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Understanding Virtual Meeting Engagement in the Professional Environment : Conceptualization, Development, Validation, and Application of Virtual Meeting Engagement
No full textThesis (Ph.D.)--Michigan State University. Information and Media - Doctor of Philosophy, 2025With the growing need for remote work and collaboration, virtual meetings\u2014synchronous interactions facilitated by technology-mediated communication\u2014have become increasingly common across various professional settings, including workplaces and classrooms. Scholars and practitioners alike recognize that effective virtual meeting practices and tools are essential for mitigating negative outcomes (e.g., Zoom fatigue) while fostering positive experiences such as meeting engagement. Understanding virtual meeting engagement is also critical from an equity perspective, particularly in examining how technology use and communication behaviors intersect with personal characteristics such as health conditions and status characteristics (e.g., gender, race, job level) to shape individual engagement. Chapter 1 introduces the significance of virtual meeting engagement and its relationships with other factors and behaviors in virtual meeting environments. Chapter 2 explores professionals\u2019 lived experiences with virtual meetings and their perceptions of engagement through qualitative interviews with individuals who regularly participate in virtual meetings for professional purposes. Building on these insights, Chapter 3 conceptualizes, develops, and validates a Virtual Meeting Engagement (VME) scale. Informed by the qualitative findings and the validated scale, Chapter 4 investigates the relationship between social interaction anxiety and virtual meeting fatigue and engagement. This chapter draws on the Hyperpersonal Model and impression management theory to examine how virtual meeting technologies may help alleviate anxiety-related barriers to engagement. Chapter 5 focuses on how individual status characteristics (e.g., gender, racial identities, job levels) influence virtual meeting fatigue and engagement, further exploring whether specific virtual meeting features (e.g., camera control, avatars, filters) can mitigate these effects by supporting impression management and reducing fatigue. Building upon the literature about virtual work, social presence, and social facilitation, Chapter 6 examines the role of social presence in shaping virtual meeting engagement, analyzing how meeting features and modalities are associated with social presence and engagement. This dissertation project integrates perspectives from media psychology, computer-mediated communication, and organizational communication, offering theoretical contributions to the understanding of engagement, fatigue, impression management, mental health, and social presence in virtual meeting contexts. Chapter 7 discusses the theoretical, methodological, and practical contributions, as well as the future research directions. Ultimately, this project advances understanding of how affordances of virtual meeting technologies, mental health conditions, and status characteristics influence virtual meeting engagement\u2014mediated by fatigue and social presence. It contributes to the broader effort to foster effective computer-mediated group communication, supporting employee well-being, enhancing collaboration, and promoting a sustainable virtual workplace culture and technologies.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
UNPACKING EPISTEMOLOGIES IN ORGANIC CHEMISTRY : A COMPARATIVE STUDY OF STUDENTS AND INSTRUCTORS IN TRANSFORMED AND TRADITIONAL COURSES
No full textThesis (Ph.D.)--Michigan State University. Chemistry - Doctor of Philosophy, 2025A central aim of science education is to support students not only in mastering disciplinary knowledge but also in developing epistemic insight\u2014an understanding of how knowledge is constructed, evaluated, and used. In chemistry education, this dual goal has proven particularly challenging, as traditional instructional approaches often emphasize factual recall, algorithmic procedures, and rule-based thinking. These pedagogical choices can inadvertently lead students to view chemistry as a disconnected body of knowledge rather than a coherent and explanatory discipline. In contrast, reformed curricula such as Chemistry, Life, the Universe, and Everything (CLUE) and Organic Chemistry, Life, the Universe, and Everything (OCLUE) aim support both conceptual coherence and epistemic development by engaging students in Three-Dimensional Learning. This dissertation explores how the epistemic climate of undergraduate organic chemistry courses shapes students\u2019 and instructors\u2019 beliefs about the structure and purpose of disciplinary knowledge. It draws on Chinn et al.