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Trucking industry thrives on just-in time management, efficient routing and less travel delays. While traffic congestion continues to be a significant ‘highway’ problem, delays in truck travel cause loss of revenue to the trucking companies. Truck travel time performance measures assist in understanding the level of “truck-exclusive” congestion to plan for better routing. The truck travel times and routing strategies depend on the on-network (road) characteristics and off-network (land use and demographics) characteristics within the vicinity of roads. The literature documents limited to no research dedicated to truck travel time performance measures or their association with on-network and off-network characteristics.
The main goal of this dissertation is to research truck travel patterns, recommend performance measures, identify chokepoints, and understand the influence of on-/off-network characteristics on truck congestion. The first part of the research focuses on examining truck travel time data to choose performance measures, and understand their relationship with on-network and off-network characteristics. These performance measures are visualized geospatially to locate the chokepoints. The second part of the research focuses on the truck travel time estimation models using the on-network and off-network characteristics as the independent variables. The methodology and findings assist in locating chokepoints and prioritizing areas for truck travel improvement. The models help to estimate truck travel times and proactively plan land use or transportation network improvements.
The prediction of RNA secondary structure is complex. The biomolecule can adopt or sample numerous stable conformations, can change structure in response to a stimulus such as a binding event, and does not simply obey thermodynamically favorable folding rules. Due to this, estimation of structure based on the primary sequence is unreliable and misleading. Probing RNA structure dramatically improves computational prediction. The examination of both, ex vivo and in cell RNA can provide important information regarding structural stability, the RNA interactome, and refolding effects.
Current structural probes for RNA selective 2′-hydroxy acylation analyzed by primer extension (SHAPE) rely on a reaction with the 2′-OH on the ribose sugar of residues that are not base paired. These flexible residues can then be determined using gel electrophoresis or quantified using next generation sequencing (NGS) and mutational profiling (MaP) to prepare a library of probing data. The advent of SHAPE technologies led to a rapid increase in the accessibility of RNA structural data. Several successful SHAPE probes have been previously demonstrated, but arguments regarding reactivity and cell permeability remain. In this work, the design and application of novel, variably reactive SHAPE probes is shown ex vivo and a novel in cell probe is demonstrated.
Students with extensive support needs (ESN) are a heterogenous group of students with the most pervasive and ongoing support needs who typically receive special education services under the categories of autism spectrum disorder (ASD), intellectual disability, or multiple disabilities and often qualify to take their state’s alternative assessment (Taub et al., 2017). Students with ASD who have ESN may have elevated support needs for social behavior (Jang et al., 2011; Matson et al., 2011; Shogren et al., 2017). Although there are several evidence-based practices to support the behavioral needs of students with ASD who have ESN (Steinbrenner et al., 2020), educators often have difficulty implementing these practices with fidelity (Brock et al., 2014; Morrier et al., 2011; Robertson et al., 2020). School-wide Positive Behavioral Interventions and Supports (SWPBIS) is an evidence-based framework to support the social and behavioral needs of all students with evidence-based practices, data-based decision making, and systems to support teacher implementation fidelity (Horner & Sugai, 2015; Sugai & Horner, 2006, 2009). However, students with ASD who have ESN are not consistently included in SWPBIS (Kurth & Enyart, 2016; Kurth & Zagona, 2018; Walker et al., 2018). Check-in/Check-out (CICO) is an evidence-based intervention commonly used as a Tier 2 behavioral support within a SWPBIS framework (Conley et al., 2018; Maggin et al., 2015). CICO is effective for K-12 students without disabilities and students with high incidence disabilities (Maggin et al., 2015). The purpose of this study was to examine the effects of traditional or adapted CICO on the adherence to schoolwide expectations and challenging behavior of students with ASD who have ESN. Results of this single-case, multiple baseline across participants study indicated there was a decrease in challenging behavior for two of the four participants when adaptations were made to the standard CICO protocol. Additionally, educators, students, and parents found CICO feasible and socially valid. Limitations, implications for practice, and suggestions for future research are discussed.
In this thesis, a combined approach based on the Finite Element (FE) and Smoothed Particle Hydrodynamics (SPH) methods is proposed to model turning operations. The approach exploits the advantages of each method and leads to high-fidelity coupled FE-SPH machining models that are significantly more numerically efficient and are on par with the models based on each of the two methods alone. Both two-dimensional and three-dimensional models are developed and validated by comparing predicted forces and chip morphologies with experimental results. Parametric studies are carried out to fine-tune the model-based parameters in order to avoid numerical stability issues. The three-dimensional models are extended to include modulated tool path (MTP) machining which is a technique for breaking chips during machining by modulating the motion of the tool. The MTP model predictions are shown to agree with the results from an existing analytical model. With this model, various tool paths can be simulated to choose an optimal path that decreases tool-wear without sacrificing productivity. Preliminary results from a three-dimensional turning model incorporating machining dynamics through a spring-damper system are also presented. This model has the potential to be used for studying machining stability for a given set of machining conditions.
