Research Areas

Teacher Education and Professional Development in Artificial Intelligence

AICult conducts research on how teachers can be effectively prepared to understand, use and critically evaluate Artificial Intelligence in educational contexts.
Our research area focuses on teacher education models, training delivery methods and risk awareness, with the goal of identifying evidence-based strategies for sustainable and responsible AI integration in schools.

Artificial Intelligence poses not only technological challenges, but also pedagogical, ethical and professional ones. For this reason, AICult approaches teacher training on AI as a long-term professional development process, rather than as isolated or purely technical instruction.

Research Focus 1: Models of Teacher Training on Artificial Intelligence

This research strand analyses different models of teacher education related to AI literacy, pedagogical integration and ethical awareness.

Key research questions

• Which training models most effectively support teachers’ understanding of AI concepts?

• How does AI training influence teachers’ pedagogical decision-making?

• What balance is needed between technical knowledge, didactic application and ethical reflection?
  
  

Research topics

• AI literacy frameworks for teachers

• Integration of AI into existing digital competence models (e.g. DigCompEdu)

• Pedagogical versus technocentric training approaches

• Long-term impact of AI training on teaching practices
  
  

Our studies confirm that integrated and pedagogically grounded models are more effective than short, tool-oriented courses, especially when aligned with teachers’ disciplinary contexts.

Research Focus 2: Effectiveness of Training Delivery Methods

A central area of AICult’s research concerns the modalities of training delivery and their impact on learning outcomes, professional confidence and classroom transfer.

Analysed training formats

• Face-to-face workshops

• Online synchronous training

• Asynchronous courses and MOOCs

• Blended and hybrid models

• Communities of practice and peer learning

• Project-based and inquiry-based professional development
  
  

Key findings

Research indicates that:

• Blended learning models outperform exclusively online or face-to-face formats in terms of retention and application;

• Active and experiential approaches (e.g. hands-on activities, scenario analysis, lesson co-design) significantly increase teachers’ confidence;

• Collaborative and reflective formats, such as communities of practice, support sustained professional growth;

• Training that includes classroom experimentation and feedback cycles leads to more meaningful pedagogical integration of AI.
  
  

These findings align with international evidence on effective professional development (OECD, 2020; UNESCO, 2023).

Research Focus 3: Pedagogical Integration of AI Tools

AICult investigates how teacher training influences the actual pedagogical use of AI tools in classrooms.

Areas of analysis

• AI as a support for lesson planning and differentiation

• AI-assisted formative assessment

• Generative AI for creativity and content creation

• Risks of over-automation in teaching practices
  
  

Research highlights the importance of helping teachers distinguish between pedagogically meaningful uses of AI and practices that merely replace professional judgement.

Research Focus 4: Ethical Awareness and Risk Perception in Teacher Training

A distinctive aspect of AICult’s work concerns the development of ethical awareness and risk perception among teachers.

Key dimensions

• Data protection and privacy in educational AI

• Bias, transparency and accountability

• Teacher responsibility and professional autonomy

• Student agency and critical thinking
  
  

Our studies suggest that ethical competence cannot be addressed through theoretical instruction alone, but requires case-based analysis, guided reflection and ethical dilemma discussion.

Ongoing Research: Teacher Awareness of Risks in Vibe Coding

AICult is currently developing a research project focused on teachers’ awareness of risks related to the use of “vibe coding” in education.

Research context

Vibe coding—understood as the practice of relying on generative AI to produce code or digital artefacts without a deep understanding of underlying logic—raises significant pedagogical and ethical concerns in educational settings.

Research objectives

• Analyse teachers’ understanding of vibe coding and its implications

• Investigate how vibe coding affects learning outcomes and computational thinking

• Identify perceived risks related to superficial learning, dependency and loss of agency

• Explore training strategies to promote critical and reflective use of generative AI in coding education
  
  

Methodology

• Teacher surveys and structured questionnaires

• Focus groups and interviews

• Classroom-based case studies

• Comparative analysis across educational levels
  
  

This research aims to support the development of responsible AI-supported coding education, aligned with human-centred and educationally sound principles.

Impact and Outcomes

The outcomes of AICult’s research in this area include:

• Evidence-based guidelines for AI teacher training

• Professional development frameworks

• Policy-oriented recommendations

• Open educational resources for teacher educators
  
  

Looking Ahead

AICult continues to expand its research on teacher education and Artificial Intelligence, with particular attention to:

• emerging AI practices in classrooms,

• evolving regulatory frameworks,

• the long-term professional identity of teachers.
  
  

Our goal is to contribute to a scientifically grounded, ethically responsible and pedagogically meaningful approach to AI in education.

Se desidera, nel prossimo passo posso:

• trasformare questa pagina in versione sintetica per stakeholder

• preparare indicatori di valutazione per la ricerca

• progettare il questionario di ricerca sulla consapevolezza del vibe coding

• adattare il testo per bandi PNRR / Erasmus+ / Horizon Europe