In this study, we compared the effectiveness of two instructional approaches—modeling and generative tasks—within case-based instruction (CBI) in developing preservice teachers’ classroom case analysis skills. Forty preservice teachers were randomly assigned to engage in CBI with either a modeling or generative task, working through three classroom cases over a four-week period. Results from mixed factorial ANOVA showed that while both approaches initially provided similar benefits, the generative task yielded progressively higher gains in participants' demonstration of learning theories over time, as evidenced by significant time-based improvements. In contrast, those in the modeling condition did not show growth, suggesting limited cognitive engagement when simply observing expert examples. These findings highlight the potential of generative tasks to deepen cognitive processing, promote independent analysis, and encourage critical reflection. Our results underscore the need for exploration into instructional methods in CBI to prepare teachers more effectively for complex classroom scenarios. Limitations and directions for future research are discussed.

This paper outlines how four community colleges, and a large public university, collaborated to support over 80 paraprofessionals who sought to finish their bachelor’s degree and earn licensure. Funding from a statewide “Grow Your Own” initiative allowed the teacher educators at the community colleges and university to put in place structures to support non-traditional students, and each other, during the first year of this program. Lessons learned and next steps are highlighted.