Learners & Workers
Explore how learners and workers are affected by Texas workforce data challenges.
Learners and workers in Texas need to make critical decisions about their education and career paths, but the information that could help them make their decisions is incomplete or imprecise.
General information about trends in industries is not specific enough for students and workers to plan to enter into specific jobs because we do not collect job-specific data at the state level and schools, training programs and employers do not align their data for students to be able to see the connections between learning and careers. Additionally, employment data that is collected focuses on the location of the employer headquarters rather than where workers are actually located.
Without specific job level and geography data it's difficult for students to have insights into employment trends, such as which types of jobs are in demand and where, and what the typical career trajectories look like. Students’ ability to make decisions that fit their overall needs, such as which education or training program is best for their location and finances, is limited.
A student accesses general reports on engineering trends in Texas, to plan their studies and career path. These reports highlight that the field is growing, but do not specify which branches of engineering (e.g., civil, mechanical, software) are in highest demand. This lack of detail prevents them from understanding where to focus their studies.
Learners and workers in Texas need access to skills data linked to career progression to make informed decisions about their education and career paths.
Skills data that is collected is not linked to outcomes data consistently or at scale, making it difficult for students and workers to understand what skills are transferable between programs and jobs and to compare what is taught in one institution or training program with another.
The data on the actual skills present in the workforce is collected for employers by third-party organizations by scraping job postings. Currently skills data is not well connected to learning and employment data. As a result, learners and workers lack a complete picture of how to achieve their employment goals.
A mechanical engineer wants to choose a training program to develop additional skills for a higher-paying position, such as a senior engineer or an engineering manager. One program offers "advanced mechanical design skills," while the other lists "engineering leadership and project management competencies." However, there is no standardized description of what these skills entail, and they are not linked to occupation data, so the engineer cannot determine which program would better align with their career goals or offer the most valuable opportunities for advancement.
Texans have difficulty accessing the information they need to present their skills when applying for educational programs and searching and applying for jobs.
While resumes, transcripts, and references provide a partial picture, they often fail to capture the full scope of a person’s skills and achievements, especially non-traditional credentials. By contrast, the ability to access and share verifiable data about one’s skills and credentials (such as Learning and Employment Records or “digital wallets”) can offer a more complete representation of qualifications. Without this kind of data, it’s difficult for Texans to demonstrate their capabilities to potential employers or educational institutions, and understand how their skills and career or educational goals align.
A mechanical engineer is trying to transition into a leadership role. In addition to their degree, they have non-academic credentials on project management but they’re struggling to apply for positions because the online job application systems often require specific skills or experiences that they struggle to present. They cannot easily access skills data or education outcomes data to compare their skills, and the lack of information or a system that verifies their skills puts them at a disadvantage compared to other candidates who have more traditional qualifications.