right before you forget:

Bulk Import: Ask for CSV Output

Ask the AI to format the output so you can import it in bulk:

Output every flashcard as one row of a CSV with two columns:
"front","back". No headers, no extra text, no markdown.
Escape any commas inside the fields by wrapping them in quotes.
I will import this directly into Anki.

In Anki: File → Import → select the .txt or .csv file → choose the fields (Front / Back) → Import. In Quizlet: Create set → Import → paste the two-column text → select the separator.

Cloze Deletion Cards

Cloze cards hide a key word inside a sentence ("The capital of Ghana is ____"), which is scientifically shown to aid recall better than plain Q/A for definitions:

Convert these 20 definitions into cloze deletion cards.
Format each as: Sentence with the key term replaced by {{c1::term}}.
Example: Ghana's national currency is the {{c1::Ghana Cedi}}.

Anki supports cloze directly via the "Cloze" card type — paste {{c1::...}} markup into the Front field.

Choosing Between Card Types

Question Design with Bloom's Taxonomy

For exam-ready coverage, ask the AI to explicitly map questions to Bloom's levels:

• Remember — "List the three layers of a neural network."
• Understand — "Explain why learning rate affects convergence."
• Apply — "Which tool would you use to find open-access PDFs?"
• Analyze — "Break down the methodology of study X and identify its assumptions."
• Evaluate — "Judge whether approach A or B is more ethical, and why."
• Create — "Design a 3-step experiment to test hypothesis Y."

Quality Control: Verifying Generated Questions

• Check for invented facts — ask: "Cite the page or section each answer comes from."
• Remove duplicates — ask: "Remove any questions that test the same fact twice."
• Demand exam relevance — tell the AI which topics your lecturer emphasized.
• Fix ambiguous wording — ask: "Rewrite any question with two possible answers."

Anki Settings for Maximum Retention

Default Anki settings work, but these tweaks dramatically improve retention:

What Anki Actually Costs in 2026 (Read This Before You Install)

The pricing picture changed recently and a lot of blog posts have it wrong. Here is the verified situation:

On iPhone? You can still use the full free workflow: build and edit decks on a desktop or on Android, and use the free AnkiWeb sync. If you only have an iPhone, AnkiMobile's one-time $24.99 buys you the same FSRS scheduling everywhere rather than a locked-in subscription.

FSRS vs the Old SM-2 Algorithm — and Why It Matters

Anki has shipped two schedulers. Understanding the difference tells you whether you have actually configured anything:

• SM-2 is the 1987 SuperMemo-2 algorithm. It multiplies a card's interval by a single global "ease factor" every time you answer Good. Every card with the same ease factor is treated identically, regardless of how well you actually remember that specific fact.
• FSRS (available since Anki 23.10, and enabled per-deck in Deck Options) models each card individually with three values — Difficulty, Retrievability and Stability — and fits those to your own review history using machine learning.
• Why FSRS wins in practice: fewer wasted reviews at the same retention level, and far better handling of cards you reviewed late — which is exactly what happens to every student who takes a study break and comes back.
• The only setting you should touch: desired retention. You are meant to set a target recall probability (90% is the usual default) rather than hand-tuning the parameters — the Anki team explicitly advises against editing them manually.

Bulk Generation Across Many Documents

When you have 5 lectures or 5 papers, generate in one pass for a unified deck:

I'm uploading 5 lecture slide decks [FILES]. For the whole set:
1. Generate 15 cards per deck (75 total)
2. Tag each card with its source deck: #lecture1..#lecture5
3. Remove cards that test the same fact in two decks
4. Output as CSV with "front","back","tags" columns

Anki imports the tags column automatically — just map the fields in the import dialog. For true one-click automation, power users also use the AnkiConnect add-on with an AI script, but the CSV route is enough for most students.

Ready-to-Use Template Library

Template 1: Full Question Bank Builder

From this document [FILE], build a 40-card question bank:
- 10 definition cards (one fact each)
- 10 application cards (use the concept in a scenario)
- 10 analysis cards (compare / contrast two concepts)
- 10 evaluation cards (justify a choice in a given context)
Output as CSV with "front","back" columns. Mark the 5 cards most
likely to appear in an exam with [EXAM].

