Effects of Generative Artificial Intelligence on Instructional Design Outcomes and the Mediating Role of Pre-service Teachers’ Prior Knowledge of Different Types of Instructional Design Tasks

Generative artificial intelligence (GenAI) is increasingly becoming a tool used in many spheres, including education. A key question is whether GenAI can support teachers in one of their major roles: designing learning environments. This research aims to bridge the gap in understanding how different types of GenAI use impact instructional design outcomes. To achieve this, the study design includes three experimental conditions: 1) with GenAI, 2) with a GenAI bot pre-trained as a co-instructional designer, 3) automated by GenAI and one control condition (no use of GenAI). Participants, who are pre-service teachers, are tasked with designing a lesson blueprint and developing a lesson plan. The quality of instructional design outcomes and any common patterns across conditions are evaluated. Moreover, the impact of teachers’ interactions with GenAI on the instructional design outcomes is analyzed. Additionally, the study aims to reveal a relationship between participants’ prior familiarity with instructional design tasks and the way they design instruction with and without different uses of GenAI. This research study is crucial for exploring GenAI's potential to become a valuable partner for teachers in co-designing instruction and providing students with better learning opportunities.