Chapter 15: Bridging the Disconnect Between How We do and Teach Science: Cultivating a Scientific Mindset in an Era of Data-Driven Education

The above are sentiments heard over years of researching postsecondary education improvement. All reflect, in one way or another, educators’ suspicion of using instruction-related data to improve curriculum, instruction, and programming. Policy makers, education leaders and researchers, and parents and students alike may be discouraged by what may appear to be educators dismissing this cornerstone of good teaching practice. Indeed, past research indicates that most postsecondary educators may not consider the collection of or reflection on instructional data to be their responsibility (Blaich & Wise, 2010). As well, these educators may not have access to meaningful instructional data (Blaich & Wise, 2010; Jenkins & Kerrigan, 2008), may not possess competencies to analyze it (Jenkins & Kerrigan, 2008), or may not have the time to engage in data-driven decision-making concerning teaching practice (Anderson, 2006; Julian & Ofori-Dankwa, 2006). Even those trained in the STEM disciplines (science, technology, engineering, and mathematics), assumed to possess requisite data-related abilities and commitments per their disciplinary training, have shown limited instructional data use (Bouwma-Gearhart & Hora, 2016).