Learner Lab

Many of the student support tools currently available to educators take a deficits-first approach. They start with a student's challenges and suggest strategies to support those challenge areas. Learner Lab is designed with a strengths-first approach based on the understanding that every student has genuine strengths, and that leveraging those strengths is often the most effective path to growth in challenging areas.

What It Does

Learner Lab is a searchable library of teaching strategies, each one designed around a specific student strength. An educator looking for ways to support a student who struggles with task initiation but has hyperfocus and sustained attention can filter by those exact attributes and find strategies that leverage what that student does well to address what's hard. Each strategy card displays the strategy name and description, the strengths it leverages, the challenge areas it supports, relevant tags including neurodiversity categories and instructional approach, and the appropriate age group.

How It Works

The backend is a Node.js/Express API connected to a MongoDB Atlas database. Each strategy is stored as a document with arrays for strengths, challenge areas, and tags, providing a flexible structure that supports the multi-value filtering the app requires. The frontend uses react-select to handle multi-input filter bars, allowing educators to build searches unique to each individual student across three dimensions simultaneously.

Where It Stands

The database is populated, the cards render correctly, and the filter UI is in place. Connecting the filter selections to backend queries to dynamically update the displayed cards is the primary remaining work.

What's Next

Dynamic filtering connected to the backend, user authentication to support educator accounts, the ability to submit new strategy cards, and student profile pages where favorite strategies can be saved.