Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item Supporting data-intensive environmental science research: data science skills for scientific practitioners of statistics(Montana State University - Bozeman, College of Letters & Science, 2020) Theobold, Allison Shay; Chairperson, Graduate Committee: Stacey Hancock; Stacey Hancock was a co-author of the article, 'How environmental science graduate students acquire statistical computing skills' in the journal 'Statistics education research journal' which is contained within this dissertation.; Stacey Hancock and Sara Mannheimer were co-authors of the article, 'Designing data science workshops for data-intensive environmental science research' submitted to the journal 'Journal of statistics education ' which is contained within this dissertation.; Stacey Hancock was a co-author of the article, 'Data science skills in data-intensive environmental science research: the case of Alicia and Ellie' submitted to the journal 'Harvard data science review' which is contained within this dissertation.The importance of data science skills for modern environmental science research cannot be understated, but graduate students in these fields typically lack these integral skills. Yet, over the last 20 years statistics preparation in these fields has grown to be considered vital, and statistics coursework has been readily incorporated into graduate programs. As 'data science' is the study of extracting value from data, the field shares a great deal of conceptual overlap with the field of Statistics. Thus, many environmental science degree programs expect students to acquire these data science skills in an applied statistics course. A gap exists, however, between the data science skills required for students' participation in the entire data analysis cycle as applied to independent research, and those taught in statistics service courses. Over the last ten years, environmental science and statistics educators have outlined the shape of the data science skills specific to research in their respective disciplines. Disappointingly, however, both sides of these conversations have ignored the area at the intersection of these fields, specifically the data science skills necessary for environmental science practitioners of statistics. This research focuses on describing the nature of environmental science graduate students' need for data science skills when engaging in the data analysis cycle, through the voice of the students. In this work, we present three qualitative studies, each investigating a different aspect of this need. First, we present a study describing environmental science students' experiences acquiring the computing skills necessary to implement statistics in their research. In-depth interviews revealed three themes in these students' paths toward computational knowledge acquisition: use of peer support, seeking out a 'singular consultant,' and learning through independent research. Motivated by the need for extracurricular opportunities for acquiring data science skills, next we describe research investigating the design and implementation of a suite of data science workshops for environmental science graduate students. These workshops fill a critical hole in the environmental science and statistics curricula, providing students with the skills necessary to retrieve, view, wrangle, visualize, and analyze their data. Finally, we conclude with research that works toward identifying key data science skills necessary for environmental science graduate students as they engage in the data analysis cycle.Item Authentic science research in the classroom: does it promote science-related affective growth?(Montana State University - Bozeman, College of Letters & Science, 2020) Shulstad, Andrew Michael; Chairperson, Graduate Committee: Greg FrancisThe purpose of this concurrent mixed methods study was to investigate the effects of middle school science students' participation in authentic science research on their science-related affective characteristics. The affective characteristics considered for this study were those that have been repeatedly shown to be associated with student cognitive growth and academic achievement. These included science identity, science self-efficacy, interest and enjoyment of science, perceived relevance of science, and intrinsic motivation for science learning. Four authentic science treatments involving eight different classes and 166 total participants (120 unique) were administered. Data collection methods included novel Likert scales based on a novel student survey instrument, a naturalistic observation instrument, student interviews, and various formative assessments. Data were collected before, during, and after each treatment with the primary purpose of supporting a before versus after comparative research design. Data analysis strategies included validation and reliability analysis of the student survey instrument and Likert scales and a triangulated complex of inferential comparative quantitative analysis and thematic qualitative analysis. While effect size was small, student affective domain growth was determined to have taken place. Affective characteristics that were shown to be strengthened in a statistically significant way (p<0.05) include science identity, interest and enjoyment of science, and intrinsic motivation for science learning. Though it has some limitations, such as a significant time requirement, authentic science research in the classroom should be considered an effective way to promote student science-related affective growth.Item The influence of transformational leadership and diversity climate on using TRIZ to generate ideas: a case study from UAE companies(Montana State University - Bozeman, College of Engineering, 2019) AlDhaheri, Abdulla Saeed Obaid Saeed; Chairperson, Graduate Committee: Bill SchellThe rapidly changing dynamics in global industry are forcing companies to continually improve methods for harnessing the creativity of their employees and to use that creativity to drive innovation. Frequently, projects to develop new products fail at the end of the development process or during commercialization. These failures often have their origin at the very beginning of the development process, during the pre-development phase called the Fuzzy Front End (FFE). To manage this phase, there is a need to focus on idea and concept generation, for instance by using new techniques like the Theory of Inventive Problem Solving (TRIZ). To improve