Mixed-methods study explores vocal educators’ hopes and concerns about AI integration, suggesting strategies for effective use.
Artificial Intelligence (AI) is emerging as a valuable tool in education, with the potential to expand opportunities for educators and students. While research specifically focused on vocal educators remains scarce, understanding their perspectives is essential for ensuring AI’s ethical and practical integration into vocal instruction. This study explores vocal educators’ hopes and concerns about AI to recommend actionable strategies for effective integration. An explanatory sequential mixed-methods design was employed, with 34 vocal educators completing an online questionnaire incorporating Stein et al.’s (2024) Attitudes Towards Artificial Intelligence Scale (ATTARI-12), followed by semi-structured interviews with nine participants. Quantitative data were analysed using statistical methods, and qualitative data were evaluated through inductive analysis. Results of this study suggest vocal educators are cautiously optimistic, with Likert means ranging from 2.59 to 3.44 on a five-point scale, and two primary themes emerging: Conditions for AI Integration and Potential Uses for AI. This study proposes a model of AI integration grounded in pedagogical relevance, peer engagement, and practitioner-informed governance, positioning vocal educators as essential contributors to AI tool development.
No takes yet. Share an insight, caveat, or question.
Wende Donahue (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: