Traditional notions of “who counts” involve historically assigned classifications or categorizations of students by ethnicity or gender. “What counts” involves (narrowly) focusing on quickness or one correct pathway (represented by the instructor), as opposed to valuing actual scientific practices, such as collaboration, question- asking and data analysis. Learning how to effectively implement data-driven learning through the application of “Data Tasks” in ways that disrupt inequity in chemistry classrooms is challenging and requires significant shifts in faculty mindsets about “who counts” and “what counts” as competent in chemistry classrooms. Faculty mindset is the biggest contributor to the success of underrepresented students and understanding the basis of faculty beliefs is an important component of this process. This work will showcase work done on shifting faculty mindsets, beginning with examining their own STEM beliefs and bias, so that they can positively influence their teaching and their students. The application of these shifts to the use of “data tasks” on shifting student’s sense of themselves as chemistry learners, and on their persistence in STEM pathways after introductory chemistry.

The overall goal of our work is to disrupt pervasive narratives and misplaced assessments of what defines scientific brilliance, specifically in the introductory chemistry classroom. The traditional design of STEM courses perpetuates the narrow view that intelligence is characterized by innate talent, knowing lots of information, and being quick and correct. This view disproportionately impacts students historically underrepresented in STEM. Our group (The Chem Avengers) aim to transform chemistry education into an inclusive practice where all learners can thrive. The work reported here is focused on creating and implementing group worthy tasks that support equitable participation. These tasks center around sorting, using, and making sense of data, trends, and patterns and data presented suggest both shifts in mindset and GPA.

Carmen Bustos-Works

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