The Predictive Validity Of Ielts And Vietnam High School Graduation Examination English Test : Evidence From English Majors, Tuan Anh Nguyen, Hung Viet Nguyen

PASAA

No abstract provided.

Pragmatic Competence And Transfer In Requests And Refusals : A Study Of Efl University Students In Southern Thailand, Uraiwan Rattanapan Noonkong, Usa Intharaksa

PASAA

No abstract provided.

กฎหมายการหมุนเวียนทรัพยากรพลาสติกของญี่ปุ่น : พัฒนาการ กลไกเชิงสถาบัน และบทเรียนเชิงนโยบายต่อประเทศไทย, พรนภัส สุวลักษณ์ วอห์น, สุจิตรา วาสนาดำรงดี

Thai Environment

บทความนี้มีวัตถุประสงค์เพื่อวิเคราะห์พัฒนาการของกฎหมายญี่ปุ่นด้านการจัดการพลาสติกโดยมุ่งเน้นพระราชบัญญัติส่งเสริมการหมุนเวียนทรัพยากรพลาสติก ค.ศ. 2021 (Act on Promotion of Resource Circulation for Plastics) และกฎหมายที่เกี่ยวข้อง การศึกษานี้ใช้การวิเคราะห์เชิงเอกสารภายใต้กรอบแนวคิดเศรษฐกิจหมุนเวียน (Circular economy) หลักลำดับขั้นการจัดการขยะ (Waste hierarchy) และแนวคิดการจัดการตลอดวัฏจักรชีวิตผลิตภัณฑ์ (Life-cycle approach) เพื่ออธิบายโครงสร้างและกลไกทางกฎหมายในการกำกับการหมุนเวียนทรัพยากรพลาสติก

ผลการศึกษาพบว่า ระบบกฎหมายของญี่ปุ่นได้พัฒนาจากการกำกับการจัดการของเสียแบบปลายทางไปสู่การกำกับการหมุนเวียนทรัพยากรตลอดวัฏจักรชีวิตผลิตภัณฑ์ โดยบูรณาการมาตรการด้านการออกแบบผลิตภัณฑ์ การลดการใช้พลาสติกแบบใช้ครั้งเดียว การจำหน่าย การเก็บรวบรวม การคัดแยกและการรีไซเคิลไว้ภายใต้กรอบกฎหมายเดียวกัน จุดเด่นของระบบกฎหมายญี่ปุ่นอยู่ที่การกำหนดบทบาทของรัฐ องค์กรปกครองส่วนท้องถิ่น ผู้ประกอบการ และประชาชนอย่างเป็นระบบในลักษณะการกำกับหลายระดับ รวมทั้งการใช้มาตรการทางกฎหมายควบคู่กับแรงจูงใจทางเศรษฐศาสตร์และการปรับเปลี่ยนพฤติกรรมของผู้บริโภค ซึ่งสะท้อนแนวปฏิบัติที่ดีในการขับเคลื่อนเศรษฐกิจหมุนเวียนด้านพลาสติก อย่างไรก็ตาม ผลการศึกษายังพบข้อจำกัดบางประการของระบบญี่ปุ่น เช่น การพึ่งพาการเผาขยะเพื่อผลิตพลังงานในสัดส่วนสูงและความท้าทายในการลดการใช้พลาสติกอย่างเป็นรูปธรรม

ข้อค้นพบจากการศึกษานำไปสู่ข้อเสนอแนะสำหรับประเทศไทยว่า ควรมีการพัฒนากฎหมายแม่บทด้านเศรษฐกิจหมุนเวียน การพัฒนาระบบความรับผิดชอบที่เพิ่มขึ้นของผู้ผลิต (Extended Producer Responsibility: EPR) การกำหนดมาตรฐานการออกแบบเชิงนิเวศ (Eco-design) การพัฒนาโครงสร้างพื้นฐานด้านการคัดแยกและรีไซเคิลและการจัดทำระบบข้อมูลเพื่อสนับสนุนการกำกับการหมุนเวียนทรัพยากรอย่างยั่งยืน

Humanizing Education Through Subject-Centered Instruction: A Mixed Methods Case Study Of Engagement And Achievement In An Exploring Hip-Hop As Literature English Elective, Alicia Hyman-Peters

