STEM and Data: Instructional Decision Making of Secondary Science and Mathematics Teachers
Abstract
This research is focused on the intersection of secondary teachers’ data-use to inform instructional decisions and their teaching of STEM in STEM-focused high schools. Teaching STEM requires presenting more than just the content knowledge of the STEM domains. The methods of inquiry (e.g., scientific inquiry, engineering design) are skills that should be taught as part of STEM activities (e.g., science labs). However, under the data- and standards-based accountability focus of education, it is unclear how data from STEM activities is used in instructional decision-making. While teachers give tremendous weight to the data they collect directly from their observations of their classrooms, it is data from standardized testing that strongly influences practices through accountability mandates. STEM education alters this scenario because, while there is a growing focus on teaching STEM, important aspects of STEM education are not readily standardized. This mixed-methods study will examine the perspectives of 9th through 12th grade science and mathematics teachers, in STEM-focused schools, on datause and STEM teaching. We developed a framework, adapted from existing frameworks of datause, to categorize these perspectives and outline contexts influencing them. Through a concurrent triangulation design we will combine quantitative and qualitative data for a comprehensive synthesis of these perspectives.
Degree
Ph.D.
Advisors
Kenney, Purdue University.
Subject Area
Mathematics education|Pedagogy|Educational technology|Education Policy|Science education|Continuing education|Curriculum development|Design|Education|Educational tests & measurements|Mathematics
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