Yes — what you’ve described is very appropriate from a learning science perspective. Let me break down why it works in terms of cognitive load theory, encoding to long-term memory, and schema-building:
1. Cognitive Load Management
Split into steps (Intro → Interactive → Questions → Resources → Workbook) → This is segmenting, which reduces extraneous load by chunking the process. Learners aren’t hit with everything at once.
Workbook is simple (Inquiry → Discover → Action) → A repeatable, predictable structure lowers extraneous cognitive load, so learners’ brains can focus on germane load (building schema).
Interactive elements (iSpring/PPT HTML) give background & context before the learner has to process their own info, which scaffolds intrinsic load.
2. Encoding to Long-Term Memory
Questions (Inquiry) → This activates generative processing (the learner retrieves prior knowledge + sets a purpose for learning). Retrieval + elaboration are proven to aid long-term memory.
Resources & Discover → Learners are not passively receiving; they’re actively searching, comparing, and writing down what they find. That encoding step is what moves info from working memory to long-term memory.
Action → By personalizing (documents, contacts, next steps), learners are elaborating the information into their own schema — “this is mine,” not abstract.
3. Schema Building (Making It Stick)
Each topic = its own schema (e.g., banking schema, healthcare schema).
The Bridge structure (Inquiry → Discover → Action) mirrors how schema grow:
Inquiry = activating prior schema / gaps
Discover = filling the schema with new links
Action = connecting schema to lived context
By the end, the learner doesn’t just have information — they have an organized, personalized mental model of relocation tasks that can be retrieved and applied later.
✅ Why this design is strong:
Manages cognitive load by chunking.
Uses retrieval, elaboration, and personalization → proven methods for long-term memory.
Builds schema in context (relocation topics), which increases transferability to real life.
If you’d like, I can put this into a short “learning science rationale” paragraph that you could even include in your facilitator/partner materials to show the intentional design behind Becoming Home – France. Would you like me to draft that?
Learning Science Rationale
The Becoming Home – France course is intentionally designed around principles of cognitive load theory, long-term memory encoding, and schema development to maximize learner success.
Managing Cognitive Load: Each lesson is broken into clear, sequential steps (intro → interactive component → guiding questions → curated resources → Bridge workbook). This segmenting approach reduces extraneous load and helps learners focus on the essential information.
Encoding for Long-Term Memory: The Bridge workbook uses a consistent three-step structure:
Inquiry – learners generate their own questions, activating prior knowledge and establishing relevance.
Discover – learners engage with curated resources, processing new information in a guided way.
Action – learners personalize the learning by recording steps, documents, and contacts specific to their own situation.
This cycle uses retrieval, elaboration, and personalization — all evidence-based strategies shown to strengthen memory retention.
Schema Building for Transfer: Each relocation topic becomes a self-contained schema (e.g., healthcare, banking, housing). By consistently moving from question → discovery → action, learners actively organize information into meaningful frameworks. These schemas connect directly to lived experience, making the knowledge more retrievable and transferable to real-world problem solving.
By the end of the course, learners will not only have gained knowledge but will have constructed a personalized, actionable immigration plan — a durable outcome that bridges learning with life.