UNF Graduate Theses and Dissertations

This study examined how humanizing education through relationally-driven, subject-centered teaching affects student engagement, literacy, and achievement in an Exploring Hip-Hop as Literature English elective at a diverse high school in Northeast Florida. Drawing on Freire’s concept of humanization, Noddings’ Ethic of Care, Palmer’s focus on subject-centered learning, and the culturally relevant and sustaining pedagogies of Ladson-Billings, Paris, and Alim, the research investigated how humanized education restores meaning and connection to learning. Using a Convergent Parallel Mixed Methods Design, data from thirty students were gathered through surveys, participation and assignment records, standardized assessments, interviews, focus groups, and classroom observations. Quantitative findings …

The Impact Of Censorship On Curriculum And Black Women Secondary English Language Arts Teachers In Florida, Crystal Parker

UNF Graduate Theses and Dissertations

This study examined the instructional, curricular, and school climate impacts of book censorship on Black women secondary English Language Arts teachers, exploring how they navigate and/or resist content restrictions. Using educational criticism and portraiture, this qualitative study captures the nuanced narratives of these educators. Grounded in Bourdieu’s Field Theory, along with Culturally Relevant Pedagogy, Historically Responsive Literacy, Mirrors, Windows, and Sliding Glass Doors, and Cognitive Pluralism, the research addresses the following questions: How do Black women teachers describe the influence of recent book bans on their curriculum choices? In what ways do their identities shape their responses to censorship? Data …

Brewing Black Girl Magic: From Hush-Toned Kitchens To Educational Spaces: A Narrative Inquiry Into The Inherited Wisdom, Radical Resilience, And Professional Becoming Of Black Women, A Three-Paper Dissertation, Sheryl Patterson-Coulibaly

UNF Graduate Theses and Dissertations

This dissertation examines how racialized and gendered expectations shape the professional experiences of Black women in predominantly white educational spaces. Drawing on a three-article format, this study investigates how Black women navigate institutional conditions that depend on their labor yet fail to provide adequate support. Grounded in Black Feminist Marxist Thought and emerging Black Womanist Theory, the study centers the emotional, relational, and spiritual dimensions of Black women’s labor, extending traditional analyses of work, leadership, and resilience.

Of Fire and Fabrication: A Systematic Review on the Myth of Strength and Erasure of Black Women in White Educational Spaces reveals that …

Operationalizing Mtss: A Case Study Of Principal Leadership Practices In Guiding School-Based Leadership Teams Through Inquiry And Improvement Science, Heather M. Teto

UNF Graduate Theses and Dissertations

The COVID-19 pandemic widened academic achievement gaps, creating an urgent mandate for school leaders to implement systemic, data-driven frameworks to support student academic recovery. While the Multi-Tiered System of Supports (MTSS) is a widely adopted framework for addressing these disparities, its success is dependent on the strategic involvement and instructional leadership of the school principal. This qualitative case study explores the lived experiences and leadership characteristics of elementary school principals as they lead School-Based Leadership Teams in implementing a district-developed MTSS framework.

Guided by the principles of Improvement Science and the Plan-Do-Study-Act (PDSA) inquiry cycle, this research examines the specific …

Fostering Reading: Review Of A College Bridge Program For Deaf And Hard Of Hearing High School Students, Cara Wilmot

UNF Graduate Theses and Dissertations

This mixed-methods formative program evaluation examined the reading component of a summer College Bridge Program (CBP) designed for high school students who are deaf and hard of hearing (d/Dhh). Persistent disparities in reading outcomes among d/Dhh students have been linked to differences in language access, communication access, and opportunities to receive specialized instruction. Using the Context, Input, Process, Product (CIPP) evaluation model, this study evaluated how the CBP identified and addressed students' reading needs, implemented evidence-based instructional practices, and supported reading development through a three-week summer program.

