2025 Badge Summit

“There are too many badges and many of them don't matter.” While this statement might seem counter to the prevailing logic in higher education, this is the feedback we receive in nearly every consultation with hiring employers. What these employers are looking for is skills and a way to verify that applicants have the skills they are looking for. Badges could be the solution employers are demanding, but we've put too much effort into creating badges and too little effort into aligning them with workforce needs.


Leveraging AI for Skills Extraction and Research (LAiSER) is an open-source project of the George Washington Institute of Public Policy (GWIPP) designed to help align skills in curricula with workforce demand. By applying LAiSER extraction tools we can create more meaningful badges that not only better align with workforce but also allow for interoperability amongst different employers and issuers using LAiSER’s skills mapping tools.


In this presentation we will focus on the promise of badges and the opportunity to create variable microcredentials linked to skills. Describing badges using skills not only creates an opportunity for embedding skills within the Open Badge 3.0 standard but also aligning individual badges to LAiSER’s skill maps to help build more robust microcredentials out of badges. LAiSER also has the benefit of making these badges interoperable with other standards, including non-standardized use cases such as job applications, allowing for customized skill assertations beyond Open Badges 3.0.


Our presentation will begin with a brief explanation of LAiSER and an update on the open-source tools available. We will then walk through a demonstration of how to create a badge using LAiSER in the Open Badge Standard (3.0) by taking advantage of the skill assertations feature. We will finish by demoing some of the new features of LAiSER and discussing upcoming development projects.