RESILIENT WOMEN, METISTIC SCIENTISTS: A MULTIPLE CASE STUDY OF HOW WOMEN NEGOTIATE THEIR SITUATEDNESS IN SCIENCE FIELDS

The concept of feminist metistic resilience postulates that the voiceless, the marginalized and the minority in societies employ strategies in order to turn tables in their favor. This study presents a qualitative analysis of how women, considered to be the minority, negotiate their situatedness in science fields in order to effect change in their lives or that of the society and why they become successful. By “situatedness,” I refer to the everyday life of women as they live and encounter people, society and culture, especially, the life of women who have transcended the culturally stipulated role of women and are excelling in a male dominated field. The study, in different dimensions, conceptualizes the reason for the fewer number of women in science; looks at how scientific methods and practices inhibit the development of women in science; and, finally, interrogates the question of objectivity in science. It becomes apparent, through feminist metistic resilience, that women become successful when they accept conventional practices in scientific arrangements and structures. They accept the practices by embracing and not questioning structures and arrangements that have shaped the field of science and by shifting shapes and assuming different forms in order to adapt to conditions they encounter. Apart from adapting and shape shifting, the women also become successful through environmental and social influences. My analysis suggests that more women can be encouraged to pursue science when women practicing science begin to question structures and arrangements that have shaped the practice of science over the centuries. The overall findings of the research provide implications for policy makers, educators and feminist researchers.

INVESTIGATION OF STRATEGIES TO PROMOTE EFFECTIVE TEACHER PROFESSIONAL DEVELOPMENT EXPERIENCES IN EARTH SCIENCE

This dissertation serves as a call to geoscientists to share responsibility with K-12 educators for increasing Earth science literacy. When partnerships are created among K-12 educators and geoscientists, the synergy created can promote Earth science literacy in students, teachers, and the broader community. The research described here resulted in development of tools that can support effective professional development for teachers. One tool is used during the planning stages to structure a professional development program, another set of tools supports measurement of the effectiveness of a development program, and the third tool supports sustainability of professional development programs. The Michigan Teacher Excellence Program (MiTEP), a Math/Science Partnership project funded by the National Science Foundation, served as the test bed for developing and testing these tools. The first tool, the planning tool, is the Earth Science Literacy Principles (ESLP). The ESLP served as a planning tool for the two-week summer field courses as part of the MiTEP program. The ESLP, published in 2009, clearly describe what an Earth science literate person should know. The ESLP consists of nine big ideas and their supporting fundamental concepts. Using the ESLP for planning a professional development program assisted both instructors and teacher-participants focus on important concepts throughout the professional development activity. The measurement tools were developed to measure change in teachers’ Earth science content-area knowledge and perceptions related to teaching and learning that result from participating in a professional development program. The first measurement tool, the Earth System Concept Inventory (ESCI), directly measures content-area knowledge through a succession of multiple-choice questions that are aligned with the content of the professional development experience. The second measurement, an exit survey, collects qualitative data from teachers regarding their impression of the professional development. Both the ESCI and the exit survey were tested for validity and reliability. Lesson study is discussed here as a strategy for sustaining professional development in a school or a district after the end of a professional development activity. Lesson study, as described here, was offered as a formal course. Teachers engaged in lesson study worked collaboratively to design and test lessons that improve the teachers’ classroom practices. Data regarding the impact of the lesson study activity were acquired through surveys, written documents, and group interviews. The data are interpreted to indicate that the lesson study process improved teacher quality and classroom practices. In the case described here, the lesson study process was adopted by the teachers’ district and currently serves as part of the district’s work in Professional Learning Communities, resulting in ongoing professional development throughout the district.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.