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This piece builds on a previous piece where we explored the importance of keeping your desired outcome in mind when working with generative AI (genAI). We also highlighted the value of including specific data and contextual details in your prompt to align with your goals. If you haven’t read that piece, we recommend starting there:

Backward design is, as the name suggests, a process for designing curricula, courses, and lectures by working backward from big-picture learning goals. The concept, introduced by Grant Wiggins and Jay McTighe (2005), suggests that instructors create assessments, activities, and course content that are explicitly aligned with the broader learning goals of the unit. This is different from the traditional content-driven approach to learning design, which focuses on course content first and only secondarily tries to align that content with learning goals.

The Third Space theory, introduced by postcolonial theorist Homi K. Bhabha, explores a transformative space where new identities and meanings emerge through the interaction of diverse cultural elements. This "third space" is characterized by hybridity, challenging rigid, binary notions of identity and culture, and emphasizing fluid negotiations between dominant and marginalized perspectives (Burke, 2012; Lin, 2014). Bhabha’s theory builds on Ray Oldenburg’s (1999) concept of the "third place"—an informal public space where people gather to form a community that is neither home nor work—and extends it into the realms of cultural and social discourse, creating a broader framework for negotiating power, identity, and cultural exchange (Bhabha, 2012). These third spaces can emerge in a variety of contexts, including both physical locations like cafés or parks and virtual environments such as online forums or social media platforms, making the theory applicable to both in-person and digital interactions.