Methodological Approach WORKPACKAGE 2: ETH-TECH Framework

The document outlines the methodological approach for Work Package 2 (WP2) of the ETH-TECH project, which aims to create actionable tools and Open Educational Resources (OERs) to foster ethical use of AI and data in higher education. Building on EU, UNESCO, and OECD guidelines, the project addresses the gap between ethical principles and their practical implementation in educational settings. Guided by activity theory, WP2 focuses on transformative learning through Awareness Raising Sessions (ARS) involving faculty and students. The methodology includes two main strands: syllabi analysis and practice exploration. For syllabi, universities will sample and analyze courses related to educational technology, using text mining and qualitative methods to detect ethical content, alignment, and rationale. This process is structured around Biggs’ concept of curriculum alignment. For practices, ARS will engage participants through case-based learning, interactive tools, and future-oriented exercises to identify ethical gaps and propose improvements. Data collection follows GDPR standards, with informed consent, anonymization, and secure storage. Analyses will combine discourse, thematic, and sentiment analysis to inform the ETH-TECH framework. Data and outcomes will be shared via Zenodo for transparency and reuse. The document also includes a comprehensive Data Management Plan ensuring FAIR principles, long-term preservation, and ethical governance.