Matching Items (101)
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There is increasing interest in understanding how active learning affects students’ mental health as science courses transition from traditional lecture to active learning. Prior research has found that active learning can both alleviate and exacerbate undergraduate mental health problems. Existing studies have only examined the relationship between active learning and

There is increasing interest in understanding how active learning affects students’ mental health as science courses transition from traditional lecture to active learning. Prior research has found that active learning can both alleviate and exacerbate undergraduate mental health problems. Existing studies have only examined the relationship between active learning and anxiety. No studies have examined the relationship between active learning and undergraduate depression. To address this gap in the literature, we conducted hour-long exploratory interviews with 29 students with depression who had taken active learning science courses across six U.S. institutions. We probed what aspects of active learning practices exacerbate or alleviate depressive symptoms and how students’ depression affects their experiences in active learning. We found that aspects of active learning practices exacerbate and alleviate students’ depressive symptoms, and depression negatively impacts students’ experiences in active learning. The underlying aspects of active learning practices that impact students’ depression fall into four overarching categories: inherently social, inherently engaging, opportunities to compare selves to others, and opportunities to validate or invalidate intelligence. We hope that by better understanding the experiences of undergraduates with depression in active learning courses we can create more inclusive learning environments for these students.

ContributorsAraghi, Tala (Author) / Cooper, Katelyn (Thesis director) / Brownell, Sara (Committee member) / Busch, Carly (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05
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Mounting evidence suggests that gender biases favoring men and racial biases favoring whites and Asians contribute to the underrepresentation of women and underrepresented minorities (URM) in science, technology, engineering, and mathematics (STEM). Systemic issues caused by gender and racial biases create barriers that prevent women and URM from entering STEM

Mounting evidence suggests that gender biases favoring men and racial biases favoring whites and Asians contribute to the underrepresentation of women and underrepresented minorities (URM) in science, technology, engineering, and mathematics (STEM). Systemic issues caused by gender and racial biases create barriers that prevent women and URM from entering STEM from the structure of education to admission or promotions to higher-level positions. One of these barriers is unconscious biases that impact the quality of letters of recommendation for women and URM and their success in application processes to higher education. Though letters of recommendation provide a qualitative aspect to an application and can reveal the typical performance of the applicant, research has found that the unstructured nature of the traditional recommendation letter allows for gender and racial bias to impact the quality of letters of recommendation. Standardized letters of recommendation have been implemented in various fields and have been found to reduce the presence of bias in recommendation letters. This paper reviews the trends seen across the literature regarding equity in the use of letters of recommendation for undergraduates.
ContributorsKolath, Nina (Author) / Brownell, Sara (Thesis director) / Goodwin, Emma (Committee member) / Barrett, The Honors College (Contributor) / School of Criminology and Criminal Justice (Contributor) / School of Life Sciences (Contributor)
Created2022-05
Description
Since the 20th century, Arizona has undergone shifts in agricultural practices, driven by urban expansion and crop irrigation regulations. These changes present environmental challenges, altering atmospheric processes and influencing climate dynamics. Given the potential threats of climate change and drought on water availability for agriculture, further modifications in the agricultural

Since the 20th century, Arizona has undergone shifts in agricultural practices, driven by urban expansion and crop irrigation regulations. These changes present environmental challenges, altering atmospheric processes and influencing climate dynamics. Given the potential threats of climate change and drought on water availability for agriculture, further modifications in the agricultural landscape are expected. To understand these land use changes and their impact on carbon dynamics, our study quantified aboveground carbon storage in both cultivated and abandoned agricultural fields. To accomplish this, we employed Python and various geospatial libraries in Jupyter Notebook files, for thorough dataset assembly and visual, quantitative analysis. We focused on nine counties known for high cultivation levels, primarily located in the lower latitudes of Arizona. Our analysis investigated carbon dynamics across not only abandoned and actively cultivated croplands but also neighboring uncultivated land, for which we estimated the extent. Additionally, we compared these trends with those observed in developed land areas. The findings revealed a hierarchy in aboveground carbon storage, with currently cultivated lands having the lowest levels, followed by abandoned croplands and uncultivated wilderness. However, wilderness areas exhibited significant variation in carbon storage by county compared to cultivated and abandoned lands. Developed lands ranked highest in aboveground carbon storage, with the median value being the highest. Despite county-wide variations, abandoned croplands generally contained more carbon than currently cultivated areas, with adjacent wilderness lands containing even more than both. This trend suggests that cultivating croplands in the region reduces aboveground carbon stores, while abandonment allows for some replenishment, though only to a limited extent. Enhancing carbon stores in Arizona can be achieved through active restoration efforts on abandoned cropland. By promoting native plant regeneration and boosting aboveground carbon levels, these measures are crucial for improving carbon sequestration. We strongly advocate for implementing this step to facilitate the regrowth of native plants and enhance overall carbon storage in the region.
ContributorsGoodwin, Emily (Author) / Eikenberry, Steffen (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2024-05
Description
Glioblastoma Multiforme is a prevalent and aggressive brain tumor. It has an average 5-year survival rate of 6% and average survival time of 14 months. Using patient-specific MRI data from the Barrow Neurological Institute, this thesis investigates the impact of parameter manipulation on reaction-diffusion models for predicting and simulating glioblastoma