\u2019s (2011) five-dimensional model of epistemic cognition, focusing on two dimensions most relevant to chemistry learning: epistemic structure of knowledge and epistemic aims and values. Specifically, I examine how different curricular models\u2014traditional textbook-based courses versus transformed curricula, OCLUE influence these dimensions of epistemic thinking. Through four qualitative and mixed-methods studies, this research investigates how students make sense of chemistry knowledge and how instructors conceptualize what it means to teach for understanding. The first study investigates students\u2019 visual representations of organic chemistry knowledge using an open-ended, in-class prompt. A total of 272 second-semester organic chemistry students from traditional and OCLUE courses were asked to illustrate what they considered important ideas and how those ideas were connected. Thematic analysis of the resulting diagrams revealed notable differences: students in the transformed curriculum more often represented chemistry knowledge as integrated around core ideas and overarching ideas, while students in the traditional curriculum tended to produce disconnected topic-based structures. These findings suggest that curriculum design plays a significant role in shaping students\u2019 epistemic views. To better understand the reasoning behind these representations, the second study presents data from semi-structured interviews with students from both instructional pathways. This study probes how students interpret what is valued in their courses and how those interpretations inform their beliefs about the nature of chemistry knowledge. Interview data revealed that students\u2019 epistemic stances were closely tied to their perceptions of course expectations, grading practices, and the types of thinking modeled by instructors. While students in transformed courses described chemistry as a system for making sense of phenomena, students in traditional courses often associated learning with memorization and exam preparation. Further, findings of this interview study showed that sociocultural factors can shape or hinder the epistemic goals of the course. The third study shifts the focus to faculty, exploring the epistemic stances of three organic chemistry instructors through semi-structured interviews. While most faculty expressed expert-like conceptions of chemistry as an interconnected and explanatory, their teaching practices were often shaped by constraints such as textbook structure, pacing demands, and institutional assessment cultures. This tension between instructors\u2019 disciplinary expertise and the realities of instructional enactment contributes to an epistemic climate that may not always support the development of coherent knowledge and perceived epistemic aims of the instructors. The final study builds on findings of the in-class prompt through a revised, more structured task administered via the beSocratic platform. This digital prompt asked students not only to create diagrams but also to explain their choices and the reasoning behind their connections. Data from 188 students were analyzed to capture both epistemic structures and epistemic aims. The study found that OCLUE students were more likely to articulate sense-making goals, such as predicting chemical behavior or explaining reactivity, whereas traditional students emphasized task performance and memorization. These results highlight the impact of curriculum design and expectations on epistemic outcomes. Collectively, these studies illuminate how instructional practices, curricular structures, classroom expectations and sociocultural factors influence both students\u2019 and instructors\u2019 views about chemistry knowledge. This dissertation contributes to the growing body of discipline-specific epistemology research by offering novel methods such as open-ended prompts and as well as evidence-based recommendations for promoting epistemic development in chemistry education. Ultimately, the findings underscore that learning science involves more than mastering content: it requires fostering students\u2019 understanding of how scientific knowledge is structured, justified, and used to make sense of the world.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
EXPLORING PHOTOINDUCED EXCITED-STATE DYNAMICS IN SPIN-CROSSOVER FE(II) COMPLEXES FOR CHROMOPHORE DESIGN
