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The lack of computer science education in rural areas presents unique challenges in the present pursuit of achieving equitable access to computer science education. The increase in the recognition of the need for computer science education comes with a need for inclusion of rural areas, and a corresponding increase in the demand of competent computer science teachers and educators. Teacher training programs play an important role in meeting these demands. This paper evaluates the impact of a teacher training program with focus on professional identity, commitment, confidence and competence as it relates to the teaching of computer science. The research includes teachers from rural, suburban and town locales enrolled in three separate semester courses. Through a mixed-method design, it uses quantitative data obtained through surveys taken prior to and at the completion of the training program to measure the impact. A combination of p-values and effect sizes were used to measure the impact of the teacher training programs. The survey covers three different domains - Teacher and Computing Identity, Rural Identity and Teacher Mindset, and lastly, Teaching Perceptions and Computational Thinking. Qualitative data gathered through reflective journals provides insights into teachers’ backgrounds and teaching experiences as well as anticipated professional growth. Following the training, findings show that rural teachers reported positive shifts in their identities and teaching competencies and are more likely to advocate for more students to take computer science courses. Teachers from the rural locales also showed a marked improvement in confidence and commitment to teaching computer science. 

Students at the Rochester Institute of Technology and Dowling College used bioinformatics software, which they had helped develop, to predict the function of protein structures whose functions had not been assigned or confirmed. Over the course of time, they incorporated other bioinformatics tools and moved the project to the wet lab, where they sought to confirm their in silico predictions with in vitro assays. In this process, we saw so much personal and professional growth among our students that we chose to implement their approach in an undergraduate biochemistry teaching lab, which we call BASIL, for Biochemistry Authentic Scientific Inquiry Lab. This curriculum has now been implemented by thirteen faculty members on eight campuses, and we look forward to a long-range exploration of BASIL’s impact on the students who enroll in courses that use the BASIL curriculum. 

Students at the Rochester Institute of Technology and Dowling College used bioinformatics software, which they had helped develop, to predict the function of protein structures whose functions had not been assigned or confirmed. Over the course of time, they incorporated other bioinformatics tools and moved the project to the wet lab, where they sought to confirm their in silico predictions with in vitro assays. In this process, we saw so much personal and professional growth among our students that we chose to implement their approach in an undergraduate biochemistry teaching lab, which we call BASIL, for Biochemistry Authentic Scientific Inquiry Lab. This curriculum has now been implemented by thirteen faculty members on eight campuses, and we look forward to a long-range exploration of BASIL’s impact on the students who enroll in courses that use the BASIL curriculum.