Participants included 45 d/Dhh high school students from 12 southeastern states, as well …

Automatic Generation Of Introductory Programming Exercises With Large Language Models, Nguyen Binh Duong Ta, Hua Gia Phuc Nguyen, Gottipati Swapna

Research Collection School Of Computing and Information Systems

Despite recent advances in code generation made possible by large language models (LLMs), programming is still an essential skill that computing students need to master now and in the foreseeable future. In learning programming, frequent practices with exercises set at an appropriate difficulty and knowledge level is of crucial importance for students. However, it’s not a trivial task for instructors to create many good quality exercises customized for each student. Programming problems found on Internet sources such as LeetCode are mostly too challenging for novice programmers with no prior coding knowledge. Recent work in AI-enabled education has been leveraging LLMs …

Choice-Based Crowdshipping For Next-Day Delivery Services: A Dynamic Task Display Problem, Alp Arslan, Firat Kilci, Shih-Fen Cheng, Archan Misra

Research Collection School Of Computing and Information Systems

This paper studies integrating the crowd workforce into next-day home delivery services. In this setting, both crowd drivers and contract drivers collaborate in making deliveries. Crowd drivers have limited capacity and can choose not to deliver if the presented tasks do not align with their preferences. The central question addressed is: How can the platform minimize the total task fulfilment cost, which includes payouts to crowd drivers and additional payouts to contract drivers for delivering the unselected tasks by customizing task displays to crowd drivers? To tackle this problem, we formulate it as a finite-horizon Stochastic Decision Problem, capturing crowd …

Can We Read Ai’S Mind? A Quest For Transparency, Santhosh Kumar Ravindran, Estera Kot, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Although Artificial Intelligence (AI) systems are playing an increasing role in critical domains such as healthcare, finance, and autonomous systems, their decision-making processes remain largely opaque. This paper examines the challenges of AI transparency, addressing the “black box” problem using Explainable AI (XAI) techniques such as SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME). It also examines the ethical, regulatory, and societal implications of AI opacity and proposes a Comprehensive AI Observability (CAO) Framework that integrates deep explainability, provenance tracking, and real-time monitoring to enhance AI accountability. By bridging technical solutions with governance structures, this research emphasizes the …

Actor-Critic For Continuous Action Chunks: A Reinforcement Learning Framework For Long-Horizon Robotic Manipulation With Sparse Reward, Jiarui Yang, Bin Zhu, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Existing reinforcement learning (RL) methods struggle with long-horizon robotic manipulation tasks, particularly those involving sparse rewards. While action chunking is a promising paradigm for robotic manipulation, using RL to directly learn continuous action chunks in a stable and data-efficient manner remains a critical challenge. This paper introduces AC3 (Actor-Critic for Continuous Chunks), a novel RL framework that learns to generate high-dimensional, continuous action sequences. To make this learning process stable and dataefficient, AC3 incorporates targeted stabilization mechanisms for both the actor and the critic. First, to ensure reliable policy improvement, the actor is trained with an asymmetric update rule, learning …

Leveraging Large Language Models For Career Mobility Analysis: A Study Of Gender, Race, And Job Change Using Us Online Resume Profiles, Palakorn Achananuparp, Ye Xu, Yao Lu, Xavier Jayaraj Siddarth Ashok, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

We present a large-scale analysis of career mobility of college-educated U.S. workers using online resume profiles to investigate how gender, race, and job change options are associated with upward mobility. This study addresses key research questions of how the job changes affect their upward career mobility, and how the outcomes of upward career mobility differ by gender and race. We address data challenges – such as missing demographic attributes, missing wage data, and noisy occupation labels – through various data processing and Artificial Intelligence (AI) methods. In particular, we develop a large language models (LLMs) based occupation classification method known …

Dual-Lora And Quality-Enhanced Pseudo Replay For Multimodal Continual Food Learning, Xinlan Wu, Bin Zhu, Feng Han, Pengkun Jiao, Jingling Chen

Research Collection School Of Computing and Information Systems

Food analysis has become increasingly critical for health-related tasks such as personalized nutrition and chronic disease prevention. However, existing large multimodal models (LMMs) in food analysis suffer from catastrophic forgetting when learning new tasks, requiring costly retraining from scratch. To address this, we propose a novel continual learning framework for multimodal food learning, integrating a Dual-LoRA architecture with Quality-Enhanced Pseudo Replay. We introduce two complementary low-rank adapters for each task: a specialized LoRA that learns task-specific knowledge with orthogonal constraints to previous tasks’ subspaces, and a cooperative LoRA that consolidates shared knowledge across tasks via pseudo replay. To improve the …