No full textThesis (Ph.D.)--Michigan State University. Chemistry - Doctor of Philosophy, 2025There has been a surge of interest in developing earth-abundant Fe(II)-based chromophores as alternatives to Ru(II)-based systems. However, studies have shown that in low-spin (LS) Fe(II) polypyridyl complexes, upon photoexcitation, ultrafast deactivation occurs from the metal-to-ligand charge transfer (MLCT) excited state to the relatively long-lived high-spin (HS) 5T2 excited state within 150 fs. Given the long-lived nature of the 5T2 state, a fundamental understanding of its photophysical properties is essential for evaluating the potential to harness the energy stored in this state. Semi-classical Marcus theory provides a framework for describing the relaxation kinetics of the 5T2 excited state, where the rate of transition is governed by the reorganization energy (\u3bb), driving force (\u394G0), and electronic coupling matrix (Hab). However, a complete description of the deactivation kinetics of the 5T2 state is limited by the lack of information on the \u394G0 between the 5T2 and 1A1. In this study, a series of spin crossover (SCO) tris-bidentate Fe(II) complexes are employed to investigate the excited-state kinetics associated with the 5T2 state, serving as a platform to gain insight into the \u394G0. With these SCO Fe(II) complexes, semi-classical Marcus theory enables a complete kinetic description of the spin-state transition, offering insight into how synthetic modifications influence relaxation dynamics. These findings support a rational design strategy for tuning photophysical kinetics in iron-based photosensitizers through targeted molecular design.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
VARIABLE SELECTION AND ESTIMATION IN PARTIAL LINEAR MODEL : A VARIATIONAL BAYES APPROACH
No full textThesis (Ph.D.)--Michigan State University. Statistics - Doctor of Philosophy, 2025Partial Linear Models and their generalized extensions represent an important class of semiparametric models that combine the strengths of linear regression with the flexibility of nonparametric function estimation. These models are especially appealing because they include both a linear component, which captures straightforward additive effects of covariates, and a nonparametric component, which allows for complex, unknown relationships without imposing rigid parametric assumptions. This balance of interpretability and adaptability has made Partial Linear Models and Generalized Partial Linear Models widely used in many applied fields.Traditionally, estimation of the nonparametric component in these models has relied on spline-based techniques or kernel smoothing methods. While effective in certain contexts, these approaches can be limited in their capacity to capture highly nonlinear or high-dimensional structures. In this work, we propose a more flexible alternative by employing neural networks to approximate the nonparametric function. Neural networks offer rich representational power and can adaptively learn intricate patterns in the data, making them especially well suited to modeling complex dependencies that are difficult to pre-specify with classical smoothers.To address variable selection in both the linear and nonlinear parts of the model, we incorporate a spike-and-slab prior distribution. This prior combines a point mass at zero (the \u201cspike\u201d) with a continuous distribution (the \u201cslab\u201d), enabling the model to automatically identify and shrink irrelevant predictors while retaining important signals. This approach improves interpretability and helps guard against overfitting, particularly in settings where the number of potential covariates is large.Inference in this model is challenging due to the high dimensionality and the presence of neural network parameters. To achieve computational scalability, we develop a variational inference strategy that approximates the true posterior distribution of model parameters by a more tractable family of distributions. Variational inference provides an efficient optimization-based framework for Bayesian estimation, enabling the method to handle large datasets and complex model structures that are beyond the reach of traditional sampling-based approaches.This combination of neural network estimation, spike-and-slab priors for variable selection, and variational inference creates a powerful toolkit for semiparametric modeling in high-dimensional settings. By moving beyond conventional smoothing techniques, our approach opens new possibilities for flexible, interpretable, and scalable estimation in Partial Linear Models and Generalized Partial Linear Models. We believe these contributions will support further research into modern semiparametric methods and broaden their applicability to contemporary scientific problems where both structure and flexibility are essential.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
DESIGNING AI-FACILITATED FEEDBACK USING FEEDBACK TRIANGLE THEORY : EXAMINING INSTRUCTOR IMPLEMENTATION
