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An OCR Application for Location-Based Indoor Entity Recognition
Full text linkThe integration of optical character recognition (OCR) technology with indoor positioning systems marks a significant advancement in innovation, poised to revolutionize various aspects of daily life by enhancing safety, navigation, and efficiency within indoor environments. This research project stems from a critical use case focusing on precise localization in emergency scenarios within indoor environments. The research aims to generalize this capability across buildings, facilitating user navigation and entity localization through application-based directions. Central to this paper is the extraction of entity information from image frames using OCR technology, presenting challenges in efficient image data processing in terms of both accuracy and computation during inference especially over extended periods of time. The primary objective of this research project is to explore deep learning methodologies and deduce a method for simplistic OCR which minimizes computational overhead without compromising accuracy. A set of standardized entities relevant to building environments is defined to ensure selective identification and prioritization based on relevance and importance. The study later pivoted to a comparative analysis of existing models as a consequence of model training setbacks
The effect of minimum wage increases on wage disparities across different education attainment levels in Minnesota
Full text linkThis study examines the impact of minimum wage increases on wage disparities, with a particular focus on whether or not the increases in minimum wage reduce the wage gap found between the education levels attained by adults. Using wage data from 2013 and 2019, the analysis evaluates how wage growth varied between workers with less than a high school diploma and those with a high school diploma but no college degree using a difference-in-difference empirical estimation approach. The findings suggest that minimum wage hikes significantly benefit low-wage earners, particularly individuals with lower educational attainment, contributing to a reduction in wage disparities. While minimum wage policies serve as a tool for reducing income inequality, the study underscores the need for complementary measures such as gender pay equity initiatives, workforce development programs, and policies that promote lifelong learning. These findings contribute to the broader discourse on labor market policies and provide insights for future research and policymaking aimed at fostering economic mobility and wage equity
Early Childhood Teachers\u27 Experiences and Perceptions of the Reflective Supervision and Consultation Model
Full text linkThis research examines the experiences that early childhood education and early childhood special education teachers have with reflective supervision and consultation. Specifically, this research explored the experiences of teachers engaged in reflective supervision and consultation and their perception of its impact on their teaching practice, ability to manage stress and cope with the emotional demands of the job. This study also looked at whether or not teachers feel equipped to remain in the field of early childhood education and what they perceive is working well and what concerns they have regarding their reflective supervision and consultation practice. has on the teacher’s experiences of secondary trauma, compassion fatigue, and burnout. Participants were interviewed, in a semi-structured manner, to elicit deep reflection and conversations about their experiences and how those experiences have impacted their daily experiences in education. Results indicated that participants overwhelmingly feel that engaging in reflective supervision and consultation helps them feel equipped to manage the emotional stress of the job and contributes to them feeling equipped enough to remain in the field of early childhood education. Participants also unanimously agreed that reflective supervision and consultation is helping them improve their teaching practice in a myriad of ways
User Perceptions of Trust, Credibility, Security, and Privacy in ChatGPT Interactions: A Mixed-Methods Analysis of Task-Dependent Attitudes
Full text linkChatbots have rapidly transformed domains such as customer service, education, and digital assistance. However, trust and credibility in generative AI systems like ChatGPT remain underexplored, particularly in relation to task context. Existing studies often focus on traditional rule-based chatbots or specific domains, overlooking how user perceptions may vary depending on the nature of interaction. This study addresses that gap by examining task-dependent perceptions of trust, credibility, privacy, and security in interactions with ChatGPT. A mixed-methods approach was employed, combining a two-week diary study with follow-up interviews. Thirty participants (aged 20–26, primarily students in computer-related majors) engaged with ChatGPT in two task contexts: structured (event planning) and preference-based (e.g., recommending books or restaurants). Quantitative ratings and qualitative reflections were analyzed using independent t-tests and grounded theory, respectively. Findings revealed that while trust and security remained stable across tasks, credibility perceptions differed significantly, with higher ratings in preference-based tasks. Participants expressed strong trust when ChatGPT’s suggestions aligned with prior knowledge but questioned credibility in tasks requiring real-time data or source verification. Privacy concerns were minimal, though some users hesitated to share personal details due to unclear data handling practices. Theoretically, the study draws on trust and credibility frameworks from human-computer interaction research, focusing on how task type and the transparency of information influence users’ evaluations of ChatGPT. Design implications include the need for real-time data integration, visible source citations, and personalized privacy settings to improve user confidence. Limitations include the homogeneity of the sample and lack of real-world testing environments. Future research should explore similar dynamics in high-stakes domains like healthcare, finance, or legal services, and examine user behavior over longer-term AI interactions. This study contributes to a nuanced understanding of human-AI trust formation, offering actionable insights for developers and researchers building transparent, context-aware chatbot systems
Implementing High-Quality Texts: Award-Winning Books in K-8 Classrooms
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Effects of Book Banning on School Libraries
