- Year 2023
- NSF Noyce Award # 2150702
- First Name Nancy
- Last Name Moreno
- Discipline Data Science, Life Sciences
Antonie Rice, Gad Shaulsky
Data-driven discovery—finding answers to complex questions through exploration and analysis of large data sets—is a high priority across all areas of science and engineering research and education. Yet, most science, technology, engineering or mathematics (STEM) teachers have little experience with how STEM fields are being transformed by novel approaches to “big data.” Accordingly, our project is designed to provide future STEM teachers with background and experiences that will help prepare them to offer their learners: 1) guidance about authentic STEM careers related to data science to their students, and 2) classroom experiences that incorporate modern data science approaches.
Overall, our work intends to provide and evaluate the effectiveness and impact of STEM research experiences for pre-service STEM teachers in data analytics. Accordingly, this project is guided by two main evaluation questions related to our pre-service teachers’ experiences: 1) To what extent do teachers’ knowledge and skills related to the nature of science, science inquiry and the application of data analytics change due to participation?; 2) Are pre-service teachers’ science teaching efficacy beliefs and science identities enhanced through participation?
Our project engages future STEM teachers in real-world life science investigations using data mining, visual and analytical approaches to expand their skills and understandings related to analysis of large data sets and the nature of scientific discovery; and enhance their identities as members of the scientific community. Authentic research opportunities have potential to allow “newcomers” to develop habits of mind, skills and knowledge that enable legitimate participation in the community of practice of scientists. Research experiences for pre-service or in-service teachers have contributed to increased understanding of the processes of scientific inquiry, opportunities to learn the language of science, persistence in teaching careers and better learning outcomes for K–12 STEM students.
Accordingly, we first provide a one-week data analytics course to prepare participants to enter labs engaged in a range of data-intensive bioscience research in fields such as genomics, molecular and cellular biology, neuroscience and bioinformatics. We then partner these pre-service STEM teachers with active researchers during a five-week-long summer research experience that also includes seminars and other enrichment activities to help prepare them to translate these experiences to their future classrooms.
Overall, participating pre-service teachers in the first year of the program self-reported increases their knowledge and skills related to the nature of science, science inquiry and the application of data analytics. Specifically, they noted increased knowledge related to the day-to-day work of scientists (pre-M=1.50, post-M=3.33 on a 5-point scale), abilities to analyze (pre-M=2.33, post-M=3.17) and interpret scientific data (pre-M=2.17, post-M=2.67), and explain data concepts to others (pre-M=1.67, post-M=2.33). All participants also rated the quality of the program highly and all agreed that they felt prepared to mentor students interested in STEM careers and intend to incorporate data science into their future STEM classes. We are currently recruiting for the 2023 summer cohort and intend to deepen and improve the project through enhanced school-year sessions, as well as provide experiences explicitly designed to enhance participants’ identities as members of the community of scientists.
BCM’s Pre-Service Teacher Summer Research program engages six pre-service STEM teachers per year in authentic research related to life sciences data mining and analysis. These individuals have potential to reach as many as 9,000 secondary students in STEM classes after five years. Evaluations of long-standing NSF-funded research experiences for teachers have shown that such programs improve teachers’ understanding of the nature of scientific inquiry and abilities to communicate the concepts and value of science to students. We expect that program participants will acquire these understandings while also learning how scientists explore complex data sets and be able to impart these views of science to students in the future. Participation in research experiences and connection to a broader community increases teacher enthusiasm and self-efficacy, and ultimately enhance job satisfaction and the likelihood that teachers will remain in teaching positions. Thus, the project has potential to contribute to 1) STEM teacher retention, and 2) exposing secondary school students to concepts of data analytics and the work of scientists. We are currently recruiting for the 2023 summer cohort and intend to deepen and improve the project through enhanced school-year sessions to broaden our participants’ knowledge related to applying data science to their classrooms. We are also working to provide additional experiences explicitly designed to enhance participants’ identities as members of the community of scientists.