No full textThesis (Ph.D.)--Michigan State University. Educational Psychology and Educational Technology - Doctor of Philosophy, 2025AI-facilitated feedback has emerged as a promising tool to enhance instructor\u2019s feedback practice. However, its application within the framework of established feedback theories has been underexplored. This dissertation addresses this gap by applying the Feedback Triangle Theory to investigate how AI can support feedback practices that are cognitively enriching, socially engaging, and structurally manageable for instructors. The dissertation includes two interrelated studies. Study 1, a case study of three instructors with diverse backgrounds, used Zoom-based think-aloud sessions and interviews to examine how instructors co-constructed feedback with ChatGPT. Instructors acted as critical mediators, revising AI drafts to reflect their pedagogical values and student needs. Effective AI feedback was specific, connected to student work, socially responsive when appropriate, and adaptable through edits and prompting. Study 2 expanded the scope to seven instructors who provided AI-facilitated feedback to students. Interviews explored their perceptions and how factors like teaching motivation, modality, and experience shaped implementation. While most found the tool useful and efficient, engagement levels varied based on teaching experience, alignment with instructional identity, and concerns about relational and ethical aspects of feedback. Two key contributions emerge from this research. First, the design of AI-facilitated feedback was guided by a holistic, theory-driven framework, moving beyond content accuracy to consider emotional tone and workflow flexibility. Second, the study highlights how instructor-level factors influence the integration of AI into feedback practices, with important implications for tool design and professional development. Together, these findings offer timely insights for educational technology design, feedback theory, and the ethical use of AI in teaching.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
PRODUCTION AND APPLICATION OF LEAD AND BISMUTH RADIONUCLIDES IN PREPARATION FOR ISOTOPE HARVESTING AT THE FACILITY FOR RARE ISOTOPE BEAMS
No full textThesis (Ph.D.)--Michigan State University. Chemistry - Doctor of Philosophy, 2025Isotope Harvesting at the Facility for Rare Isotope Beams (FRIB) will provide rare beams for use in multiple nuclear physics applications with unused beams being deposited into a flowing-water beam dump. The irradiated water becomes filled with hundreds of different isotopes that can be collected on resins and then purified and used for various applications. Among the many isotopes that will be produced, Pb and Bi have useful applications in nuclear science. The isotopes of Pb and Bi have many uses in nuclear medicine such as in targeted alpha therapy with 212Pb/212Bi, 213Bi, 214Pb/214Bi and single photon emission computed tomography with 203Pb. Many other isotopes of Pb and Bi can be harvested to develop generators (203Bi/203Pb, 204Bi/204mPb, and 210Pb/210Po), radiotracers (205,206,207Bi), and chronometers (202,205Pb) to meet the needs of the nuclear science community. 204mPb has useful applications in perturbed angular correlation (PAC) spectroscopy, a nuclear technique to observe hyperfine interactions. This offers an opportunity to expand upon the existing Pb-based radiopharmaceutical knowledge to potential better understanding of reaction kinetics and protein interactions at a cellular level.This work focused on the development of the necessary chemistry to harvest Pb and Bi from a water source and develop applications in radiolabeling and PAC. Initial tests for harvesting used ion exchange resins with an elemental cocktail comprised of nine elements: uranium, thorium, lanthanum (actinium), barium (radium), tellurium (polonium), bismuth, lead, thallium, and gold. These represented elements that would be generated with a 238U beam. When the elements had absorbed onto the resins from the water, batch studies were performed to determine distribution coefficients, and to create a separation scheme for isolating Pb and Bi. To begin radiolabeling and PAC experiments, six irradiations using 24 MeV protons on natural Pb targets were performed at the University of Alabama at Birmingham yielding a set of neutron deficient Bi isotopes, 203,204,205,206,207Bi. Using the distribution coefficient data, a dual generator of 203,204Bi/203,204mPb was created. The generator had >99% retention of Bi onto an AG 1-x8 column. The generated 204mPb was eluted in 0.1 M HCl and used in PAC experiments. The data acquired from the experiments were preliminary and focused on the perturbations arising from Pb interactions with pharmaceutically relevant compounds. The results demonstrated in this work provide methodologies for harvesting and separating Pb and Bi for applications in nuclear medicine, PAC spectroscopy, and as radiotracers. The work can be translated to FRIB on a larger scale when the water beam dump is implemented and the Isotope Harvesting Program is fully operational.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
