Digital Commons Network^™

Empirical Evaluation Of Bayes Error Rate Bounds In Binary Classification, Riley May

All Graduate Theses and Dissertations, Fall 2023 to Present

Classification tasks are fundamental in statistical machine learning. In classification tasks, a general goal is to build or select a model that can correctly classify data with as few errors as possible. However, for a particular dataset, the minimal number of errors achievable is seldom zero since overlap in the data makes errors unavoidable. As a result, it is often difficult for machine learning practitioners and data scientists to know whether classification errors can be reduced through further refinement. A potential solution to this lies in the Bayes error rate (BER). The BER is the lowest error rate achievable for …

From Marriage To Migration: Analyzing Return Migration, Gender Inequalities And Household Resource Allocation Patterns, Saeed Ahmad

All Graduate Theses and Dissertations, Fall 2023 to Present

In Kyrgyzstan, a country shaped by deep-rooted traditions and high rates of migration, women's lives are often influenced by powerful cultural expectations, economic pressures, and limited choices. My research explores how these forces intersect—particularly through the lens of bride kidnapping, migration, and how families use money and resources. Together, these issues reveal how gender inequality operates in everyday life, and how women navigate both constraint and resilience.

This dissertation includes three connected studies. The first examines how the COVID-19 pandemic disrupted international labor migration, especially for Kyrgyz migrants working in Russia. Many returnees lost their jobs and faced hostility or …

An Exploratory Study Of The Vertical Snarc Effect In Mayan Numerals: Effects Of Language Transparency And Reading Direction, Emmett A. Speed

All Graduate Theses and Dissertations, Fall 2023 to Present

The Mayan numerical system, used by the ancient Maya people, is very different from the Western Arabic numerical system. Instead of being based on 10, it's based on 20, and it uses dots and bars instead of the numbers 0 through 9. This study explored how people learn and understand Mayan numbers.

Participants took a 2.5-hour online course to learn Mayan numerals and number words. They were tested to see how quickly and accurately they could recognize and compare Mayan numerals. The results showed that people can learn the Mayan number system and use it automatically.

The study also looked …

Distal Impact Of Learning Trajectories On Motivational Factors In Second Language Acquisition Of Adult English Learners, Feng Zhang

All Graduate Theses and Dissertations, Fall 2023 to Present

Learning a foreign language is a long-term process sustained by learners’ motivation, self-efficacy, and self-regulation. While prior research has established that past performance influences these motivational factors, overlooking the impact of past performance on current motivational constructs. This dissertation explores how past learning performance impact current motivational factors. Using a person-centered approach, three subgroups were identified as latent learning profiles within the sample population based on their performance features: the high-performing early peak profile, the stable profile, and the rising profile. Regression models were conducted to evaluate the extent to which latent learning profiles predicted motivational variables. The results showed …

Exploring The Long-Term Impact Of Dating And Family Violence On American Indian Youth And Adults: The Role Of Belongingness In Moderating Negative Effects, Racheal M. Killgore

All Graduate Theses and Dissertations, Fall 2023 to Present

Exposure to violence during childhood and adolescence is an important issue, particularly among Native Americans, who experience violence at higher rates compared to other racial/ethnic groups. This early exposure to violence can significantly affect future physical and mental health outcomes—including depression, substance abuse, suicide attempts, obesity, and premature death—while also shaping subsequent relationships in adulthood. Though widely studied in the general population, research focused on American Indians is lacking, with cultural contexts and factors uniquely shaping the experiences of those affected. In AI/AN communities, belongingness is important for well-being and, as such, is a relevant cultural factor that calls for …

A Scoping Review Of Arabic Self-Reported Measures Of Hearing, Tinnitus And Hyperacusis: Limited Quality And Quantity, Abdulsalam Alhaidary, Kishore Tanniru, Kevin J. Munro, Ahmed Bin Afif, Ibrahim Almufarrij

Saudi Medical Journal

ABSTRACT Objectives: To identify Arabic-language self-report measures related to hearing, tinnitus and hyperacusis and evaluate whether they had been validated and cross-culturally adapted following translation from other languages. Methods: The review followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR guidelines) and searched 5` information sources (PubMed, Embase, Web of Science, PsycINFO and Google Scholar) from their inception to September 2023, identifying all originally developed or translated Arabic self- or parent-report measures related to hearing, tinnitus and hyperacusis. A total of 1,458 records were screened, with only 28 deemed eligible for inclusion. Results: This …

Trust In Healthcare Ai Can’T Just Be Designed – It Must Be Felt By Clinicians And Patients, Adriana Banozic-Tang, Heng Wang

Research Collection Yong Pung How School Of Law

Trust in healthcare AI currently over-relies on system design, not lived medical realities.Continuous feedback loops are necessary to embed trust in healthcare AI that is responsive to clinician and patient needs.Initiatives in South-East Asia show how trust in technology can be extended from policy to practice.