Glioblastoma Multiforme is a prevalent and aggressive brain tumor. It has an average 5-year survival rate of 6% and average survival time of 14 months. Using patient-specific MRI data from the Barrow Neurological Institute, this thesis investigates the impact of parameter manipulation on reaction-diffusion models for predicting and simulating glioblastoma growth. The study aims to explore key factors influencing tumor morphology and to contribute to enhancing prediction techniques for treatment.
ContributorsShayegan, Tara (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2024-05
Description

Mental health conditions can impact college students’ social and academic achievements. As such, students may disclose mental illnesses on medical school applications. Yet, no study has investigated to what extent disclosure of a mental health condition impacts medical school acceptance. We designed an audit study to address this gap. We

Mental health conditions can impact college students’ social and academic achievements. As such, students may disclose mental illnesses on medical school applications. Yet, no study has investigated to what extent disclosure of a mental health condition impacts medical school acceptance. We designed an audit study to address this gap. We surveyed 99 potential admissions committee members from at least 43 unique M.D.-granting schools in the U.S. Participants rated a fictitious portion of a medical school application on acceptability, competence, and likeability. They were randomly assigned to a condition: an application that explained a low semester GPA due to a mental health condition, an application that explained a low semester GPA due to a physical health condition, or an application that had a low semester GPA but did not describe any health condition. Using ANOVAs, multinomial regression, and open-coding, we found that committee members do not rate applications lower when a mental health condition is revealed. When asked about their concerns regarding the application, 27.0% of participants who received an application that revealed a mental health condition mentioned it as a concern; 14.7% of participants who received an application that revealed a physical health condition mentioned it as a concern. Committee members were also asked about when revealing a mental health condition would be beneficial and when it would be detrimental. This work indicates that medical school admissions committee members do not exhibit a bias towards mental health conditions and provides recommendations on how to discuss mental illness on medical school applications.

ContributorsAbraham, Anna (Author) / Brownell, Sara (Thesis director) / Cooper, Katelyn (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2022-05
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A description of numerical and analytical work pertaining to models that describe the growth and progression of glioblastoma multiforme (GBM), an aggressive form of primary brain cancer. Two reaction-diffusion models are used: the Fisher-Kolmogorov-Petrovsky-Piskunov equation and a 2-population model that divides the tumor into actively proliferating and quiescent (or necrotic)

A description of numerical and analytical work pertaining to models that describe the growth and progression of glioblastoma multiforme (GBM), an aggressive form of primary brain cancer. Two reaction-diffusion models are used: the Fisher-Kolmogorov-Petrovsky-Piskunov equation and a 2-population model that divides the tumor into actively proliferating and quiescent (or necrotic) cells. The numerical portion of this work (chapter 2) focuses on simulating GBM expansion in patients undergoing treatment for recurrence of tumor following initial surgery. The models are simulated on 3-dimensional brain geometries derived from magnetic resonance imaging (MRI) scans provided by the Barrow Neurological Institute. The study consists of 17 clinical time intervals across 10 patients that have been followed in detail, each of whom shows significant progression of tumor over a period of 1 to 3 months on sequential follow up scans. A Taguchi sampling design is implemented to estimate the variability of the predicted tumors to using 144 different choices of model parameters. In 9 cases, model parameters can be identified such that the simulated tumor contains at least 40 percent of the volume of the observed tumor. In the analytical portion of the paper (chapters 3 and 4), a positively invariant region for our 2-population model is identified. Then, a rigorous derivation of the critical patch size associated with the model is performed. The critical patch (KISS) size is the minimum habitat size needed for a population to survive in a region. Habitats larger than the critical patch size allow a population to persist, while smaller habitats lead to extinction. The critical patch size of the 2-population model is consistent with that of the Fisher-Kolmogorov-Petrovsky-Piskunov equation, one of the first reaction-diffusion models proposed for GBM. The critical patch size may indicate that GBM tumors have a minimum size depending on the location in the brain. A theoretical relationship between the size of a GBM tumor at steady-state and its maximum cell density is also derived, which has potential applications for patient-specific parameter estimation based on magnetic resonance imaging data.
ContributorsHarris, Duane C. (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J. (Thesis advisor) / Preul, Mark C. (Committee member) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2023
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Similar-identity role models, including instructors, can benefit science undergraduates by enhancing their self-efficacy and sense of belonging. However, for students to have similar-identity role models based on identities that can be hidden, instructors need to disclose their identities. For concealable stigmatized identities (CSIs) – identities that can be hidden and