In addition to the above, another significant contribution of this thesis is the determination of Johnson-Cook material model parameters for a given material using an inverse method and experimental values of cutting forces and workpiece temperatures. The methodology described in the present work identifies the non-uniqueness of the solution to the inverse problem and proposes an approach that eliminates the non-uniqueness.
Athletes are aware that with involvement in sport they are exposed to the risk of getting injured. Suffering an injury can be one of the most stressful experiences in a student-athlete’s athletic career and can cause a series of psychological, emotional, and social responses, as well as impact one’s sense of identity. The very sparse literature in the counseling field regarding student-athletes and lack of research in general, exploring women student-athletes and women track and field student-athletes in particular, contributes to the need for this study. The purpose of this study was to explore lived experiences of former women track and field college student-athletes who trained and competed through pain and injury. This study utilized a phenomenological approach and implemented semi-structured interviews. Over the course of a six-week period, a total of 10 participants completed a demographic questionnaire and were interviewed via Zoom to facilitate in-depth descriptions of their experiences. Moustakas (1994) methods consistent with qualitative phenomenological research design were used to facilitate the data analysis. A total of five major themes emerged from the data, including: identity, perception of pain and injury, student-athlete - coach relationship, support system, and psychological impact. This research found that the themes are interconnected and impact each other. The findings indicate that women track and field student-athletes who chose to train and compete through pain and injuries face identity challenges, which are further facilitated by student-athlete – coach relationship, one’s support system, and acceptance of the “push through the pain” mindset. This mindset was found to be further facilitated by the underlying belief that student-athlete role is a job for which participants have been compensated. Participants were also found to minimize and justify their pain as a coping mechanism to help them in continuing to train and compete despite being in pain and injured. The relationship between participants and their coaches was found to contribute to negative psychological experiences. All themes were closely connected with cognitive and emotional functioning of the participants. Implications for counselors and counselor educators as well as future research recommendations are discussed. However, the emphasis for counselors is to approach working with student-athletes from a holistic standpoint, disclose personal experiences with athletics early on in the therapeutic relationship, and provide substantial psychoeducation regarding intercorrelation between mental health and athletic performance.
The main goal of learning analytics and early detection systems is to extract knowledge from student data to understand students' trends of activities towards success and risk and, therefore, design intervention methods to improve learning performance and experience. However, many factors contribute to the challenge of designing and building effective learning analytics systems. Because of the complexity of heterogeneous student data, models designed to analyze it frequently neglect temporal correlations in the interest of convenience. Moreover, the performance descriptions gained from the student data model or prediction results from the analytical models do not always help explain the "why" and "how" behind it. Furthermore, domain specialists are unable to participate in the knowledge discovery process since it necessitates significant data science abilities, and an analytical model is a black box to them.
This research aims to develop analytical models that enable domain experts to study their students' performance behavior and explore trustworthy sources of information with the help of explanations on the analytics. Our work demonstrates various approaches to using the temporal aspect of heterogeneous student data to build analytical models: weighted network analysis, unsupervised cluster analysis, and recurrent neural network analytics. The description, implementation process, and findings of each method are presented as technical contributions to the temporal analysis of student data. We experiment with all these analytical models that highlight the complexity of heterogeneous-temporal data, model building, decision-making tasks, and the need for a more in-depth focus on visual information of analytics with state-of-art explainable AI tools and techniques.
Our work underscores a need for developing a robust way to integrate the possibilities inherent within each approach. To achieve this goal, we present a comprehensive yet flexible and empirical framework to support the design and development of analytical models to extract meaningful insights about students' academic performance and identify early actionable interventions to improve the learning experience. We illustrate our framework on three applications (e.g., student network model, unsupervised clustering model, and recurrent neural network analytics) to demonstrate the value of this framework in addressing the challenges of using student data for learning analytics. These applications present vast opportunities to benefit students' learning experience by implementing flexible educational data representations, fitting different predictive models, and extracting insights for designing prescriptive analytics and building strategies to overcome perceived limitations.
An academic institution's culture drives its ability to accept, leverage, and deploy predictive and prescriptive analytics to enhance the workflow of maximizing pedagogical outcomes. We believe that our work will aid in the future development or refinement of a set of design standards for learning analytics systems.