the pre-development activities in the FFE phase, there is a further need to understand how TRIZ methods interact with transformational leadership behaviors and team make-up to improve the effectiveness of the FFE. Prior work has shown that transformational leadership has positive impacts on organizational outcomes, including improved performance of research and development (R&D) functions. This research applied TRIZ problem-solving in several semi-government companies in the United Arab Emirates (UAE) and investigated the influence of leadership, diversity climate, knowledge management practices and organizational change variables, to measure participants' perception of being able to apply TRIZ in problem-solving. Measures of team performance during a two-day TRIZ session were also made using organization-specific challenges. A Structural Equation Model (SEM) was utilized to understand the relationships between the measured factors. Hypothesis analysis showed that transactional leadership did not support knowledge management practices while group and organizational diversity climates positively impacted knowledge management practices and particpants' perception on being able to apply TRIZ. Transformational leadership, knowledge management practices, and organizational change positively impact participants' perception of being able to apply TRIZ. The implications are as follows: the full range of the leadership model along with group and organizational diversity climate strongly effect the relationship between knowledge management practices and particpants' perception of being able to apply TRIZ. The presence of transformational leadership improved the particpants' perception of being able to apply TRIZ in problem-solving. Workers' knowledge converted information into a general solution based on TRIZ training outcomes.Item Outdoor education and citizen science in a high school freshwater ecology science classroom(Montana State University - Bozeman, College of Letters & Science, 2019) Tierney, Sarah Martina; Chairperson, Graduate Committee: Greg FrancisOutdoor education and citizen science practices were implemented into a high school freshwater ecology curriculum to assess student motivation, attitude, and in general their connection with the outside world. In this study students were exposed to various outdoor learning opportunities and citizen science activities. Pre and post treatment student surveys were conducted, student interviews, student journaling, and student engagement tally sheets were all recorded to assess student engagement. As a result of this study, a majority of students reported a benefit from lessons outside the classroom as well as indicating an increase of energy, pleasantness, and engagement.Item An analysis of fossil identification guides to improve data reporting in citizen science programs(Montana State University - Bozeman, College of Letters & Science, 2018) Butler, Dava; Chairperson, Graduate Committee: Greg FrancisAn increasing number of organizations use untrained volunteers to gather scientific data. This citizen science movement builds enthusiasm for science by engaging the public, as well as providing a way to gather large amounts of information at little or no expense. The challenge of citizen science is obtaining accurate information from participants. Identifying an image style that increases correct identifications helps not only the citizen science movement but also scientific instruction in general. This study tests three visual guides for identifying late Hemphillian (5-4.5 m.y.a.) fossils from Polk County, Florida. Each guide has identical layout and text, differing only in image style: color photos, grayscale photos, or illustrations. Teams of untrained participants each use one guide to identify fossils. Geology and paleontology professionals also identify fossils for comparison. Comparing results reveals that photographic images, either color or grayscale, produce results most similar to data from professionals.Item Citizen science in a high school science classroom(Montana State University - Bozeman, College of Letters & Science, 2019) McAndrews, Sean David; Chairperson, Graduate Committee: Greg FrancisThis study was conducted to determine the impact of adding citizen science projects into a high school science classroom. The primary question of interest was what impact does the inclusion of citizen science projects have on student achievement? I was also interested in evaluating student attitudes about science before and after taking part in citizen science projects, as well as student perceptions of taking part in 'real science' activities in class. Students participated in a pre-treatment test and survey to measure their knowledge and interest in science. They participated in online citizen science projects for three weeks. At the end of the treatment, students completed a post-test and post-survey to measure changes in knowledge, attitudes, and confidence. Observations of student behavior in class during participation in the project were documented. Finally, randomly-chosen students participated in exit interviews about the project. Student scores on the assessment did show a small increase when compared to pre-treatment values. Measures and observations of student attitudes such as the survey, student journals, and post-treatment interviews did indicate that many students enjoyed participating the project, and that they did perceive that they were assisting with authentic science projects. These results align with previous research studies on the value of incorporating citizen science projects into classrooms. This project allowed me to incorporate new activities and ways of teaching into my science classroom. I was able to test these new activities and methods and evaluate their effectiveness. This will serve as the basis for similar future projects.Item Field science experiences in paleontology: shaping science stewardship in high school learners(Montana State University - Bozeman, College of Letters & Science, 2019) Lepore, Taormina Jean; Chairperson, Graduate Committee: Greg FrancisHow do field science experiences shape a sense of conservation and stewardship in learners? This study analyzed separate groups of female-identifying and male-identifying 9th grade high school students (N=80) on their first field paleontology experience at Rainbow Basin Natural Area, California. Likert-style surveys and written self-reflections indicate relative consistency in pre- and post-treatment responses