Design Principles For Customer-Engaging Digital Service Systems: An Action Research Study, Keng Leng Siau, Xiaofeng Chen, Xin Tan

Research Collection School Of Computing and Information Systems

Digital services represent a business approach employed by organizations to operate in the digital environment. However, systematic development guidelines for developing quality digital service systems are lacking in the literature. The authors identified four general challenges for developing and implementing customer-engaging digital service systems (CEDSS). By employing the method of canonical action research in a digital service system project, they derived 10 design principles for developing high-quality CEDSS. They empirically evaluated the design principles in the development project and through follow-up focus group sessions. The design principles provide applicable and actionable guidelines for the development of CEDSS.

Towards Secure Program Partitioning For Smart Contracts With Llm’S In-Context Learning, Ye Liu, Yuqing Niu, Chengyan Ma, Ruidong Han, Wei Ma, Yi Li, Debin Gao, David Lo

Research Collection School Of Computing and Information Systems

Smart contracts are highly susceptible to manipulation attacks due to the leakage of sensitive information. Addressing manipulation vulnerabilities is particularly challenging because they stem from inherent data confidentiality issues rather than straightforward implementation bugs. To tackle this by preventing sensitive information leakage, we present PARTITIONGPT, the first LLM-driven approach that combines static analysis with the in-context learning capabilities of large language models (LLMs) to partition smart contracts into critical (privileged) and normal codebases, guided by a few annotated sensitive data variables. We evaluated PARTITIONGPT on 18 annotated smart contracts containing 99 sensitive functions. The results demonstrate that PARTITIONGPT successfully generates …

Editorial: Special Section On Challenges And Opportunities In Retrieval-Augmented Generation For Llms: Techniques, Trends, And Applications, Philip S. Yu, Haofen Wang, Feida Zhu

Research Collection School Of Computing and Information Systems

Retrieval-Augmented Generation (RAG) represents a transformative advancement for Large Language Models (LLMs) by integrating external knowledge to substantially improve accuracy and mitigate hallucinations. As a pivotal technology in the contemporary generative Artificial Intelligence (AI) landscape, RAG addresses fundamental challenges in knowledge-intensive tasks. This special issue serves as a dedicated platform to showcase these cutting-edge advancements. It features six rigorously peer-reviewed papers that present state-of-the-art research and applications in the rapidly evolving field of RAG.

Qualitative Study For Llm-Assisted Design Study Process: Strategies, Challenges, And Roles, Shaolun Ruan, Rui Sheng, Xiaolin Wen, Jiachen Wang, Tianyi Zhang, Yong Wang, Tim Dwyer, Jiannan Li

Research Collection School Of Computing and Information Systems

Design studies aim to develop visualization solutions for real-world problems across various application domains. Recently, the emergence of large language models (LLMs) has introduced new opportunities to enhance the design study process, providing capabilities such as creative problem-solving, data handling, and insightful analysis. However, despite their growing popularity, there remains a lack of systematic understanding of how LLMs can effectively assist researchers in visualization-specific design studies. In this paper, we conducted a rnulti-stage qualitative study to fill this gap, which involved 30 design study researchers from diverse backgrounds and expertise levels. Through in-depth interviews and carefully-designed questionnaires, we investigated strategies …

Artem: Enhancing Large Language Model Agents With Spatial-Temporal Episodic Memory, Cassandra Hui Ming Tan, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Current large language models (LLMs) exhibit significant deficiencies in episodic memory tasks including encoding, storing, and retrieving specific information from temporally dependent events over a long period of time. Recent approaches to handle memory tasks in LLMs, such as in-context learning, retrieval-augmented generation (RAG), and fine-tuning, may resolve the long-term retention issues, but are still inadequate to handle tasks requiring chronological awareness of the stored information. We introduce Agentic Retrieval with Temporal-Episodic Memory (ARTEM), a hybrid LLM-based agent architecture integrating LLMs with a self-organizing neural network named Spatial-Temporal Episodic Memory (STEM), designed to handle episodic memory tasks. Our approach employs …