Ai In The Judiciary: The Singapore Case, Nydia Remolina Leon

Research Collection Yong Pung How School Of Law

This paper examines the integration of Artificial Intelligence (AI) within the judicial system of Singapore. Singapore's judiciary has embraced AI not as a tool for adjudication, but as an augmentative instrument for legal research, procedural efficiency, and access to justice. It provides a detailed account of AI use cases in the courts, including case summarization, evidence review, assistance for selfrepresented litigants, and tools like the Divorce Assets Informative Division Estimator. The discussion then turns to the legal profession, exploring how law firms in Singapore are adopting AI technologies. The paper also addresses how AI implementation in the judicial system is …

Full Circle: Historiography, Missiology, And Theology In Lin Yutang’S From Pagan To Christian, Teng-Kuan Ng

Research Collection College of Integrative Studies

Lin Yutang (1895–1976) is renowned for bridging the Chinese and Western worlds through his prolific writings, but the vital role of religion in his intercultural endeavors remains underappreciated. This article situates his seminal work of religious reflection, From Pagan to Christian (1959), within the context of World Christianity, defined as both movement and method. Lin’s departure from the Christianity of his youth into Chinese religions—and back again to the church in his later years—presents timely insights for the study of religious change and pluralism in global modernity. Analyzing the text’s decolonizing, dialogical, and polyphonic dimensions, this article brings Lin’s spiritual …

The Marginalization Of Black Students And The Burnout Of Black Teachers, Jasmine N. Wilson

Language Arts Journal of Michigan

Black students' language and culture should matter inside the classroom, but the K-12 education system perpetuates racist ideologies that otherwise stifle and shame Black students and their identities. There is a disproportion between the number of White teachers and Black students in minority-serving K-12 institutions, and this racial mismatch severely influences Black students’ academic success. In addition to the racial mismatch between White teachers and Black students, K-12 institutions foster a prejudiced learning environment that condemns African American English speakers. There is an abundance of research that suggests that Black teachers, Black culture, and Black English are of the utmost …

Reflection And Reimagination As Resistance: Towards Humanizing Critical Writing Pedagogy, Grace Y. Kang, Sonia M. Kline

Language Arts Journal of Michigan

Given the pressures, demands, and standardization teachers face in our sociopolitically charged times, teachers need opportunities to reflect and reimagine their instruction. Drawing on critical and related scholarship, we conceptualize critical humanizing writing pedagogy. We share our instructional moves as teacher educators for enacting humanizing writing pedagogy in a graduate course and supporting teachers to enact humanizing writing pedagogy in their K-12 classrooms. Specifically, we show how a graduate student and practicing teacher found ways to shift toward critical orientations as she navigated her school’s curriculum and state standards. We argue that sociocultural and critical lenses provide powerful tools for …

Dialogic Instruction: Teachers Can Have Their Cake, And Eat It, Too, Rebecca L. Lee

Language Arts Journal of Michigan

Dialogic instruction is a talk-intensive approach to learning and teaching that is student-centered and discussion-based, promoting collaboration and academically productive conversations. Recently, educators across the country have increased the amount of time spent preparing students for standardized assessments, which often reduces teaching and learning to test preparation. While this tension suggests that teachers must choose between good teaching or good test scores, dialogic instruction is a promising practice that can enhance students’ reading comprehension outcomes while centering student choice and valuing student voice. Research shows dialogic instruction is most effective when teachers a) co-create a conducive classroom climate, b) incorporate …

An Examination Of The Lived Experiences Of Community College Students Of Color Who Utilize On-Campus Food Pantries, Maria Luisa Marte

