How AI feedback supports lesson planning in vocational teacher education: a longitudinal intervention study using an analytical AI platform

Abstract This study explores the use of analytical artificial intelligence (AI) to enhance lesson planning in teacher education, particularly in vocational business education. Providing detailed, individualized feedback for lesson planning is challenging for university instructors. An analytical AI platform that offers expert-level feedback on lesson plans could be a suitable supplement to traditional feedback as it balances out critical aspects of generative AI systems. In a longitudinal study with 103 participants, an experimental group received AI feedback on the lesson plans they developed throughout a semester, while a control group received human feedback. Results indicate that AI feedback can match or surpass human feedback in some dimensions, improving planning aspects like certain content-related sustainability aspects, action orientation, relatedness or even technology use, lesson structure, and learner engagement. Besides the integration of didactic planning dimensions into the lesson plans, this study looked at student motivation, self-reported AI literacy, AI attitudes, self-efficacy with digital technologies and digital competences. Results of these meta-dimensions show that the mere use of AI does not automatically enhance AI literacy, change attitudes or improve motivation. The study suggests that as a consequence, analytical AI platforms can effectively supplement traditional feedback but should be used within a holistic framework.