Automatic Question Generation

Automatic question generation allows us to scale the Doer Effect.

Using artificial intelligence methods, we can use textbook content to generate questions, and these questions can be created for textbooks nearly instantaneously to provide students with the learning by doing practice they need. However, it’s crucial to know that these questions are good. Our award winning research analyzed engagement, difficulty, and persistence of automatically generated questions and human authored questions answered by the same students in the same courseware. This research has shown:

Students do not treat automatically generated questions differently than human authored questions.
The differences in engagement, difficulty, and persistence were actually related to the cognitive process dimension of the question (recognition versus recall), not how the questions were created.
Easy questions did not deter students from answering, but very difficult questions did decrease student persistence in answering.

Recent Publications About Automatic Question Generation

Search our catalog of recent publications authored by our team.

2026

Student attitudes and perceptions of AI and AI-generated practice in the classroom

The IAFOR International Conference on Education – Hawaii 2026

Rachel Van Campenhout, Michelle Clark (2026)

Automatic Question Generation Generative AI Teaching & Learning

2025

AI-generated formative practice and feedback: Performance benchmarks and applications in higher education

Artificial Intelligence in Measurement and Education Conference (AIME-CON)

Rachel Van Campenhout, Michelle Clark, Jeffrey S. Dittel, Bill Jerome, Nick Brown, Benny G. Johnson (2025)

Automatic Question Generation Generative AI Feedback

See all publications