Abstract:

Canada lacks a consistent, system-wide way to capture and analyze intersectional demographic information about K-12 leadership. This limits school divisions' ability to monitor representation, identify gaps, and evaluate whether recruitment and retention efforts are improving equity over time. We present the Data Acquisition Model (DAM) Hub, a bilingual (English/French) data-collection and reporting platform designed to help school boards securely gather voluntary demographic and career-pathway information and translate it into actionable analytics. This is a part of the Mitacs and SSHRC project.

DAM Hub is implemented as a lightweight module within a secured Moodle deployment, leveraging mature authentication, role-based access, and hosting controls while keeping the application focused on a single purpose: data acquisition and analytics. The platform delivers a configurable, sectioned survey, stores responses in a normalized schema, and provides a question-by-question dashboard that generates distributions and cross-tabulations to support intersectional analysis (e.g., gender identity by role, experience, certification, or geography). To support responsible use of sensitive data, the analytics layer includes privacy safeguards such as small-cell suppression and controlled access to raw counts.

We describe the system architecture, data model, multilingual design, and reporting workflow, including exportable PDF/Excel report packages and email delivery with links back to interactive dashboards. We also outline an integration pathway for districts that prefer system-to-system workflows via token-secured web services. We discuss how DAM Hub can support longitudinal monitoring of leadership diversity and enable evidence-informed decision making at the school-board level.

Keywords:

Learning analytics, educational leadership, equity, diversity and inclusion, bilingual survey, privacy-preserving reporting, K-12.