How to Create AI Flashcards from Reading Highlights Using Glasp for Exam Preparation

Active recall and spaced repetition are the most effective study techniques backed by cognitive science research, yet most students still rely on passive re-reading for exam preparation. Glasp bridges this gap by automatically converting your reading highlights into flashcards for spaced repetition learning. This tutorial covers the complete workflow for using Glasp as a study tool for exam preparation.

Step 1: Set Up Your Study Workflow

Install the Glasp browser extension and create a dedicated tag for your current study topic — for example, “bio-101-exam” or “machine-learning-midterm.” This tag will collect all highlights relevant to your exam preparation in one place. Create a consistent highlighting strategy: use yellow for key definitions, green for important processes or sequences, and blue for concepts you find difficult and want to review more frequently.

Step 2: Highlight Study Materials Systematically

As you read textbooks, lecture notes, research papers, and online resources, highlight key information systematically. Focus on definitions, formulas, cause-and-effect relationships, and comparison points — these are the types of information that make effective flashcards. Add a brief note to each highlight explaining why it’s important or how it connects to other concepts. This note becomes the “answer context” on your flashcards, providing deeper understanding than a simple Q&A format.

Step 3: Generate AI Flashcards

After accumulating highlights from a study session, navigate to your Glasp profile and click the “Flashcards” tab. Select the tag for your current study topic and click “Generate Flashcards.” Glasp’s AI analyzes your highlights and creates flashcard pairs — a question on one side and the answer on the other. The AI extracts key concepts from your highlights and formulates questions that test understanding rather than just memorization. Review the generated flashcards and edit any that are unclear or incorrectly formulated.

Step 4: Review Flashcards with Spaced Repetition

Glasp’s flashcard system includes a built-in spaced repetition scheduler. After reviewing a card, rate your confidence level (Easy, Good, Hard, or Again). Cards rated as difficult will appear more frequently in future review sessions, while easy cards are shown less often. This algorithm ensures you spend more time on the material you haven’t mastered yet, optimizing your study efficiency. Aim for daily review sessions of 10-15 minutes to maintain retention without overwhelming your schedule.

Step 5: Create Thematic Flashcard Decks

For comprehensive exam preparation, organize your flashcards into thematic decks. For example, if you’re studying biology, create separate decks for “Cell Biology,” “Genetics,” and “Ecology.” Use Glasp’s tag system to filter highlights by theme before generating flashcards. This thematic organization makes it easy to focus your study sessions on specific topics and track your progress by subject area. You can also merge decks for comprehensive review sessions as the exam approaches.

Step 6: Collaborate with Study Groups

Glasp’s social features extend to flashcards. Share your flashcard decks with study group members by clicking “Share” on the deck and sending the link. Your group members can review the same flashcards, add their own highlights and flashcards, and build a collaborative study resource. This is particularly effective for courses where different students focus on different aspects of the material — the combined deck covers more ground than any individual could create alone.

Best Practices

• Highlight with flashcard creation in mind — focus on self-contained facts and concepts that can be formulated as clear questions.
• Review AI-generated flashcards before studying — the AI sometimes misinterprets context or creates ambiguous questions.
• Maintain a daily review habit — spaced repetition is only effective when reviews are consistent.
• Use the difficulty rating honestly — marking everything as “Easy” defeats the purpose of the algorithm.