Dystop: Dynamic Staleness Control And Topology Construction For Asynchronous Decentralized Federated Learning, Yizhou Shi, Qianpiao Ma, Yan Xu, Junlong Zhou, Ming Hu, Yunming Liao

Research Collection School Of Computing and Information Systems

Federated Learning (FL) has emerged as a potential distributed learning paradigm that enables model training on edge devices (i.e., workers) while preserving data privacy. However, its reliance on a centralized server leads to limited scalability. Decentralized federated learning (DFL) eliminates the dependency on a centralized server by enabling peer-to-peer model exchange. Existing DFL mechanisms mainly employ synchronous communication, which may result in training inefficiencies under heterogeneous and dynamic edge environments. Although a few recent asynchronous DFL (ADFL) mechanisms have been proposed to address these issues, they typically yield stale model aggregation and frequent model transmission, leading to degraded training performance …

Llamoco: Instruction Tuning Of Large Language Models For Optimization Code Generation, Zeyuan Ma, Yue-Jiao Gong, Hongshu Guo, Jiacheng Chen, Yining Ma, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Recently, combining the strength of large language models (LLMs) and Evolutionary Computation (EC) has shown promising results for addressing optimization problems. It typically involves either iterative next-step solution seeking or directly prompting LLMs to generate critical optimization codes. However, these methods often suffer from low computational efficiency, high sensitivity to prompt design, and a lack of domain-specific knowledge. We introduce LLaMoCo, the first instruction-tuning framework designed to adapt LLMs for solving optimization problems in a code-to-code manner. LLaMoCo features a comprehensive instruction set that includes code-style problem descriptions as input prompts and robust optimization codes from expert EC optimizers as …

Understanding Wage Theft: Beyond The Numbers Through Community Practice, Lived Experience, And Research, André Simões Da Silva, Lenita Reason, Cristina Araujo Brinkerhoff

Gastón Institute Publications

Wage theft is a widespread form of labor exploitation that disproportionately affects immigrant and other vulnerable workers. This report examines the scope and impact of wage theft in Massachusetts by analyzing case data from the Brazilian Worker Center (BWC) alongside wage and labor enforcement data from the Massachusetts Attorney General’s Office (AGO). The analysis demonstrates how wage theft affects immigrant workers across industries, with particularly high numbers of cases in construction, cleaning, and hospitality. The data also reveal significant gaps in the reporting and enforcement of wage violations, particularly among domestic workers, whose cases are likely substantially underrepresented in available …

Social Support, Trauma And Neurophysiological Stress, Devon S. Glicken

UNF Graduate Theses and Dissertations

Traumatic life experiences and the prolonged effects of stress can negatively impact an individual’s mental and physical health. Hyperreactivity to acute stressors can often be seen in individuals with anxiety, depression, and suicidal ideations, conditions commonly observed with endocrine dysfunction. How do traumatic experiences, particularly experiences related to military affiliation, influence stress responses and feelings of burdensomeness and thwarted belongingness? This study predicted (1) that military-affiliated individuals (and those with PTSD symptomology and high perceived life stress) will have heightened neurophysiological responses to minor levels of acute stress compared to individuals without military-affiliations (and those without PTSD symptomology or high …

Novice Teachers' Perceptions Of Clinical Experience And Their Preparedness To Teach In High-Need Urban Schools, Robin D. Renelus

UNF Graduate Theses and Dissertations

This hermeneutic phenomenological study examined novice teachers’ perceptions of how clinical experiences in a teacher preparation program prepared them to teach in high-need urban schools. The study included 12 novice teachers with three or fewer years of teaching experience who completed their clinical experience at the same university in Northeast Florida. Data were collected using Seidman’s (2019) three-interview approach, which explored participants’ backgrounds, day-to-day teaching experiences, and reflections on their sense of preparedness. Data were analyzed to develop textural descriptions of what participants experienced and structural descriptions of how those experiences were shaped (Moustakas, 1994).