Full text linkLibrary media specialists are crucial in curating diverse and inclusive collections for school libraries. The increasing number of book bans and challenges present significant obstacles to their material selection, retention, and display. This study examines the impact of book bans on school librarians\u27 collection development decisions, particularly in Minnesota, and explores how censorship efforts influence their purchasing, retention, and display of books. Through an analysis of existing literature and survey data, this research seeks to answer key questions regarding the effects of book challenges on library media specialists\u27 practices
Chauntecleer and Oikos: An Ecological Reading of Nun’s Priest’s Tale/Wilderness Assemblage, Ecofeminism, and In the Lake of the Woods
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The Impact of Post-Partum Depression on Mothers and their Babies
Full text linkPostpartum depression (PPD) is a severe, long-lasting form of depression following childbirth that affects a substantial number of new mothers (Mayo Foundation for Medical Education and Research, 2022). Research shows that, in fact, one in seven women suffer from PPD, with an unknown number of women going undiagnosed (Bianciardi et al., 2020). This mental illness is filled with feelings of intense sadness, hopelessness, and fatigue. PPD can disrupt a mother’s ability to bond with her new bundle of joy, manage self-care, and participate in routine daily activities (O\u27Hara & McCabe, 2013). This illness not only has a significant emotional and psychological weight on the mother, but it can also have wide-ranging consequences for the baby’s development and general welfare. Infants of mothers with postpartum depression are at a higher risk for issues such as impaired cognitive and emotional development, attachment difficulties, and behavioral problems (Bennett et al., 2004). Given the vital early years of life for a child’s developmental milestones, understanding the full scope of the dual impact of postpartum depression is essential. Therefore, this Starred Paper aims to understand the psychological, physiological, and developmental effects of PPD on both mothers and their babies while also considering researched strategies for intervention and/or care to alleviate these potential negative outcomes
School Principals’ Perceptions and Perspectives on Culturally Responsive Practices that Enhance the Academic Success of Black K-12 Students
Full text linkThe body of literature outlines the following innovative means to address the achievement gap: the interconnected nature of Culturally Responsive Practices as evidence-based educational interventions for Black K-12 students, along with the continuum of their replication to enhance academic outcomes (Gay, 2018; Hammond, 2015; Ladson-Billings, 1995b; Muhammad, 2020; Paris, 2012). Education is one of the five main components of Social Determinants of Health; equitable access to quality education is deemed to be a human right according to the Partnership for Global Education.
This study centers on the evaluation of best practices regarding culturally responsive educational interventions for Black K-12 students, and school principals’ viewpoints for replication to address the achievement gap. The research explored school principals’ perceptions and perspectives related to the repeated and seamless integration of Culturally Responsive Pedagogy in curriculum development, and student performance evaluation. Also, the research examined the impact of organizational culture on school principals’ decision-making as educational leaders, in relation to the identification and implementation of educational intervention approaches designed for effective student learning.
Additionally, this study aimed to reposition the achievement gap narrative from the lens of a growth mindset, using K-12 school principals’ positions on Culturally Responsive School Leadership to create successful learning environments for Black K-12 students.
Reflections from school principals on their experiences in designing culturally responsive interventions reveal that Culturally Responsive Pedagogy develops the basis for establishing a safe and inclusive learning environment for all students, with a particular focus on Black K-12 students. Culturally Responsive Teaching is crucial for promoting student-centered instruction and enhancing academic outcomes for students from diverse cultural backgrounds
A Comparison of Aerial Magnetic Survey Flightline Interpolation Methods Case Study: Scranton, Newark, and Reading Prong Surveys
Full text linkThe number of spatial interpolation methods that have been applied to the extremely spatially anisotropic data capture that regularly occurs with aerial geophysical measurement surveys. The data capture methodology of the United States Department of Energy’s National Uranium Resources Evaluation (NURE) Aeromagnetic Survey consisted of near parallel flightlines spaced at three-mile intervals flown by helicopter with attached magnetometers taking measurements every second. Unfortunately, the applicability of many spatial interpolation methods is limited to rigid grids that can often be generalized to accommodate randomly distributed measurements, while uncommon or even rare generalization or even novel methods have continued to be developed for extremely spatially anisotropic data interpolation. Additionally, with the capability of machine learning algorithms to be trained to situation specific needs many new spatial interpolation methods relying on machine learning have been emerging in recent years. The machine learning technique Random Forest (RF) has been applied to spatial interpolation using various techniques implemented to prevent the occurrence of Zonal Artifacts, which are bounded zones of isolated prediction distributions, with boundaries arising from decision tree nodes utilizing the spatial coordinate data in splitting the node. This study set of to evaluate the baseline capabilities of seven spatial interpolation methods when applied to aeromagnetic flightline measurements while at the same time investigating the some of the characteristics of Zonal Artifacts when applied in this situation. When it comes to quick implementation particularly in situation where limited expertise is a concern the long-established Thin Plate Splines (TPS) can be expected to perform with up to moderate accuracy requiring little to no parameter tuning to achieve preliminary results. The other interpolation methods explored show some promising capabilities where expertise in the study area, parameter tuning, data collection procedures, etc. can be utilized to enhance the accuracy. In the evaluation of RF Zonal Artifacts, the position of zone boundaries were regularly situated along flightlines with the alignment accentuated in the local RF variation Geographical Random Forests (GRF) which permits the boundaries to follow perturbations in the flightline. The alignment of Zonal Artifact boundaries was also shown be associated with Easting, Northing, and Elevation spatial coordinates