
This project addresses the disconnect between science, design, and technology and how high school students can benefit from innovative learning experiences in plant science that integrate these disciplines while gaining interest in and skills for future STEM careers. We created a research experience where students work in collaborative teams of self-identified science, technophile, and art students to create 3D models of plants under research at the Donald Danforth Plant Science Center. Through augmented and virtual reality immersive experiences, the students understand the benefits of integrating science, technology, and design. The students also practice their communication skills by disseminating their projects. We use a mixed-methods approach to assess changes in students’ understanding of the role of design and technology in STEM, gain of knowledge and appreciation of plant science, and development of interests in STEM subjects and careers. Preliminary results indicate that students are more aware of the role of design in science and vice versa and are more interested in STEAM subjects. Future results will provide a better understanding of the impact on plant awareness and interest in STEAM careers. This project will contribute to the body of knowledge on theory, best practices, and practical technological applications in STEAM education.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