Participants described clinical experiences as …

From Preparation To Practice: A Study Of Assistant Principals After Completion Of An Aspiring Assistant Principal Preparation Program, Mallory L. Mcconnell

UNF Graduate Theses and Dissertations

Leadership programs and readiness in schools, particularly those in Florida, is well studied. However, few studies have investigated how current assistant principals who have completed Clay County District School’s Aspiring Assistant Principal Program describe their experiences, believe the program has prepared them for the realities of school leadership, or identify the most impactful elements that have supported their leadership development. This case study seeks to collect foundational research knowledge by analyzing data from the program, participants, and key facilitators. Using a sampling of current assistant principals who have completed the Aspiring Assistant Principal Program, this research examines the results in …

Development Of Alternative Plasma Etching Techniques For The Selective Removal Of Tan With Respect To Sioch Dielectric Materials To Enable Future Back-End-Of-The-Line Scaling, Ivo Otto Iv

Electronic Theses & Dissertations (2024 - present)

Transistor scaling has continued according to Moore’s Law for over fifty years. As transistor size decreases, adequate power delivery is required to enable transistor scaling without performance loss. Power delivery is provided by a metal interconnect network with insulating dielectric that connects the transistor level to the power source, the signal speed within this metal line network limiting transistor level switching speeds. Reduction of signal delay has moved from primarily dimension-based improvement towards adoption of conductor and dielectric materials with lower resistivity and a reduced dielectric constant value, respectively: transitioning from Al/SiO₂ to Cu/low-κ SiOCH. With this transition comes …

Genetic Diversity Of Cryptosporidium Species In New York State, Kimberly A. Mergen

Electronic Theses & Dissertations (2024 - present)

The knowledge regarding Cryptosporidium infections in New York State (NYS) is severely lacking in two ways: 1) there are currently no NYS-based data regarding the subtypes of Cryptosporidium parvum and Cryptosporidium hominis, which are the two most prevalent species that infect humans and 2) information regarding uncommon Cryptosporidium species that infect the New York population is also unavailable. Filling these gaps concerning this pathogenic parasite would provide a substantial amount of information when considering public health, outbreak investigations, and prevention measures. Therefore, improving Cryptosporidium subtype and species surveillance in NYS will aid in prevention and control efforts as well …

As If It Were Food: A Prose Translation Of The Old English Genesis B, Kane R. Malone

Electronic Theses & Dissertations (2024 - present)

The anonymous Old English poem known as “Genesis B” comes down to us as one of the most inherently human retellings of the Fall of Adam and Eve. Despite this, the piece is seldom read by the average twenty-first century middle-school learner. The poem, originally penned in Old English, has been translated into modern English numerous times, yet as I read through a variety of these translations, they all seemed to downplay the human element which I found intriguing. Thus, I created my own translation of “Genesis B” with a more general audience in mind, looking to create something that …

Entropic Foundation Of Finance And Physics: Securities Price Dynamics And Quantum Theory, Mohammad Abedi

Electronic Theses & Dissertations (2024 - present)

In many scientific and financial contexts, we must reason and make predictions under conditions of incomplete information. This dissertation develops Entropic Dynamics (ED) as a unified framework for deriving dynamical laws directly from principles of inference. Within this approach, probability distributions represent states of knowledge, and their evolution is determined through entropy maximization subject to relevant constraints. This leads to a novel concept of entropic time and a formulation of dynamics as an inferential process. In this talk, I will present how ED provides a common foundation across multiple domains. In physics, quantum dynamics for particles and scalar fields in …

Human Vaccine Hesitancy Spillover In The Field Of Veterinary Medicine: A Systematic Narrative Review Of Impacts And Veterinary Responses, Allison Schimpf

HEAL Project Outputs

Human vaccine hesitancy spillover in the veterinary field is a relatively new concept that has gained traction since the COVID-19 pandemic. Concerns about vaccine safety have increased among pet owners leading to questions about the potential impacts of reduced vaccination and how veterinarians can address these attitudes. A systematic search strategy following PRISMA 2020 guidelines was used with 3 different databases to collect peer-reviewed research articles from 2022 until now. The initial search yielded 376 articles for review and 11 were included after screening. Articles were analyzed using a narrative review format. Results showed that pet owners are more vaccine …