A Research Design for NASA-Funded Professional Development Projects

This proposal outlines a research plan designed to measure gains in student learning resulting from their teachers participating in professional development. Project Description Misconceptions about global climate change (GCC) are prevalent in the general public (Kellstedt, Zahran, & Vedlitz, 2008; Washington & Cook, 2011). One solution is to provide high school students with a better grounding in the basic science and data that underlie GCC. The overarching goal of a NASA-funded project, Promoting Educational Leadership in Climate Change Literacy (PEL), is to increase GCC literacy in high school students. Research Design The research design is interpretative (Erickson, 2006), framed within a multi-method design, synthesizing both quantitative and qualitative data sources (Morse, 2003). Overall, the data will provide rich information about the PEL's impact on curriculum development, teacher pedagogical knowledge, and student learning. The expectancy-value theory of achievement motivation (E-V-C) (Fan, 2011; Wigfield & Eccles, 1994) provides a theoretical foundation for the research. Expectancy is the degree to which a teacher or student has reason to expect that they will be successful in school. Value indicates whether they think that performance at school will be worthwhile to them. Cost is the perceived sacrifices that must be undertaken, or factors that can inhibit, a successful performance at school. For students, data from an embedded E-V-C investigation will help articulate how E-V-C factors relate to student interest in science, continuing to study science, or embarking on STEM related careers. For teachers, the E-V-C measures will give insight into a key mediating variable on student achievement in science. The evaluation will seek to address research questions at the student and teacher levels. Table 1 presents a sample of research questions and data sources. This is a sample of a much larger set of questions that will be addressed in the project. Data Analysis Data will be analyzed using a strategy developed by Huberman and Miles (2002). This methodology provides a framework for researchers to perform three research functions: 1) reduce the data to a subset of information (categories) without losing essential data, 2) display (matrices, maps, summaries) this information in a manner that facilitates group discussion and notation of consensus upon emerging patterns, and 3) draw and verify conclusions. The multiple sources of qualitative and quantitative data allow for triangulation of findings, which helps establish a measure of validity and reliability to final findings and recommendations for future research and changes to the project.<br />Table 1. Research Questions, Data Sources.
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