FoResTCHAT: AI-Supported Resilience Building in Teacher Education
FoResTCHAT strengthens pre-service teachers’ resilience through AI-supported, personalized, and interactive digital learning.
Duration: January 2026 – December 2027
Status: Ongoing
Educational Level: Tertiary Level
Topic: Artificial Intelligence AI, Digital Tools
Keywords: Teacher Education, Psychological Resilience, Artificial Intelligence, Adaptive/Personalized Learning, Well-Being
Initial Situation
The teaching profession is under increasing pressure: shortages, high dropout rates, and growing mental health challenges affect early-career educators. Many feel overwhelmed or stressed, which can lead them to leave the profession, threatening both their well-being and educational quality. Resilience—the ability to adapt, cope, and use personal and social resources effectively—is a key skill for thriving in this demanding environment. Crucially, resilience can be strengthened, especially during the transition from university to professional teaching. Existing digital tools, such as the FoResT platform at PHBern, support pre-service teachers’ resilience but are mostly static and self-directed, offering limited interactivity and personalization. This restricts engagement and the capacity to address diverse learning needs. FoResTCHAT bridges this gap by integrating AI-powered, locally hosted large language models (LLMs) to create a highly interactive, personalized learning experience. Through dialogue-based reflection, adaptive tasks, and real-time feedback, the platform supports pre-service teachers in building coping strategies, enhancing motivation, and developing professional readiness—while safeguarding privacy and promoting ethical AI use.
Previous Project
In the previous project FoResT, a digital learning platform was developed, evaluated, and implemented to promote resilience among students in teacher education. The aim was to bridge research and practice, support individual learning processes, and, in the long term, strengthen both the health and media education competencies of the target group.
Objectives
FoResTCHAT strengthens pre-service teachers’ resilience by integrating AI-powered, interactive, and personalized learning into the FoResT platform. It fosters reflection, adaptive coping strategies, self-regulation, and professional readiness, while ensuring ethical, privacy-conscious AI use. The project evaluates effectiveness, usability, and learner acceptance to guide scalable implementation in teacher education.
Method
FoResTCHAT applies a mixed-methods approach to evaluate its impact on pre-service teachers. Five predefined use cases will be implemented in the AI-enhanced platform. Formative testing with PH Bern students will combine qualitative interviews and quantitative surveys (SUS, TAM) to assess usability and acceptance. Effectiveness is evaluated through a quasi-experimental study comparing FoResTCHAT with the original FoResT platform, using repeated self-assessments on resilience, well-being, motivation, adaptive coping, as well as engagement, personalization, and learner feedback.
Planned Translation
The FoResTCHAT will be gradually integrated into the BERG module at PHBern, beginning with pilot testing in fall semester 2026 and full implementation in spring semester 2027. Iterative refinements will be informed by student feedback to optimize usability and effectiveness. The continued collaboration with PHBern ensures alignment with teacher education practices. Insights and resources from BeeChat , a locally hosted alternative to commercial chatbot tools at Bern University of Applied Sciences, support the development of privacy-conscious AI tools. Lessons learned will be shared with other Swiss teacher education institutions for broader adoption. FoResTCHAT is expected to enhance pre-service teachers’ resilience, well-being, and adaptive coping, strengthening their preparedness for profession-specific challenges. By integrating AI-supported interactivity and personalization, the platform aims to boost engagement, motivation, and self-regulation. Impact will be measured through repeated self-assessments, qualitative feedback, and surveys on usability and acceptance. Insights will guide evidence-based improvements in teacher education, supporting scalable, effective, and ethically responsible digital learning interventions.