Theses, Dissertations and Culminating Projects

In this dissertation, I present the findings of a descriptive phenomenological study I conducted focused on examining the experiences of community college students of color who utilize on-campus food pantries, aiming to understand how these resources impact their well-being. Through in-depth interviews, two central themes emerged. The first theme, Introduction to the On-Campus Food Pantry, highlights the accessibility of the service, with participants emphasizing the simplicity and efficiency of the registration process as a key factor in their initial engagement. The second theme, Experiences Using the Pantry, reveals that students found the pantry environment to be welcoming and non-stigmatizing, fostering …

A Collaborative Teaching Approach: Teaching Emergent Bilinguals In Higher Education, Erika Oliveros

Theses, Dissertations and Culminating Projects

This dissertation examines the collaboration between two college instructors, one in writing and one in psychology, to enhance support for emergent bilinguals at a private university in the northeastern United States. While collaboration among educators is widely encouraged in K–12 settings, it is far less common and studied in higher education, particularly in relation to language-minoritized students. Through an action research model, this study examines how our informal exchanges evolved into a more intentional and reflective collaboration over time. Grounded in the frameworks of translanguaging (García, 2009) and community cultural wealth (Yosso, 2005), the study traces the evolution of our …

This Is Fine: A Reflexive Case Study On Beliefs, Institutional Rhetoric, And The Quiet Despair Of Capstone Completion, Dana Turner Blair

Graduate Theses and Dissertations

For graduate students, capstone writing is often a stressful process that involves significant obstacles to progress. This dissertation presents an exploratory multi-case study of four graduate capstone writers to examine how institutional contexts and rhetoric shape students’ beliefs and related emotions and behaviors during the high-stakes, low-structure settings of capstone research projects. Data for this study was collected through interviews and reflexively compared with reflections from the principal researcher. To gather insights into the relationship between writers’ internal beliefs and institutional contexts, interview excerpts were analyzed according to both cognitive behavioral coaching and institutional critique frameworks. Findings indicated that students …

Firm Disclosures And Retail Investor Behavior: The Role Of Information Type, Disagreement, And Social Networks, Hansol Yoon

Graduate Theses and Dissertations

This paper examines whether disclosure characteristics–specifically hard versus soft information–influence disagreement among retail investors, whether due to differences in information sets or interpretation, and how such disagreement subsequently affects trading volume. Using a sample of 85,050 earnings conference calls and StockTwits disagreement data from 2010 to 2021, I find that hard information (i.e., earnings figures) is negatively associated with investor disagreement, while soft information (i.e., forward-looking statements) is positively associated with it. Further analysis reveals that the disclosure characteristics impact trading activity only indirectly, through their influence on investor disagreement. Additionally, I examine the moderating role of social network centrality, …

Difficulty In American Dramatic Literature, David Turkel

Dissertations

Speaking broadly, this dissertation explores the marginalization of American drama within the field of literary studies. In attempting to account for this marginalization, theater scholars have tended to invoke the genre’s supposed lack of “difficulty,” meaning its failure to pose meaningful interpretive challenges to its readers. However, this dissertation takes an alternative view of the matter, contending that if American drama has indeed been marginalized, it is not because literary studies departments have regarded it as intrinsically “simpler” than other literary genres; in fact, it is theater scholars who have been more likely to read the genre as simple, or …

Focus: Evaluating Pre-Trained Vision-Language Models On Underspecification Reasoning, Kankan Zhou, Yibin Lai, Kyriakos Mouratidis, Jing Jiang

Research Collection School Of Computing and Information Systems

Humans possess a remarkable ability to interpret underspecified ambiguous statements by inferring their meanings from contexts such as visual inputs. This ability, however, may not be as developed in recent pre-trained visionlanguage models (VLMs). In this paper, we introduce a novel probing dataset called FOCUS to evaluate whether state-of-the-art VLMs have this ability. FOCUS consists of underspecified sentences paired with image contexts and carefully designed probing questions. Our experiments reveal that VLMs still fall short in handling underspecification even when visual inputs that can help resolve the ambiguities are available. To further support research in underspecification, FOCUS will be released …

Think Both Ways: Teacher-Student Bidirectional Reasoning Enhances Mcq Generation And Distractor Quality, Yimiao Qiu, Yang Deng, Quanming Yao, Zhimeng Zhang, Zhiang Dong, Chang Yao, Jingyuan Chen