Similar-identity role models, including instructors, can benefit science undergraduates by enhancing their self-efficacy and sense of belonging. However, for students to have similar-identity role models based on identities that can be hidden, instructors need to disclose their identities. For concealable stigmatized identities (CSIs) – identities that can be hidden and carry negative stereotypes – the impersonal and apolitical culture cultivated in many science disciplines likely makes instructor CSI disclosure unlikely. This dissertation comprises five studies I conducted to assess the presence of instructor role models with CSIs in undergraduate science classrooms and evaluate the impact on undergraduates of instructor CSI disclosure. I find that science instructors report CSIs at lower rates than undergraduates and typically keep these identities concealed. Additionally, I find that women instructors are more likely to disclose their CSIs to students compared to men. To assess the impact of instructor CSI disclosure on undergraduates, I report on findings from a descriptive exploratory study and a controlled field experiment in which an instructor reveals an LGBTQ+ identity. Undergraduates, especially those who also identify as LGBTQ+, benefit from instructor LGBTQ+ disclosure. Additionally, the majority of undergraduate participants agree that an instructor revealing an LGBTQ+ identity during class is appropriate. Together, the results presented in this dissertation highlight the current lack of instructor role models with CSIs and provide evidence of student benefits that may encourage instructors to reveal CSIs to undergraduates and subsequently provide much-needed role models. I hope this work can spark self-reflection among instructors to consider revealing CSIs to students and challenge the assumption that science environments should be devoid of personal identities.
ContributorsBusch, Carly Anne (Author) / Cooper, Katelyn (Thesis advisor) / Brownell, Sara (Thesis advisor) / Collins, James (Committee member) / Zheng, Yi (Committee member) / Arizona State University (Publisher)
Created2024
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The most advanced social insects, the eusocial insects, form often large societies in which there is reproductive division of labor, queens and workers, have overlapping generations, and cooperative brood care where daughter workers remain in the nest with their queen mother and care for their siblings. The eusocial insects

The most advanced social insects, the eusocial insects, form often large societies in which there is reproductive division of labor, queens and workers, have overlapping generations, and cooperative brood care where daughter workers remain in the nest with their queen mother and care for their siblings. The eusocial insects are composed of representative species of bees and wasps, and all species of ants and termites. Much is known about their organizational structure, but remains to be discovered.

The success of social insects is dependent upon cooperative behavior and adaptive strategies shaped by natural selection that respond to internal or external conditions. The objective of my research was to investigate specific mechanisms that have helped shaped the structure of division of labor observed in social insect colonies, including age polyethism and nutrition, and phenomena known to increase colony survival such as egg cannibalism. I developed various Ordinary Differential Equation (ODE) models in which I applied dynamical, bifurcation, and sensitivity analysis to carefully study and visualize biological outcomes in social organisms to answer questions regarding the conditions under which a colony can survive. First, I investigated how the population and evolutionary dynamics of egg cannibalism and division of labor can promote colony survival. I then introduced a model of social conflict behavior to study the inclusion of different response functions that explore the benefits of cannibalistic behavior and how it contributes to age polyethism, the change in behavior of workers as they age, and its biological relevance. Finally, I introduced a model to investigate the importance of pollen nutritional status in a honeybee colony, how it affects population growth and influences division of labor within the worker caste. My results first reveal that both cannibalism and division of labor are adaptive strategies that increase the size of the worker population, and therefore, the persistence of the colony. I show the importance of food collection, consumption, and processing rates to promote good colony nutrition leading to the coexistence of brood and adult workers. Lastly, I show how taking into account seasonality for pollen collection improves the prediction of long term consequences.
ContributorsRodríguez Messan, Marisabel (Author) / Kang, Yun (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Kuang, Yang (Committee member) / Page Jr., Robert E (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2018
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Education through field exploration is fundamental in geoscience. But not all students enjoy equal access to field-based learning because of time, cost, distance, ability, and safety constraints. At the same time, technological advances afford ever more immersive, rich, and student-centered virtual field experiences. Virtual field trips may be the only

