Learning Together for a Greener Future: TEAMIT+ Programme Evaluation (First Edition, 2024)

This dataset supports the findings reported in the article "Learning Together for a Greener Future: Teampreneurship as an Open Approach to Green Entrepreneurship Education" (submitted to Open Research Europe). The dataset comprises four files: 1. TEAMIT_M1_self_evaluation_BEFORE_anonymised.xlsx — Anonymised pre-event self-evaluation questionnaire responses from Module 1 participants (n = 122), covering self-assessed environmental knowledge, awareness of environmental legislation, perceived personal impact, and learning expectations. Data collected October 2024 across four countries (Finland, France, Greece, Spain).2. TEAMIT_M1_self_evaluation_AFTER_anonymised.xlsx — Anonymised post-event self-evaluation questionnaire responses from Module 1 participants (n = 139), covering the same dimensions as the pre-event form plus reported learning outcomes and behavioural intentions. Matched pairs (n = 122) underlie the pre-post analysis reported in the article.3. TEAMIT_M1_satisfaction_anonymised.xlsx — Anonymised post-event satisfaction questionnaire responses from Module 1 participants (n = 160), covering overall enjoyment, favourite activities, logistics, skills developed, and open-ended feedback.4. TEAMIT_M2_summary_data.csv — Aggregate summary data for Module 2, derived from the publicly available TEAMIT+ D2.1 Interim Assessment report (https://teamit.plus/public-deliverables/). Includes participation counts by site, team diversity and award data for the France flagship event, and the historical 24h of Innovation dataset (2007–2025) underlying Table 1 of the article. Raw individual-level Module 2 response data was not collected centrally and is not available. All personally identifiable information (email addresses, timestamps) has been removed or replaced with anonymous respondent identifiers. Data were collected via online questionnaires with written informed consent obtained from all participants prior to completion. The TEAMIT+ programme (Grant Agreement No. 101111560) was funded by the European Union's EACEA – Erasmus+. Views expressed are those of the authors only and do not reflect those of the European Union or EACEA.