Abstract:

LEAP: Unlocking Career Potential with Complex Systems, Data Analytics and Machine Learning is an Erasmus+ project that addresses the persistent mismatch between higher education provision and labour-market demand for advanced Information and Communication Technology skills. The project brings together four universities and one industry partner from Greece, Italy, Türkiye and Sweden to co-design a flexible, inclusive and practice-oriented learning offer in Complex Systems, Statistics, Data Analytics and Machine Learning for higher education students, graduates and adult learners. A robust skills-gap analysis preceded the design, development and implementation of the courses, with the aim of ensuring their relevance both to labour-market needs and to learners’ expectations.

The findings of the skills-gap analysis confirm and reinforce patterns already identified in previous research. From the employers’ perspective, demand for these skills substantially exceeds supply, and the more advanced the skill set required, the more difficult it is to recruit suitable candidates. From the learners’ perspective, the analysis highlights not only a clear lack of relevant knowledge and competences, but also a strong willingness to acquire them. Particularly significant is the diversity of those expressing interest, including many with backgrounds far removed from Science, Engineering, Technology and Mathematics (STEM) disciplines. Indeed, the overwhelming majority of respondents identified upskilling and reskilling as their main motivation for participating in LEAP courses, indicating that their primary goal is access to relevant employment opportunities or, in many cases, a career change.

Within LEAP, collaboration between higher education institutions and industry has led to the development of a practice-oriented curriculum based on project-based learning. Of particular interest is the third course, which pilots a new interdisciplinary approach: learners are invited to tackle complex systems problems by drawing on an integrated combination of Complex Systems, Data Analytics and Machine Learning. This approach brings together skills often regarded as more fundamental or academic with those currently in high demand in the labour market. The courses are designed to foster critical thinking and strengthen learners’ ability to apply newly acquired competences in practice, while the practical exercises have been developed with the direct involvement and expert oversight of the consortium’s industry partner.

As the courses will be completed by the end of spring, the presentation will also reflect on emerging evaluation priorities, including learners’ perceptions of the courses’ usefulness in achieving their goals, what worked and what did not, in order to identify best practices for the design and delivery of such courses and for online education, the difficulties encountered throughout the project, the extent to which the project was able to reduce the typically high attrition rates associated with online learning, particularly among participants from non-STEM backgrounds, and the implications for future course design and delivery.

Keywords:

Erasmus+, e-learning, advanced ICT skills, skills gap, higher education–industry collaboration, Complex Systems, Data Analytics, Machine Learning.