Template 2: Cloze Deletion Converter

Convert my existing notes [PASTE NOTES] into 25 cloze deletion cards.
For each: take the most important sentence, replace the key term or
phrase with {{c1::term}}, and put the full sentence on the front.
Group them by topic with headings.

Template 3: Exam Simulation

Using these flashcards [PASTE SET], generate a 20-minute mock exam:
- 10 questions from the Definition and Application levels
- 5 questions from Analysis
- 5 questions from Evaluation
After I answer, score me, explain each mark, and list my weakest
concepts with the matching flashcards to restudy.

Template 4: Syllabus Coverage Mapper

Here is my course outline [FILE A] and my generated flashcards
[PASTE SET]. Map every outline topic to the flashcards that cover it.
List any outline topic with ZERO flashcards so I can generate more
questions for it.

The Complete Flashcard QA Checklist

• Document uploaded — single chapter or paper for focus
• SOJT prompt used — situation, task, objective, requirements set
• All 4 levels covered — definition, application, analysis, evaluation
• ≥20% hard questions — Analysis/Evaluation present
• Bloom's mix requested — 40/30/30 distribution asked
• Facts verified — page references requested and checked
• Duplicates removed — second pass deduplication done
• Ambiguous cards fixed — one possible answer per question
• CSV generated — "front","back" columns ready
• Imported into Anki/Quizlet — spaced repetition scheduled
• Cloze cards added — 25 cloze deletions for definitions
• Exam simulation run — 20-minute mock attempted
• Syllabus mapped — every outline topic has coverage

Troubleshooting FAQ

• "The AI only makes basic 'What is X?' cards" — Re-paste the Requirements block that forces Application, Analysis, and Evaluation questions.
• "My CSV import fails in Anki" — Use two columns only, escape commas with quotes, and save the file as UTF-8.
• "The answers are too long" — Add "keep every answer under 15 words" to the prompt.
• "Cards repeat the same fact" — Ask: "Remove any question that tests the same fact twice."
• "The AI invented a term" — Require page references and delete anything you cannot verify.
• "Quizlet won't accept my paste" — Use tab-separated text (front [Tab] back) instead of commas.
• "I have 500 cards — too many" — Ask the AI to rank cards by exam likelihood and keep the top 150.
• "Cloze markup shows literally in Anki" — Make sure the card type is set to Cloze, not Basic.
• "I want images or audio on my cards" — Ask the AI to leave a placeholder line like [IMAGE: labelled diagram of the neuron], then add the media in Anki's editor. Anki also reads [sound:file.mp3] tags if you add the audio files to the deck folder.
• "I'm overwhelmed by review counts" — Lower "New cards/day" to 10 for a week. Reviews are capped by how many new cards you introduce, so the backlog will shrink by itself.
• "Cards come out in the wrong language" — Add to the prompt: "Answer in English. Keep any quoted terms in their original language, then explain them in English."

Bonus: A 2-Week Exam Study Plan

Week 1 — Build & learn
Day 1-3: Generate cards per topic (SOJT prompt), verify facts,
          import into Anki, set FSRS on
Day 4-6: Review daily (20-30 new cards/day), fix awkward cards
Day 7:    Run the exam simulation (Template 3), score yourself

Week 2 — Consolidate
Day 8-10: Review only your weakest concepts + their cards
Day 11-12: Run a second exam simulation on the weak topics
Day 13:   Re-read the syllabus map; generate any missing cards
Day 14:   Light review — 50 old cards + flagged [EXAM] cards only

Extra Resources

• AnkiWeb (ankiweb.net) — sync your decks free across phone, tablet, and desktop
• Anki decks for KNUST-style courses — search AnkiWeb for "pharmacology", "engineering math", etc. to find pre-made shared decks
• Quizlet "Learn" mode — AI-guided study that adapts questions to your weak areas
• RemNote (remnote.com) — turn PDF highlights into cards automatically
• FSRS-rs / AnkiFSRS — the open-source scheduler now built into Anki (Settings → FSRS)
• ANKI 20 rules — the classic "20 rules of formulating knowledge" guide for writing better cards
• AnkiConnect — a free add-on that lets other apps (and AI tools) add cards to Anki automatically
• HowTo Study / Study Together communities — accountability groups and shared decks for common KNUST courses