There are some powerful reasons why the Open Curriculum Development Project includes H5P in our Pressbooks. When done well, these interactives can:

• Help students achieve chapter learning objectives. Each interactive deepens a student’s understanding of the key terms, skills, or concepts that guide the chapter. Each interactive should have a clear relationship with at least one chapter learning objective.
• Give students more opportunities to check comprehension. Learner interaction, discovery, and agency encourage students to shift from passive to active learners. Interactives in the text reinforce and interleave content, supporting new learning pathways.
• Increase the relevance and overall gain of the Pressbook. Future educators and adopters value student interaction.

Because many students print the Pressbook, or download it to read offline, we include the text of H5P questions and answers in those formats of the book. We put a note in the front matter explaining where to find self-check questions. We add a section to the back matter in exported formats that includes all questions followed by all answers.

What is Well-Designed H5P?

Interactives are well-designed when they reinforce familiarity with key terms, distinguish between old and new ideas, and help students to summarize major chapter claims. They also allow students to apply chapter skills to new contexts or examples.

On the other hand, hastily or partially designed activities can disrupt learning. Questions that focus on extraneous detail or emphasize ideas that are unrelated to the chapter’s argument make students think that they are missing key content. Incorrectly coded answers contradict chapter content and lead to loss of trust with students. Future educators may assume that your book doesn’t offer high quality content.

To ensure that your H5P enhance student learning, consider the following criteria:

1. Alignment: The activity is relevant to the content, directly supports learning objectives, and focuses on specific concepts crucial to understanding the content.
2. Integration: The activity makes clear connections to chapter topics and contextual relevance.
3. Feedback: Answer feedback explains why an answer is correct, and directs students back to appropriate chapter sections to review. It enhances instructor presence and can help students form lasting connections with textbook content. H5P answer feedback is limited to 255 characters, including spaces. This is about 30 words, or 3 short sentences total.
4. Accessibility: Not all H5P question types are accessible. We recommend multiple choice and true/false question types. You can optionally learn more about H5P accessibility from Accessibility Reports for H5P Activity Types [Website].

Who Reviews My H5P for Quality?

Authors create H5P questions, answers, and answer feedback using their subject matter expertise and familiarity with chapter learning objectives. The Instructional Designer and other support team members are available to consult with you.

Once content is drafted, a Copy Editor reviews all content for consistency, clarity, and relevance to chapter language. The Copy Editor will remove or resolve low-level issues and share content questions via document comments when they are unable to resolve a point of confusion (for example, when answer feedback is missing, no answer option is marked as correct, or the answer options appear to be incorrectly coded as correct or incorrect).

The Instructional Designer will resolve comments on technical or low-level issues. They will escalate questions that require subject matter expertise back to the author. You can expect to resolve 3-5 questions about your H5P.

After your H5P is uploaded into your launch Pressbook, it will be professionally proofread for grammar and spelling, as well as for consistency with the final version of the textbook.

Can Generative AI Write Your H5P for You?

In a word, no.

In 2025, our team experimented with two GenAI tools, Nolej and ChatGPT, to generate H5P questions. We determined that it cost our program far more time and money than we would have invested in simply writing questions from scratch. We estimate that generating H5P interactives with GenAI approximately doubled our time investment when we tried it out. We can’t commit program resources to support its use since it’s demonstrably inefficient.

The overarching issue we found was that GenAI didn’t align our H5P interactives with the chapter’s learning objectives, leaving us with extensive revision work even after trying multiple prompts. The revisions were tedious to do, and because we needed to generate so many questions for our projects, it was easy to get tired and overlook places where the errors or missteps were subtle.

Here are three kinds of specific issues that we needed to correct after using two popular GenAI authoring platforms to generate questions:

1. Nolej and ChatGPT generated questions that focused on easily recognizable facts, like dates and definitions, rather than questions that require the application of new concepts or critical thinking. This might work for some course settings, but it’s not what we’re looking for in the self-check questions for our projects.
2. Nolej and ChatGPT marked answer options incorrectly – some answers that are actually true were coded as false. This would be confusing and frustrating for students to encounter.
3. Nolej didn’t generate answer feedback, and ChatGPT didn’t generate meaningful answer feedback from an equity perspective, even when explicitly prompted to do so (ex: “suffix the correct answer with ::: and an equity-minded explanation for why this was the correct answer”). Instead, it repeated itself or introduced content unrelated to the original question. Sometimes the feedback lacked important nuance, and sometimes it missed the point of the question entirely.

ChatGPT seemed to perform less reliably the more the content related to equity concepts. In one example, generated answer feedback overlooked the concept of intersectionality as it relates to feminism, even though that is a stated learning outcome of the chapter. This is consistent with the findings shared by open educator Maha Bali in the webinar Actually Scary Things About Artificial Intelligence in Open Education [Streaming Video]. Bali points out that even GenAI tools like NotebookLM that are designed to extract and paraphrase material from provided content tend to reinforce systemic bias. Because GenAI is trained on biased material, it will miss equity concepts in ways that may be subtle or overt.

Further, as we saw in Florida Scours College Textbooks, Looking for Antisemitism [Website], questions are often used as at-a-glance indicators of the textbook quality as a whole. If our H5P interactives fail to reflect the nuance and complexity of the books themselves, we not only risk reinforcing the bias that we are working against. We also may lose our audience.

Licenses and Attributions for Well-Designed H5P

Open content, original

“Well-Designed H5P” by Open Oregon Educational Resources is licensed under CC BY 4.0.

Open content, shared previously

“Can Generative AI write your H5P for you?” is adapted from AI Pause by Amy Hofer and Veronica Vold and is licensed under CC BY 4.0. Thank you to Jeff Gallant, Program Director, Affordable Learning Georgia, and Stephen Krueger, Affordable Course Content Librarian, University of Kentucky, for assistance with this blog post.