Skills-in-Demand: Bridging the Gap between Educational Attainment and Labor Market with Learning Analytics and Machine Learning Applications

Globalization and rapid technological changes have an overarching impact on business, individuals, and education in the 21st century. Employers and educational institutions face complex challenges involving reskilling and creating a chain of demand and supply based on current and future workforce needs. Increasing skills (mis)match and skills shortage have been a recurrent topic in both education and labor market research. Lack of technical skills or soft skills is often reported as the main reason for not hiring an applicant. According to Ek (2015), the underlying causes, however, lie in the lack of information about a fast-evolving job marketplace and delays in new skills development. To build actionable data-driven solutions for educators, businesses, and learners, a multi-disciplinary approach is needed involving educational data mining, learning analytics, economic research, statistics, personalized recommender systems, visualization, and machine learning.

This Research Topic is dedicated to the novel or significantly expanded at scale approaches and applications supporting various stakeholders and minimizing skills gap. Submissions can describe new tools, novel metrics, challenges in designing courses responsive to labor market demands, new collaborations between institutions and industry, prediction models for career paths or skills-in-demand. The main research question is: What tools and scientific knowledge can help predict critical skills, build career paths for learners, and “skillify” educational programs?

We cordially invite authors to submit high-quality manuscripts, such as original research papers, review articles, and case studies. Topics of interest include, but are not limited to, the following:

• Mining job postings data
• Course and career recommender systems
• Skill gap analysis
• Academia and Industry alliance
• Policy recommendations
• Prediction models
• Innovative programs development
• Visualization tools
• Learning analytics
• Educational mining
• Informal learning
• Networked learning
• Capability development

Keywords: skills gap, labor market, recommender systems, personalized career path, educational data mining, learning analytics

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.