Youth with disabilities continue to show poor in-school and post-school outcomes. Parent engagement remains as one key component to bring about positive outcomes in youth with disabilities. Despite schools’ widely adapted strategies on parent engagement, parent perception on various parent engagement strategies is largely unknown. The purposes of this dissertation were (a) to identify parents’ experiences and perceptions on the school-based parent engagement practices in secondary transition, and (b) to understand the facilitators and barriers of parent engagement strategies for engaging parents of youth with disabilities. Using a nonprobability snowball sampling, this cross-sectional mixed-method survey study included 642 parents of youth (ages 14-21) with disabilities across the United States. Each parent reported their experience and perceived helpfulness toward each school-based parent engagement strategy, on a 5-point Likert scale, ranging from 1 (rarely experienced/not at all helpful) to 5 (always/extremely helpful). On average, participants reported they “sometimes” experienced each of the 23 strategies with the lowest rated strategies being (a) discussion of cultural values and beliefs and (b) connecting with service providers or agencies. Across the race/ethnicity groups, results revealed racial differences in the perceptions of parents of youth with disabilities in secondary transition on the 23 school-based parent engagement strategies across five domains: knowledge and skills, communication, collaboration, relationship, and culturally responsive practice. Compared to parents of non-Hispanic White, parents of colors reported lower scores across all five school-based parent engagement domains for both experiences and perceived usefulness. To identify further thoughts regarding parents’ perceptions toward parent engagement, deductive, inductive, and thematic analysis of three open-ended questions uncovered four major themes pertaining to facilitators and barriers of parent engagement. The four themes included home-based factors, school-based factors, system-based factors, and existing situations (i.e., children’s disabilities/characteristics, family’s work, lack of transportation, time conflict, COVID-19, and weather). Implications for practice, limitations, and suggestions for future research are discussed.
English learners (ELs) make up a significant portion of the nation’s K-12 student population who come from culturally and linguistically diverse backgrounds. ELs bring a wealth of diversity to the United States’ education system; however, teachers’ limited knowledge and practices of how to integrate ELs’ cultural, linguistic, and prior educational experiences in the general education curriculum can contribute to low academic growth and overidentification into special education programs, particularly for learning disabilities in reading. This study examined the impact of online professional development on general and special education teachers’ knowledge of data-based individualization (DBI) and curriculum-based measurement (CBM) to adapt validated reading interventions with culturally and linguistically responsive practices (CLRPs) for ELs with persistent reading difficulties. Results indicated very large effect sizes of online DBI/CBM + CLRP professional development on teacher knowledge; however, a functional relation could not be determined due to the study ending before all teachers finished the professional development components. The findings of this study provide several implications for online DBI professional development and adapting validated reading interventions for ELs. Suggestions for future research are also offered.
Charlotte Bilingual Preschool’s Family Program aims to equip parents to support their children’s education at home and at school by increasing parents’ educational engagement, promoting parenting best practices, developing families’ social capital, and supporting families’ mental health and well-being. This study aimed to evaluate 1) how the Family Program promotes growth in these areas for the families at the preschool, 2) the interconnections among parents’ attitudes, behaviors, and supports, and 3) how parents’ attitudes, behaviors, and supports relate to their children’s functioning in preschool.
The analysis of survey data collected at the beginning and end of the 2019-20 school year uncovered little evidence that attendance at Family Program events (i.e., Family Cafes and Workshops) led to improvements in family or child outcomes, other than increased parent friendships and more connections in the preschool family network. The disruption of programming caused by the COVID-19 pandemic and the shift to remote instruction in March 2020, likely relate to the lack of findings in this area. Nonetheless, correlational and regression analyses did identify relationships among mothers’ attitudes, perceptions of social support and social capital, and educational involvement behaviors. For instance, findings suggest that common good social capital (i.e., a positive, collaborative community atmosphere) may promote positive interactions with teachers and other parents, which could in turn, promote more positive educational involvement behaviors, including home-based involvement, ethnic identity parenting, and more positive behavior management practices. Additionally, analyses indicated that the positive relationship between maternal stress and negative behavior management practices was attenuated when mothers perceive strong social support and social capital. While these positive outcomes did not relate to parents’ attendance at Family Cafes and Workshops, they were associated with parents’ self-reported school involvement, suggesting that parents’ broader interactions with the Family Program (i.e., beyond attendance at Family Cafes and Workshops) may yield positive outcomes.
This study’s findings support the approach of Charlotte Bilingual Preschool’s Family Program, by connecting caregivers’ attitudes, sense of support, and social capital (which are intermediate goals of the Family Program) to their educational involvement behaviors (the Family Program’s primary goal). Theoretically, promoting positive family involvement should yield more positive developmental outcomes for children in the short- and long-term as well. This study provided some support for this hypothesis, by connecting parents’ bonding and bridging social capital and their efforts to promote children’s appreciation of their ethnic and cultural identities to children’s social-emotional functioning and language skills. Furthermore, results suggested that when parents reported greater increases or improvements in several family-level variables, their children tended to show larger improvements in social-emotional protective factors and behavior. These findings indicate that the Family Program can have an important impact on children and families, especially by connecting socially isolated families with greater social support and social capital.
The COVID-19 pandemic and the preschool’s shift to remote programming in March 2020 was a major limitation that disrupted programming and reduced this study’s capacity to draw strong conclusions. However, the pandemic also provided an opportunity to examine the links between various forms of remote engagement and outcomes for children and families. Despite the pandemic, this study’s findings have important implications for Charlotte Bilingual Preschool, as well as other stakeholders seeking to enhance two-generation approaches to early childhood education; especially those supporting Latino immigrant families and English language learners. Limitations, implications, and future directions are discussed.