IMPROVING THE ADHESION OF POLY(ETHYLENE TEREPHTHALATE) AND POLY(ETHYLENE-CO-VINYL ALCOHOL) MULTILAYER FILMS USING POLY(ETHYLENE-CO-VINYL ACETATE) TIE LAYER
No full textThesis (M.S.)--Michigan State University. Packaging - Master of Science, 2025This study focuses on developing recyclable multilayer films (MLFs) to address the environmental challenges posed by traditional multi-material packaging. While multilayer structures are critical for protecting moisture and oxygen-sensitive products, their diverse material compositions make them one of the most difficult plastics to recycle. This research investigates the use of Poly(ethylene-vinyl acetate) (PEVA) tie layer in PET/EVOH multilayer films, where polyethylene terephthalate (PET) serves as the structural layer and ethylene vinyl alcohol (EVOH) functions as the barrier layer. Incorporating the PEVA tie layer increased seal strength by ~58%, indicating improved interfacial adhesion. The incorporation of the PEVA tie layer not only improved interfacial adhesion but also maintained favorable barrier properties, supporting the development of high-performance, recyclable multilayer films. Initial mechanical recycling results revealed that the presence of the tie layer had no negative effect on recyclability. Overall, this study supports the hypothesis that tie layers play an important role in the development of high-performance, recyclable PET/EVOH multilayer films, thereby contributing to more sustainable multilayer packaging solutions.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
DOING ACTIVISM WHILE BEING A YOUNG WOMAN OF COLOR IN BRAZILIAN FAVELAS : NEGOTIATING LAYERS OF INTERSECTIONALITY AND HEGEMONIC STRUCTURES OF POWER IN SOCIAL MEDIA PLATFORMS\u2019 STORYTELLING PROCESS
No full textThesis (Ph.D.)--Michigan State University. Information and Media - Doctor of Philosophy, 2025This study examines how young women of color from Brazilian peripheries, or favelas, utilize social media platforms to engage in activism. Drawing on Gramsci's understanding of hegemonic power, this research examines four power structures\u2014colonialism, race, gender, and media\u2014to understand how these layers of intersectionality influence and are influenced by both the participants and the collective actions in which they are involved. Based on a set of qualitative methods, the research is composed of three studies: the first involves in-person ethnographic fieldwork and in-depth interviews; the second consists of online ethnography, focusing on the analysis of social media profiles and usage by the participants and their groups; and the third includes interviews with young women engaged in two types of collective action - grassroots movements and top-down organizations. The findings reveal that social media platforms are a central part of the lives of these young women of color, as well as the groups they participate in, becoming the primary space for existence and activism. As a result, the boundaries between online and offline environments are increasingly blurred. The study also shows that these platforms play a crucial educational role, particularly concerning race and gender, where networks of support and care emerge despite the barriers present in these spaces. Finally, a significant distinction is identified in the approaches adopted by the groups: while grassroots movements operate with a collective and community-based focus, top-down organizations tend to prioritize individual growth, professional development, and the self-esteem of the girls.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
BECOMING A TEACHER OTHERWISE : THE LIVED TRAJECTORY AND PEDAGOGICAL IMAGINATION OF A TRANSMIGRANT, REFUGEE-BACKGROUND EMERGING EDUCATOR
No full textThesis (Ph.D.)--Michigan State University. Curriculum, Instruction, and Teacher Education - Doctor of Philosophy, 2025This dissertation examines the pedagogical becoming of Maya, a Pa\u2019O refugee-background transmigrant woman and preservice Teacher of Color in the United States, whose life unfolds across experiences of forced displacement, intergenerational struggle, and racialized colonial entanglements. Through a single case study grounded in narrative inquiry and a life history approach, this research traces how Maya\u2019s transnational experiences shape her educational visions, not as responses to institutional norms, but as generative, relational alternatives to dominant modes of teaching and learning.Guided by decolonial theory and AsianCrit, the study critiques how teacher education often contains refugee educators within frameworks of liberal multiculturalism, humanitarianism, and epistemic exclusion. Rather than seeking inclusion, Maya offers a pedagogy rooted in Metta, a Buddhist ethic of care, and informed by her lived negotiation of loss, language, and relational responsibility. Her