The design of BaiSE is rooted in key educational theories that prioritize active, reflective, and socially mediated learning:
BaiSE helps reduce extraneous cognitive load by curating tools and offering structured evaluation templates. This allows educators to focus on high-impact instruction and student relationships while AI supports backend tasks.
BaiSE supports learning through experience and social interaction. It draws from:
Vygotsky’s Zone of Proximal Development (ZPD): Educators move from AI novices to confident users through scaffolded, community-based learning.
Dewey’s Experiential Learning: Educators “learn by doing” as they test and review AI tools within their real-world practice.
Educators engage in collaborative reflection, sharing use cases, challenges, and ethical considerations. This crowdsourced knowledge base provides peer-vetted insights, moving beyond marketing claims to real-world application.