The Utilization of Canva Magic Box and Meta AI in Developing Instructional Presentations: Its Perceived Usefulness Among Secondary Teachers.
DOI:
https://doi.org/10.5281/zenodo.20813738Keywords:
Canva Magic Studio,, Meta AI, Instructional Presentations, Secondary Teachers, Perceived Usefulness, Technology Acceptance Model TAMAbstract
This study investigated the perceived usefulness of creative design and conversational artificial intelligence AI tools in developing digital learning materials among secondary school educators. Anchored on the Technology Acceptance Model TAM, the research employed a quantitative descriptive-correlational design to evaluate the instructional utility of Canva Magic Studio Magic Box and Meta AI. Data were gathered through a validated Likert scale survey administered via purposive sampling to the faculty of Pines City National High School in Baguio City across various academic disciplines. Descriptive analysis revealed that both platforms are highly valued, though Canva Magic Studio achieved a significantly higher overall mean rating described as Strongly Agree compared to Meta AI which was rated as Agree. A paired sample t-test demonstrated that Canva significantly outperformed Meta AI in quality of output and user satisfaction, while no significant difference was observed in time efficiency, establishing that workload reduction is a universal benefit of both platforms. Correlational analysis indicated that self-digital literacy and prior AI experience are the sole significant predictors of Meta AI’s perceived utility, whereas structural profile variables such as years of teaching service and subject specialization showed no significant relationship. The study concludes that technical proficiency, rather than generational age, dictates successful AI integration. It recommends that institutional administrators formalize a leveled, hybrid AI workflow utilizing conversational AI for content ideation and specialized design platforms for visual synthesis alongside prompt engineering training to optimize future-ready lesson delivery.
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