DESE: EdTech Systems Guide and DESE Interview Video

EdTech Systems Guide

New this summer from the Massachusetts Department of Elementary and Secondary Education (DESE) and The Learning Accelerator, the EdTech Systems Guide offers schools steps to develop and strengthen systems for equity-driven edtech selection, implementation, and evaluation.

Chris Gosselin, who is the President of the MassCUE Board of Directors, had the opportunity to talk with representatives from DESE to learn more about this new resource. Watch his interview (embedded below) with Director of Educational Technology and School Support Jackie Gantzer and Assistant Director of Educational Technology A.J. Cote and read more about the guide below.


The DESE is excited to announce the launch of the EdTech Systems Guide: Equity-Driven Selection, Implementation, and Evaluation, developed by the Massachusetts Department of Elementary and Secondary Education (DESE)’s Office of Education Technology (OET) in partnership with The Learning Accelerator (TLA). In May 2021, the Department released the EdTech Strategic Planning Guide: Sustaining Progress in Access and Equity, offering school and system leaders guidance related to intentional and strategic edtech planning and resource allocation. This new guide builds off of that foundational work by offering support in developing and strengthening systems for edtech selection, implementation, and evaluation to ensure that edtech is effectively chosen, powerfully implemented, and properly evaluated for effectiveness and equity across the state.

The resource is designed primarily for system-level administrators in charge of overseeing edtech in their district, school, or school system. Depending on the structure of a school or system, this audience may include members of academic teams, technology teams, and/or standalone edtech teams.

While this guide has been designed specifically for Massachusetts school systems, the guidance is applicable to schools outside of the state as well.

EdTech System Guide: Equity-Driven Selection, Implementation, and Evaluation

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