Turn PDFs, slides and videos into interactive lessons with AI

What should “interactive” mean?

Most people searching for a way to convert a PDF to an interactive lesson have a pile of good material that learners skim and forget: handouts, slide decks, recorded lectures, question banks. The word “interactive” gets stretched to cover a “next” button, a flip card or an animation. Those are motion, not interaction.

A useful definition comes from Chi and Wylie’s ICAP framework, published in Educational Psychologist in 2014. It sorts learning activities by what the learner visibly does: passive (receiving), active (manipulating, such as highlighting, pausing or picking from a menu), constructive (generating something beyond the material, such as a prediction or a self-explanation) and interactive (a dialogue with frequent turns where both sides contribute; the partner can be a computer agent that responds to the content). Their hypothesis, supported by the studies they review, is that learning increases in that order. Clicking through slides is passive. Even choosing an answer from a menu is, in their terms, only active.

So for this guide, an interactive lesson has four ingredients:

1. A question after each idea, not a quiz at the end of the chapter.
2. Feedback on the actual answer, including why a specific wrong answer is wrong.
3. Remediation: a hint first, then a second explanation, then a return to the idea later if it stayed weak.
4. Room to ask: the learner can raise their own question about what is in front of them.

The evidence behind these ingredients is solid. Freeman and colleagues’ 2014 meta-analysis in PNAS pooled 225 studies of undergraduate STEM courses. Average exam scores were about 6% higher under active learning, and students in traditional lectures were 1.5 times more likely to fail. Separately, Roediger and Karpicke (2006, Psychological Science) showed the testing effect: students who practiced recalling a passage remembered substantially more two days and a week later than students who reread it, even though rereading made them more confident. A question after each idea is retrieval practice built into the lesson. For more ways to check, see Checking for understanding: 12 techniques that work online.

How to convert a PDF into an interactive lesson, step by step

The same process works whether you use an authoring tool, an AI generator or a live AI tutor. Only the tool at step 5 changes.

1. 1

   Audit what you have

   List every asset for the course: PDFs, scans, decks, recordings, web pages, question banks. Note which is the most accurate and most current version of each topic. Conflicting sources produce conflicting lessons.
2. 2

   Pick one unit

   Choose a unit where learners struggle and the material is stable. One chapter of 5 to 15 pages or slides is enough to learn the process.
3. 3

   Clean the sources

   Rescan faint or crooked pages. Correct the video transcript’s technical terms. Add speaker notes to slides that are only pictures or keywords. Remove pages you would not teach from.
4. 4

   Write the objectives

   Three to five lines of “by the end, the learner can…”, each one checkable. If you cannot write a question for an objective, it is not an objective yet.
5. 5

   Generate the draft

   Let the tool split the unit into topics and concepts and draft explanations, diagrams, checks and hints. Keep the source attached so you can trace every claim.
6. 6

   Review boards, diagrams and checks

   Read it as the learner would. Check every number, formula, label and answer key. Replace generic hints with the mistakes your learners really make.
7. 7

   Pilot with real learners

   Give it to 15 to 20 learners from the actual audience, not colleagues. Watch where they fail checks, where they ask questions and where they stop.
8. 8

   Iterate, then scale

   Fix the source or the check behind each problem and regenerate that part. Once the unit holds up, convert the next ones using what you learned.

How each format converts

Different sources fail in different ways. Most of the preparation work is knowing which.

On scans, the documentation for the open-source Tesseract OCR engine is blunt. It says the engine “works best on images which have a DPI of at least 300 dpi,” that skewed pages significantly reduce the quality of line segmentation, and that dark scanning borders can be misread as characters. Whatever OCR your tool uses, a crooked photocopy of a photocopy will produce errors, and the ones that do the most damage are in numbers, units and symbols.

What AI does well, and what a human must review

Generation is the fast part. Review is where lesson quality is decided. Split the work like this:

The research on AI tutors points the same way. In the 2025 Harvard physics trial by Kestin and colleagues in Scientific Reports, the tutor’s accuracy came from step-by-step solutions the instructors wrote into its prompts, rather than from the model working problems out alone. Even dedicated generators state their limits: H5P’s help center says its Smart Import feature currently ignores mathematical equations, chemical reactions, physics numericals and diagrams. For how to keep a live tutor faithful to reviewed material, read Will an AI tutor make things up?

What a conversion pipeline looks like

Whatever tool you use, a sound pipeline turns sources into a reviewable plan before any learner sees a lesson. Tutezy is one example of this design, so the diagram uses its terms.

In Tutezy’s version, each slide or document is compiled once into that plan. Boards are built from a fixed set of operations (heading, bullet, formula, table, SVG diagram, image, highlight), and every image or diagram carries a text description so the teacher can refer to it. Checks can be multiple choice, short answer or predict-then-reveal, each with an expected answer, a rubric and hints for common misconceptions. You see the credit cost per slide before converting, preview any board exactly as a learner will see it, and recompile a slide after fixing its source. Concept ids stay stable across recompiles, so learner progress is not lost. The full mechanism is on how it works.

How to write checks that check something

Checks are where a converted lesson earns the word “interactive” or loses it. “Did that make sense?” and “Which of these is Newton’s second law?” test politeness and recognition, not understanding. A good check makes the learner use the idea once.

• One idea per check. If a wrong answer could come from two different confusions, you cannot target the hint.
• Ask for a prediction or a next step, not a definition. Applying the idea is the test, and producing an answer beats picking one.
• Write the expected answer and a rubric for any open question, or no reviewer, human or AI, can grade it consistently.
• Mine your question bank for distractors. Each popular wrong option is a misconception that deserves its own hint.
• Cap the remediation. A hint, then the answer with an explanation, then move on and come back later. Nobody should be stuck in a loop.

Tools for turning slides into interactive lessons

There are two broad kinds of tool, and they produce different things.

Authoring tools produce interactive content that you publish and host. One open example is H5P, which describes itself as “a completely free and open technology, licensed with the MIT license,” with content types such as Course Presentation (multiple choice, fill-in-the-blank and other interactions added to slides) and Interactive Video (the same kinds of questions and pop-up text added to a video). On H5P.com, the paid hosted service, a feature called Smart Import uses AI to generate H5P content from documents, audio and video. As of September 2026, H5P’s help center says it works best on declarative, factual material, accepts PDF, DOCX and ODT documents but not PowerPoint, and fully supports English and Spanish. The result is authored content: every learner sees the same questions, with feedback written in advance.

Live AI tutors produce a lesson that is taught, not published. The plan is prepared from your material, but the conversation happens live, so the tutor can react to a specific wrong answer, answer a doubt and revisit a weak idea for that one learner. The trade-off is a per-minute running cost instead of a one-time build, and a runtime you rely on rather than a file you own. If you are deciding how that fits into a course you already sell, see How to add an AI tutor to your online course.

You can use both: authored interactions for short practice sets, a live tutor for the chapters where learners get stuck. Either way, the preparation and review steps above are the same, and they are where most of the quality comes from.