by Helen C. Leligou (University of West Attica)

The energy transition challenges the education and training of students, technical /energy professionals, service designers and marketers, and citizens throughout the EU. The project ASSET has developed a set of tools that address this challenge and are evaluated by end users.

ASSET (A holistic and scalable solution for research, innovation, and education in energy transition) was an H2020 project that focused on boosting research, innovation and educational capacities for the energy transition [L1]. The energy transition is tightly bound to the smart city concept: the transition to renewable energy requires the wide deployment of smart cyber-systems that capture the city’s characteristics in terms of the technical infrastructure, citizens’ activities and the climate. The ASSET project aimed to address the challenges of: (i) improving the efficiency of education and training because the energy transition mandates the education/training and upskilling of many people of diverse technical, business, cultural and societal backgrounds; (ii) cultivating the interdisciplinary competencies necessary for the design, development and consumption of smart energy services; and (iii) uniting industry and the academia to help realise the energy transition.

ASSET broke down its aims into two tangible goals: (i) To create a sustainable and scalable ecosystem (community) that included all energy transition and education stakeholders: companies from the energy sector, universities and training actors, public authorities and policy makers, and society; (ii) To deliver the framework and means for the continuous collaborative definition of the knowledge/competencies/skills required for the energy transition and for continuous resource pooling to efficiently educate or train large numbers of people in diverse and interdisciplinary topics and for carrying out research and innovation activities.

During the project we brought together a community comprising the main energy transition actors, and developed a conceptual framework accompanied by the ASSET digital platform to speed up the creation of (single or multi-disciplinary) learning programmes. We delivered more than 25 training programmes, all of which were thoroughly evaluated through pilot studies, and are still accessible through the project website. In addition, as part of the project we promoted interdisciplinary approaches in research, education and innovation by strengthening collaboration between academia and the industry.

One of the most important exploitable results delivered by the project was the learning graph tool which assists trainers and professors in designing learning programmes in a structured manner, adopting the learning graph model [1] and also facilitates sharing of learning materials as these are described in the platform in a way that accelerates search. The model is shown in the following figure which also shows the information kept per graph element. Namely, the learning materials are associated with the targeted learning outcome, the learning style (blended, face-to-face, asynchronous) and the corresponding EQF (European Qualification Framework) levels. This tool was assessed by external experts and was found to accelerate the learning programme design by more than 25%, which significantly contributes to delivering knowledge to larger audiences faster [1].

Figure 1: The learning graph model.
Figure 1: The learning graph model.

Another valuable tool resulting from the project was the ASSET Marketplace, which enables matchmaking between industry and academic training actors. The Marketplace has two main functionalities: (i) Offer – where educational programme providers announce their offerings in the ASSET marketplace, and companies can find educational programmes that match their needs; (ii) Demand - Companies that do not find the educational programmes they are looking for can insert a request on the platform ("open request") and educational programme providers can respond with a specific offer.

Other interesting results include the assessment of education/training programme delivery: we offered several programmes in multiple delivery forms (face to face, Massive Open Online Course- MOOC and blended form) and their evaluation by users (trainees) is reported in [1] and [L2]. We also assessed the satisfaction and interest of the users (students) from the completion of interdisciplinary courses. The results showed that the students considered the non-technical topics to be very useful. Additionally, we delivered MOOCs for citizens, which were also very positively received and are still open in the EMMA platform [L3]. Last, but not least, the project investigated societal issues relevant to the energy transition. The results, which are detailed in [L4], report the level of understanding of the energy transition and its impact on everyday life of European citizens and stakeholders.

The two-year project, which was coordinated by ATOS Spain, ended in April 2021 [L1]. The consortium included well-known European Universities and training providers (Aalborg University, OTE Academy, RWTH University of Aachen, University of Naples Federico II, University of Valencia, University of West Attica), an association of energy companies (European Association for Storage of Energy), an organisation focusing on skill gap detection (Logical Soft) and two energy communities (ECOPOWER and ENOSTRA).

Links:
[L1] https://energytransition.academy/
[L2] https://energytransition.academy/deliverable/D4.5
[L3] https://platform.europeanmoocs.eu/
[L4] https://energytransition.academy/content/ssh-energy-transition

Reference:
[1]: H. C. Leligou, et al.: “Designing an innovative educational toolbox to support the transition to new technologies”, Social Sciences, Springer Ed., SN Soc Sci 1, 67, 2021, https://doi.org/10.1007/s43545-021-00087-9.

Please contact:
Helen Leligou
University of West Attica, Greece
This email address is being protected from spambots. You need JavaScript enabled to view it.,  +30 6973249129


Next issue: January 2025
Special theme:
Large-Scale Data Analytics
Call for the next issue
Image ERCIM News 127
This issue in pdf

 

Image ERCIM News 127 epub
This issue in ePub format

Get the latest issue to your desktop
RSS Feed