The “Finnish Phenomenon” in Geoscience Education
Notice bibliographique
Résumé
The declining popularity of geosciences in higher education (HE) globally has increased concern about an emerging skills gap in the geoscience workplace. Australia, Canada, the US, the UK, and Italy have observed a decline in graduates, enrolment, and/or applicant numbers of typically 20 to 40% in graduate/undergraduate geoscience programs since 2013. Geoscience educators tend to attribute these trends to negative public perception of geosciences in relation to environmental and climate change and general lack of awareness about societal relevance of the field.The opposite trend has been observed in Finland over the past eight years. Degree programmes in geology or geosciences in Finland have jointly experienced a total increase of ca. 70% both in applicant numbers (2020–2024) and enrolment (2015–2024). The Finnish geoscience education community coined the term “Finnish phenomenon” to describe these positive observations. However, the reasons behind these observations remain to be understood. As the overall applicant numbers to Finnish universities do not follow these trends, education system level effects can most likely be ruled out.This contribution explores some of the activities and changes in the Finnish geoscience higher education processes during the past ca. 10 years that could explain the “Finnish phenomenon”: 1. Changes in the Finnish HE admission systemIn 2015, the Finnish HE application process (joint application system) was transferred to the digital Studyinfo.fi-portal (https://opintopolku.fi/konfo/en/). Since 2022, all geoscience degree programmes have hosted a joint landing page within the portal to enhance the visibility of the field. 2. International Earth Science Olympiad (IESO) activitiesSince 2018, the visibility of geosciences in Finnish schools has been enhanced through the activities of the International Earth Science Olympiad (IESO). National IESO efforts coordinated through the Geological Society of Finland have increased the visibility of geosciences among students and led to success in the international competitions. 3. Upper secondary school collaboration in geosciencesGeosciences are not taught as a separate subject in Finnish upper secondary schools. Since 2020, secondary school collaboration has been systematically enhanced especially at the University of Helsinki through a working group that includes staff, students, City of Helsinki education services, and schoolteachers. 4. The FIN-GEO networkOne of the major joint efforts in the Finnish geoscience education community in recent years has been the FIN-GEO project funded by the Ministry of Education and Culture of Finland in 2021–2023. The FIN-GEO network significantly strengthened cooperation in the education of geosciences, utilizing the mutual research profiling of the parties in the development of educational offerings and the relevance of working life. The annual geoscience first-year questionnaire launched by the FIN-GEO network in 2022 has found that the Studyinfo.fi-portal alongside geoscience-specific media coverage and university webpages have been the most important sources of information for aspiring students. Further analysis of these results is ongoing, but combined the actions listed above appear to have positively affected interest in higher geoscience education, which could serve as a useful template elsewhere as well.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,007 | 0,005 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,022 | 0,004 |
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 source (Gemma direct ou Codex distillé), 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 ».