Academic Offer of Advanced Digital Skills in 2019-20. International Comparison: Focus on Artificial Intelligence, High Performance Computing, Cybersecurity and Data Science
Notice bibliographique
Résumé
This work aims at supporting policy initiatives to ensure the availability in the EU27 of an adequate education offer of advanced digital skills in the domains of artificial intelligence (AI), high performance computing (HPC), cybersecurity (CS) and data science (DS). The study investigates the education offer provided in the EU27 and six additional countries: the United Kingdom, Norway, and Switzerland in Europe, Canada and United States in America, and Australia, with a focus on the characteristics of the detected programmes. It analyses the number of programmes offered in these domains, considering the distinction based on programme’s scope or depth with which education programmes address the technological domain (broad and specialised), programme’s level (bachelor programmes, master programmes and short courses), as long as the education fields in which these programmes are taught (e.g. Information and communication technologies, Engineering, manufacturing and construction, Business, administration and law), and the content areas covered by the programmes. The analysis is conducted for each technological domain separately, first addressing the features of the overall education offer detected in the countries covered by the study, and followed by an in-depth analysis of the situation in the EU27. Among the many results that this work provides, those associated to the most relevant insights can be listed as follows. First of all, the main role in the offer of advanced technological skills is held by the US, which leads in terms of number of programs provided in almost all combinations of technological domain, scope and level. Secondly, another important player is the UK, with a very consistent offer of bachelor and master degree programs (in both cases, the UK’s share is around 25% of the total offer detected). The consequences of the Brexit have, therefore, to be considered and faced also in terms of the education offer of advanced technological skills in the EU27. Thirdly, the role of the EU27 is notable but more varying (depending on the combination of domain, scope and level of programmes) than that of the UK. Regarding more specific aspects related to the EU27 offer, we detect a good amount of programmes offered in the domain of DS. As this domain is found out to be remarkably associated to the field of education of Business, Administration and Law, this is a positive finding suggesting a good supply of competences that are suitable to economic activities of various types. Therefore, what observed for the EU27 suggests a good alignment between the offer and the demand of DS-related skills. In the EU27 we observe a large share of programmes belonging simultaneously to both DS and AI. Considering the relatively high offer in DS, and the fact that AI is currently a techno-economic domain that is attracting a lot of attention and of private and public resources, a consistent connection between these two domains can be considered as an important key to favour synergies and future economic growth. Additionally, we find DS programmes quite widespread among the fields of education, which may facilitate the role of DS as a vehicle to further introduce AI, HPC and CS in the fields of education barely addressing these technological domains. We also observe a relatively large offer of AI master degree programmes in the EU27, which is an important finding given the role of this education level in the provision of competences for the workforce. Finally, it is important to note that we detect potential elements of weakness in the EU27’s education offer related to CS. These competences are increasingly crucial to prevent and fight cyber-related incidents, concerning both private and public spheres. Therefore, the detection of a relatively modest CS education offer (in comparison to other geographic areas) is a point that deserves attention. Many other findings are described throughout this report, but what discussed in this abstract has to be retained as the most relevant content aimed at supporting EU policies.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».