Artificial intelligence and healing education: bibliotherapy and musicotherapy in primary schooling – an innovative theoretical model of Bibliotherapy and Musicotherapy Questionnaire (BMQ)

Contemporary approaches to teaching children’s literature and music education are increasingly replacing traditional pedagogical methods. The emergence of artificial intelligence (AI) has made these processes more dynamic and complex, presenting both opportunities and challenges for educators and pupils. This development raises important questions about teachers’ readiness to adopt innovative methodologies and pupils’ receptiveness to deeper learning and improved outcomes through AI-enhanced instruction. Children’s literature and music possess the capacity to educate, nurture, and heal. Their interdisciplinary nature provides primary school teachers with a rich foundation for creative and integrative teaching strategies, particularly relevant in the age of AI. This paper advocates for the deliberate integration of AI and healing education into the teaching of children’s literature and music at the primary level. It proposes that such integration can be achieved through creative and interdisciplinary applications of AI tools, alongside bibliotherapeutic and musicotherapeutic methods. The central methodological framework employed is mood mapping. The study examines the use of the Donna AI Song Generator within healing education, aiming to identify optimal strategies for both teachers and pupils. These findings may inform the development of diverse teaching methodologies and offer insights into the creative use of AI in interdisciplinary primary education. Additionally, the paper introduces an innovative conceptual framework – the Bibliotherapy and Musicotherapy Questionnaire (BMQ) – proposed as a theoretical model for future implementation in primary education settings. Although conceptual and theoretical in nature, the study is grounded in extensive practical teaching experience and the integration of AI tools, particularly within healing education. The BMQ model demonstrates adaptability to diverse instructional contexts and age groups, offering potential for future empirical validation and practical classroom application. Ultimately, this research highlights the transformative potential of AI in fostering holistic, creative, and therapeutic learning environments in primary education.