Within a university's practice-oriented education system, the incorporation of practical scientific applications into students’ areas of study can effectively cultivate a wide range of skills necessary for success in the modern era. Nevertheless, current research fails to conduct a methodical investigation into the fundamental aspects, models, and assessment criteria of popular scientific education. The capacity to analyze large datasets precisely offers opportunities for the development of an ecologically popular science education system. This study utilizes neuroscience and big data to develop a comprehensive popular science education model. The model consists of four dimensions: cultivating ecology based on data profiling, collaborative education ecology within and outside of schools, carrier ecology for three-dimensional development, and evaluation ecology from the perspective of data resource integration. This study may be tailored to the specific traits of students at various levels, harnessing their intrinsic drive for personal growth and advancement. As a result, it enhances the caliber and effectiveness of nurturing talent in higher education institutions, thereby boosting national innovation and development.