Proceedings of the International scientific and practical conference ―Synergy of Modern Science and Education‖ (June 12-14, 2026) / Publisher website: www.naukainfo.com. – New York, USA, 2026. - 145 p.

86 The study demonstrates that generative artificial intelligence is particularly effective during the initial stages of inquiry-based learning, assisting students in formulating research problems, generating questions, developing hypotheses, and conducting information searches. ChatGPT and other AI tools are viewed not as sources of ready-made answers but as instruments that support brainstorming, the clarification of scientific concepts, and the generation of new ideas. The authors further emphasize that the use of AI promotes learner autonomy, facilitates the personalization of learning, and supports independent cognitive activity. In addition, artificial intelligence technologies can be employed to simulate experiments, analyze research procedures, and conduct preliminary evaluations of educational projects [8]. The study by H.-C. Yeh (2025) investigates the integration of generative artificial intelligence with inquiry-based learning (IBL) in the professional preparation of English language teachers. Drawing on the constructivist framework of inquiry-based learning, the author argues that generative AI contributes to the creation of a student-centered learning environment by supporting active inquiry, collaboration, and reflection. The findings of the empirical study, conducted with thirteen English language teachers, demonstrate the effectiveness of AI across all stages of inquiry-based learning, from identifying pedagogical problems to developing and evaluating instructional solutions. The results indicate that ChatGPT and other AI tools enhance opportunities for personalized learning, increase learner motivation, and stimulate cognitive engagement. The author emphasizes that generative artificial intelligence should serve as a tool for supporting heuristic inquiry by assisting users in formulating problem-based questions, generating innovative ideas, and refining pedagogical solutions, while the teacher increasingly assumes the role of a facilitator of inquiry- based learning. Although the study was conducted within the context of teacher education in Taiwan, its findings are highly relevant to the United States, as they confirm the effectiveness of integrating generative AI and heuristic learning in fostering critical thinking, creativity, professional autonomy, and the independent cognitive engagement of future teachers [11]. Conclusions. The analysis of contemporary international research demonstrates that heutagogy has emerged as one of the leading conceptual approaches to organizing self-determined learning and represents a logical extension of the heuristic educational paradigm. Its core principles include learner autonomy, learner agency, self-regulation, reflection, and lifelong learning, all of which are of particular importance in the professional preparation of future teachers. The findings indicate that contemporary artificial intelligence technologies provide extensive opportunities to support autonomous, personalized, and inquiry-based learning. Generative AI facilitates the adaptation of individualized learning pathways, delivers timely feedback, encourages independent knowledge construction, and promotes the development of critical thinking, reflective skills, and the professional autonomy of prospective teachers. A synthesis of recent international research further suggests that the integration of heuristic learning and artificial intelligence is most effectively implemented within problem-based, inquiry-based, and self- determined learning environments. In these contexts, AI functions as a cognitive partner that supports problem identification, idea generation, the evaluation of alternative solutions, and reflective analysis without replacing learners’ intellectual engagement. The review also confirms that heutagogical principles, learner agency, and self-regulated learning are essential factors in fostering the professional autonomy of future teachers. Their implementation enhances students’ ability to independently define learning objectives, plan and manage their educational activities, critically evaluate learning outcomes, and adapt to the dynamic changes of digitally mediated educational environments. Finally, the study concludes that integrating heuristic learning with artificial intelligence technologies represents a promising direction for modernizing teacher education in the United States. The effective combination of the heutagogical approach and AI capabilities contributes to the personalization of learning, the development of inquiry skills, creative and critical thinking, digital competence, and future teachers’ readiness for continuous professional growth in the context of the digital transformation of education. Therefore, the integration of heutagogical principles with generative artificial intelligence may be regarded as one of the most promising directions for transforming teacher education in the United States within the broader context of digital educational innovation.