1. Skill-Trilogy-Framework

Overview

To plan for the future, employees, employers, and skill providers need to step back and look at grander trends in the skill market. Unfortunately, this is not easy to do: the job and skill market is very decentralised, with listings posted across a variety of websites and in a variety of formats. This subproject focuses on overcoming these difficulties, by automatically collecting, annotating, and aggregating all of these different data.

To this end, we work with gathered job postings dating back up to 10 years; develop an AI framework supporting the annotation of job ads, CVs, and course descriptions with a unified skills taxonomy; and develop a platform for the dynamic analysis of this annotated data.

Artifacts

JobSkape: A Framework for Generating Synthetic Job Postings to Enhance Skill Matching

Rethinking Skill Extraction in the Job Market Domain using Large Language Models

PICLe: Pseudo-annotations for In-Context Learning in Low-Resource Named Entity Detection

Could ChatGPT get an engineering degree? Evaluating higher education vulnerability to AI assistants

Challenges for AI in Multimodal STEM Assessments: a Human-AI Comparison

Visuals