student-to-student, through when paired with qualitative responses, the power of science stewardship and a personal sense of connection to public lands becomes markedly apparent. Future studies in the realm of science stewardship in field paleontology will help illuminate the impact of field paleontology on science learners.Item Implementing a citizen science project in a 9-12 high school science classroom(Montana State University - Bozeman, College of Letters & Science, 2019) Langager, Paula Marie; Chairperson, Graduate Committee: Walter WoolbaughThis classroom action research (AR) project explored the impacts of project-based learning on high school students critical thinking, decision-making, data collection and data analysis skills through the implementation of a citizen science project. AP® Environmental Science (APES) students co-developed a citizen science project that explored their local schoolyard biodiversity by designing and researching their own scientific investigative question. An evaluation of students changes in science self-efficacy, and attitudes toward science research and specific science tasks was tracked throughout the project. Pre- and post-Likert surveys, open-ended questions, field journals, focus group interviews, and a biological solutions science poster were employed as data collection tools. A mixed methodology (qualitative and quantitative) was used to analyze the data. These results showed that students made reasonable gains in data collection and analysis skills, critical thinking and decision-making abilities. Noticeable improvements were detected in student attitudes toward science and science self-efficacy. A discernable change was observed in the student's overall data and data analysis skills related to a field study.Item Analysis and implementation: converging intent based production and high speed research networks(Montana State University - Bozeman, College of Engineering, 2019) Hess, Gregory Martin; Chairperson, Graduate Committee: Mike WittieThis thesis analyzes the performance impact of converging an intent-based production network with a high-performance research network. The previous solution for high performance research networks was to segregate these networks [1]. This solution created a physically separate network dedicated to the researcher and used for high speed data transmissions. This model has been successfully utilized for years however current refresh cycles are force academic institutions to confront the ongoing maintenance of these boutique networks. Some institutions have noted their investment in their production networks have created performance to rival that of the dedicated network. For these institutions convergence to one network proves to be a viable strategic option. Additionally, vendors are going to market with intent based or software defined networking which answers many of the challenges that required the physical separation of networks. The advantages of both converged networks as well as software defined networks are well documented. Both campus Information Technology departments and the researches with this high-performance needs are in need of a quantitative analysis to understand the performance or security trade-offs associated with moving research onto a production, intent-based network. This thesis addresses this question by measuring and comparing key performance metrics of a traditional high-performance research network, a traditional production network, and a converged Intent-Based network in the same three labs at the same institution (Montana State University). The results prove that a converged, intent based network delivers the same (or superior) performance as the previous model with the same or superior level of segregation (security). These results give institutions the ability to shed the traditional, utilitarian use of institutional networks in favor of a dynamic network model based on the identity and use of the network rather than the physical location.Item Exploring the feasibility of an automated biocuration pipeline for research domain criteria(Montana State University - Bozeman, College of Engineering, 2019) Anani, Mohammad; Chairperson, Graduate Committee: Indika KahandaResearch on mental disorders has been largely based on manuals such as the ICD-10 (International Classification of Diseases) and DSM-V (the Diagnostic Statistical Manual of Mental Disorders), which rely on the signs and symptoms of disorders for classification. However, this approach tends to overlook the underlying mechanisms of brain disorders and does not express the heterogeneity of those conditions. Thus, the National Institute of Mental Health (NIMH) introduced a new framework for mental illness research, namely, Research Domain Criteria (RDoC). RDoC is a research framework which utilizes various units of analysis from genetics, neural circuits, etc., for accurate multi-dimensional classification of mental illnesses. The RDoC framework is manually updated with units of analysis in periodic workshops. The process of updating the RDoC framework is accomplished by researching relevant evidence in the literature by domain experts. Due to the large amount of relevant biomedical research available, developing a method to automate the process of extracting evidence from the biomedical literature to assist with the curation of the RDoC matrix is key. In this thesis, we formulate three tasks that would be necessary for an automated biocuration pipeline for RDoC: 1) Labeling biomedical articles with RDoC constructs, 2) Retrieval of brain research articles, and 3) Extraction of relevant data from these articles. We model the first problem as a multilabel classification problem with 26 constructs of RDoC and use a gold-standard dataset of annotated PubMed abstracts and employ various supervised classification algorithms. The second task classifies general PubMed abstracts relevant to brain research using the same data from the first task and other unlabeled abstracts for training a model. Finally, for the third task, we attempt to extract Problem, Intervention, Comparison, and Outcomes (PICO) elements and brain region mentions from a subset of the RDoC abstracts. To the best of our knowledge, this is the first study aimed at automated data extraction and retrieval of RDoC related literature. The results of automating the aforementioned tasks are promising; we have a very accurate multilabel classification model, a good retrieval model, and an accurate brain region extraction model.