Education through field exploration is fundamental in geoscience. But not all students enjoy equal access to field-based learning because of time, cost, distance, ability, and safety constraints. At the same time, technological advances afford ever more immersive, rich, and student-centered virtual field experiences. Virtual field trips may be the only practical options for most students to explore pedagogically rich but inaccessible places. A mixed-methods research project was conducted on an introductory and an advanced geology class to explore the implications of learning outcomes of in-person and virtual field-based instruction at Grand Canyon National Park. The study incorporated the Great Unconformity in the Grand Canyon, a 1.2 billion year break in the rock record; the Trail of Time, an interpretive walking timeline; and two immersive, interactive virtual field trips (iVFTs). The in-person field trip (ipFT) groups collectively explored the canyon and took an instructor-guided inquiry hike along the interpretive Trail of Time from rim level, while iVFT students individually explored the canyon and took a guided-inquiry virtual tour of Grand Canyon geology from river level. High-resolution 360° spherical images anchor the iVFTs and serve as a framework for programmed overlays that enable interactivity and allow the iVFT to provide feedback in response to student actions. Students in both modalities received pre- and post-trip Positive and Negative Affect Schedules (PANAS). The iVFT students recorded pre- to post-trip increases in positive affect (PA) scores and decreases in negative (NA) affect scores, representing an affective state conducive to learning. Pre- to post-trip mean scores on concept sketches used to assess visualization and geological knowledge increased for both classes and modalities. However, the iVFT pre- to post-trip increases were three times greater (statistically significant) than the ipFT gains. Both iVFT and ipFT students scored 92-98% on guided-inquiry worksheets completed during the trips, signifying both met learning outcomes. Virtual field trips do not trump traditional in-person field work, but they can meet and/or exceed similar learning objectives and may replace an inaccessible or impractical in-person field trip.
ContributorsRuberto, Thomas (Author) / Semken, Steve (Thesis advisor) / Anbar, Ariel (Committee member) / Brownell, Sara (Committee member) / Arizona State University (Publisher)
Created2018
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The role of climate change, as measured in terms of changes in the climatology of geophysical variables (such as temperature and rainfall), on the global distribution and burden of vector-borne diseases (VBDs) remains a subject of considerable debate. This dissertation attempts to contribute to this debate via the use of

The role of climate change, as measured in terms of changes in the climatology of geophysical variables (such as temperature and rainfall), on the global distribution and burden of vector-borne diseases (VBDs) remains a subject of considerable debate. This dissertation attempts to contribute to this debate via the use of mathematical (compartmental) modeling and statistical data analysis. In particular, the objective is to find suitable values and/or ranges of the climate variables considered (typically temperature and rainfall) for maximum vector abundance and consequently, maximum transmission intensity of the disease(s) they cause.

Motivated by the fact that understanding the dynamics of disease vector is crucial to understanding the transmission and control of the VBDs they cause, a novel weather-driven deterministic model for the population biology of the mosquito is formulated and rigorously analyzed. Numerical simulations, using relevant weather and entomological data for Anopheles mosquito (the vector for malaria), show that maximum mosquito abundance occurs when temperature and rainfall values lie in the range [20-25]C and [105-115] mm, respectively.

The Anopheles mosquito ecology model is extended to incorporate human dynamics. The resulting weather-driven malaria transmission model, which includes many of the key aspects of malaria (such as disease transmission by asymptomatically-infectious humans, and enhanced malaria immunity due to repeated exposure), was rigorously analyzed. The model which also incorporates the effect of diurnal temperature range (DTR) on malaria transmission dynamics shows that increasing DTR shifts the peak temperature value for malaria transmission from 29C (when DTR is 0C) to about 25C (when DTR is 15C).

Finally, the malaria model is adapted and used to study the transmission dynamics of chikungunya, dengue and Zika, three diseases co-circulating in the Americas caused by the same vector (Aedes aegypti). The resulting model, which is fitted using data from Mexico, is used to assess a few hypotheses (such as those associated with the possible impact the newly-released dengue vaccine will have on Zika) and the impact of variability in climate variables on the dynamics of the three diseases. Suitable temperature and rainfall ranges for the maximum transmission intensity of the three diseases are obtained.
ContributorsOkuneye, Kamaldeen O (Author) / Gumel, Abba B (Thesis advisor) / Kuang, Yang (Committee member) / Smith, Hal (Committee member) / Thieme, Horst (Committee member) / Nagy, John (Committee member) / Arizona State University (Publisher)
Created2018