supervisors: Hannie Gijlers
Education is universally acknowledged as a vital tool for addressing climate change, equipped to empower individuals with the essential knowledge and skills needed for action. Despite this, findings from EU surveys reveal that current educational frameworks fall short in fully accomplishing these objectives (European Commission, Directorate-General for Education, Youth, Sport and Culture, 2019). A significant number of youths feel unprepared by their school curriculums to either understand or respond effectively to climate change. This underscores an immediate need for substantial educational reform, particularly within Climate Change Education (CCE). To address these challenges, we have designed a collaborative learning environment specifically tailored for high school students. This environment features two unique 30-minute tasks that encourage active discussion and teamwork among students, designed to deepen their comprehension of climate change and to assess shifts in their attitudes towards sustainable actions:
- Collaborative Learning without Clair Intervention: Students will engage in traditional collaborative learning methods, relying on peer interactions without technological mediation.
- Collaborative Learning with Clair: Students will interact with Clair, a conversational AI agent, specifically designed to facilitate and enhance their discussions by providing guided prompts.
Method
This experimental study will adapt and implement an existing collaborative learning environment in a high school setting. Data collection will involve logging interactions within the learning environment and gathering responses through surveys and questionnaires before and after the completion of the tasks. The effectiveness of these educational interventions will be evaluated by examining changes in students’ understanding of climate change concepts and their attitudes towards taking sustainable actions. This method will allow us to measure the efficacy of traditional versus AI-enhanced collaborative learning in improving students' understanding of and attitudes toward climate change. Moreover, we you will investigate how students respond to Clair, by examining the dialogue.
references
de Jong, T. (2019). Moving towards engaged learning in STEM domains; there is no simple answer, but clearly a road ahead. Journal of computer assisted learning, 35(2), 153-167.
European Commission, Directorate-General for Education, Youth, Sport and Culture. (2019). How do we build a stronger, more united Europe? – The views of young people – Report. Publications Office. https://data.europa.eu/doi/10.2766/53982
Wang, C. Y. (2022). Exploring the Relationships Among Prior Knowledge, Perceptions of Climate Change, Conceptual Understanding, and Scientific Explanation of Global Warming. In Innovative Approaches to Socioscientific Issues and Sustainability Education: Linking Research to Practice (pp. 291-311). Singapore: Springer Nature Singapore.
de Araujo, A., Papadopoulos, P. M., McKenney, S., & de Jong, T. (2023). Automated coding of student chats, a trans-topic and language approach. Computers and Education: Artificial Intelligence, 4, 100123.
de Araujo, A., Papadopoulos, P. M., McKenney, S., & de Jong, T. (2024). A learning analytics‐based collaborative conversational agent to foster productive dialogue in inquiry learning. Journal of Computer Assisted Learning. 1–15. https://doi.org/10.1111/jcal.13007