This scoping and fact-finding WP will include the identification, gathering, sorting, and analysis of data (policies and curricula around youth activism) from numerous sources at national levels (Ministries of Education, NGOs, and foundations, etc.) and regional (as well as local) levels within each selected country. At this stage, policy documents on youth activism will also be gathered and analysed from supra-national organisations including the EU, OECD, UNESCO, and others. The focus of this analysis will be on documents from the last twenty years (2002-2023). All national documents will be organised in a custom-created database, coded, and analysed according to specific research questions. Supra-national, national, and regional policy documents will be compared nationally and internationally. The data will be analysed through a combination of Artificial Intelligence (AI) methodologies including Natural Language Processing (NLP), Networks Analysis (NA) and qualitative methodologies. Such a comprehensive database will be a vital resource for all stakeholders.
This WP will gather and analyse students’ (16-18 years old) perceptions of activism, its possible outcomes, and students’ perceptions around their appropriation of activism in their own lives and contexts. The main data collection phase will be the facilitation and execution of 180 discussion groups including local and migrant students in each of the locations (30 groups per country). The approach is based on Ross’s studies of youth political engagement (2018; 2020; 2021) and will facilitate small group deliberative discussions in which five to eight students will participate. The purpose of these discussion groups is to create a space in which young people feel free to discuss activism related topics with each other, on their own terms, using their own vocabulary, rather than acting merely as informants in the service of academia. STUDACT will deliver diversity in the locations, communities and contexts studied in the selected countries. Discussions will be recorded, transcribed, and translated. Subsequent STUDACT analysis will be performed in a constant comparative matter, between groups in different contexts and across countries. The analysis will be inductive, but thematic elements will be introduced in the later analytical stages.
This WP is inspired by documentary photographer Jim Hubbard, who provided cameras to homeless children, so they could reflect on their lives from their point of view. The images captured were brutal, sparking public discourse. As explained by Hemy and Meshulam (2021), this was the first time these children had been offered agency – a voice on issues related to their lives, so they could say “I am shooting back”. STUDACT will aim to reproduce this agentic mechanism, and make use of cameras as a powerful tool. It will allow them to record and reflect on their own interpretation and appropriation of activism, and invert the traditional power dynamic between students and schools, between taught curricula and student engagement, and between classroom and the outside world. In this WP 60 (16-18 years old) students (ten from each country) will be offered a tailor-made photographic training module and be provided with cameras for three months to document their experiences. They will be asked to document places, people, and situations in which they feel activism related topics are relevant, and encouraged to develop agentic behaviours. Support will be provided (e.g., online support module, 1:1 guidance by PhD students). All photographs will placed in a digital archive and analysed thematically and inductively.
This WP will experimentally investigate actual youth engagements on social media with activism related topics. It will specifically focus on four domains, (1) Climate crisis (2) Human rights, including gender equality (3) Body positive (4) Me too. In each country STUDACT will precisely identify, collect, codify, and analyse data scraped from Instagram, Tik-Tok and Twitter. Data collection will continue for one year. Socially active young people in each country will be identified using local media, local informants, and calibrated platform searches. Collected data will be coded and analysed using thematic and inductive analysis.