pedagogy of critical caring emerges not from formal training, but from embodied knowledge, recursive storytelling, and ethical commitments forged in the wake of displacement.Foregrounding Maya\u2019s narrative as a site of theory-making, the dissertation argues that refugee-background educators are not supplementary voices but epistemic agents whose lived histories reconfigure what counts as teacher knowledge. Maya\u2019s story insists that teaching need not be a profession to be mastered but can instead be understood as a practice of becoming, anchored in relationality, intergenerational memory, and decolonial possibility. This study calls for rethinking teacher education beyond liberal multicultural and humanitarian frameworks, advancing approaches that recognize refugeehood as an epistemic stance and pedagogy as a relational, justice-oriented, and decolonial practice.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references
SUPPORTING STUDENTS IN CONSTRUCTING MECHANISTIC EXPLANATIONS FOR A COMPLEX PHENOMENON THROUGH CAREFULLY DESIGNED FORMATIVE ASSESSMENTS
No full textThesis (Ph.D.)--Michigan State University. Chemistry - Doctor of Philosophy, 2025Constructing explanations supports students in developing a deep understandingof curriculum materials and in preparing them for informed decision-making beyond the classroom. Many phenomena that learners encounter, both in their courses and in their future careers and everyday life, are inherently complex, requiring them to weave together multiple ideas. The work in this dissertation investigates how we can support students in constructing causal-mechanistic (both \u2018how\u2019 and \u2018why\u2019) explanations for organic chemistry phenomena via scaffolded formative assessments. The phenomenon we focused on is how solute-solvent interactions (solvation) affect the rate of a nucleophilic substitution reaction \u2013 a foundational idea often overlooked. Explaining this phenomenon requires students to draw on and connect several ideas that may not be obviously involved in the phenomenon \u2013 such as attractive and repulsive forces, energy, stability, reactivity, and probability. Guided by a resources perspective on learning and a modified Evidence-Centered Design approach, I iteratively designed, administered, and refined a multipart solvation activity that leads students, step by step, to connect the entire chain of conceptual resources and causal links needed to explain this phenomenon. The activity was implemented over three design-based research cycles in a large-enrollment, transformed organic-chemistry sequence. The original activity (Iteration 1) consisted of scaffolded tasks to explicitly address every causal link in the chain. Despite scaffolding, only 55 % of students chose the correct solvent from the two options given. Analysis of student reasoning revealed that only 27 % constructed a fully CM explanation and the activitymight have been too long and overwhelming. We identified a persistent stumbling block, the force \u2013 energy link, as many students incorrectly associated stronger interactions (forces) with higher potential energy. These findings and insights informed Iteration 2, a streamlined 15-slide version that reduced cognitive load and added targeted prompts to support students with the force\u2013energy relationship. In Iteration 2 and its minor-reworded successor, Iteration 3, approximately 75 % of students selected the correct solvent and nearly one half produced fully CM explanations. Across all data sets, every student who had engaged in CMR always made the correct prediction, whereas those with partial or non-normative reasoning did so far less often underscoring the predictive and explanatory power of causal-mechanistic thinking. The findings highlight both the challenge and the importance of incorporating causal mechanistic reasoning into undergraduate science courses. This work shows that iteratively refined, low-stakes assessments can both elicit and support sophisticated mechanistic reasoning without overwhelming learners. This work offers a scaffold template that can be used and adapted for other complex phenomena, an empirically grounded coding scheme for characterizing reasoning, and evidence that carefully designed formative assessments that engage students in CMR can foster deep understanding. By demonstrating that students can be guided to weave multiple conceptual resources into coherent explanations, and that doing so markedly improves the accuracy of their predictions, this work advances our understanding of how to support learners in developing deep explanations, with wide-reaching implications for teaching and discipline-based education research.Description based on online resource. Title from PDF t.p. (Michigan State University Fedora Repository, viewed ).Includes bibliographical references