Research Collection School Of Computing and Information Systems

Generating high-quality Multiple Choice Questions (MCQs) remains challenging for educational tools due to the need for contextual relevance and plausible distractors. Existing methods still struggle with these dual requirements, leading to questions that lack depth and distractors that are either too obvious or irrelevant. In this paper, we propose BiFlow, a novel framework that integrates bidirectional reasoning perspectives: teacher reasoning generates contextually relevant questions and plausible distractors, while student reasoning evaluates question clarity and the misleading nature of the distractors. To further enhance reasoning, we introduce PathFinder, a mechanism that employs breadth-first search and Chainof-Thought (CoT) strategies to explore diverse …

Taclr: A Scalable And Efficient Retrieval-Based Method For Industrial Product Attribute Value Identification, Yindu Su, Huike Zou, Lin Sun, Ting Zhang, Haiyang Yang, Chen Li Yu, David Lo, Qingheng Zhang, Shuguang Han, Jufeng Chen

Research Collection School Of Computing and Information Systems

Product Attribute Value Identification (PAVI) involves identifying attribute values from product profiles, a key task for improving product search, recommendation, and business analytics on e-commerce platforms. However, existing PAVI methods face critical challenges, such as inferring implicit values, handling outof-distribution (OOD) values, and producing normalized outputs. To address these limitations, we introduce Taxonomy-Aware Contrastive Learning Retrieval (TACLR), the first retrieval-based method for PAVI. TACLR formulates PAVI as an information retrieval task by encoding product profiles and candidate values into embeddings and retrieving values based on their similarity. It leverages contrastive training with taxonomy-aware hard negative sampling and employs adaptive inference …

Consistent Client Simulation For Motivational Interviewing-Based Counseling, Yizhe Yang, Palakorn Achananuparp, Heyan Huang, Jing Jiang, Nicholas Gabriel Lim, Cameron Shi Ern Tan, Phey Ling Kit, Jenny Xiuhui Giam, John Pinto, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Simulating human clients in mental health counseling is crucial for training and evaluating counselors (both human or simulated) in a scalable manner. Nevertheless, past research on client simulation did not focus on complex conversation tasks such as mental health counseling. In these tasks, the challenge is to ensure that the client’s actions (i.e., interactions with the counselor) are consistent with with its stipulated profiles and negative behavior settings. In this paper, we propose a novel framework that supports consistent client simulation for mental health counseling. Our framework tracks the mental state of a simulated client, controls its state transitions, and …

Debate, Reflect, And Distill: Multi-Agent Feedback With Tree-Structured Preference Optimization For Efficient Language Model Enhancement, Xiaofeng Zhou, Heyan Huang, Lizi Liao

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) continue to set new standards in knowledge-intensive and complex reasoning tasks, yet their high computational demands limit widespread adoption. While distilling large models into smaller ones offers a sustainable solution, current techniques—such as static knowledge distillation, resource-intensive reinforcement learning from human feedback, or limited self-reflection—struggle to yield substantial and lasting performance gains. In this paper, we present a novel Debate and Reflect (D&R) framework that orchestrates multi-turn debates between smaller models and stronger teacher models, eliciting actionable feedback (e.g., error analysis, corrective strategies) to guide student models. Further, we introduce Tree-structured Direct Preference Optimization (T-DPO) to …

Memotune: A Measure And Moment-Driven Fine-Tuning Framework For Quantized Large Language Models, Yun Zhang, Xue Geng, Lizi Liao, Jintong Sun, Minghe Yu, Ge Yu

Research Collection School Of Computing and Information Systems

Quantizing large language models (LLMs) is essential for reducing memory and computational costs in natural language processing. Existing methods combine quantization with parameter-efficient fine-tuning but often fail to meet practical performance requirements. This paper introduces MeMoTune, a novel fine-tuning framework for quantized LLMs. By employing a measure and moment approach within a low-rank approximation framework in probability measure space, MeMoTune optimizes the objective function for superior fine-tuning results. The update process is further refined through scaled gradient, enhancing convergence efficiency and noise robustness. Experiments on tasks like text generation, summarization, and understanding show MeMoTune significantly outperforms state-of-the-art methods, e.g. fine-tuning …

Advancing Molecular Graph-Text Pre-Training Via Fine-Grained Alignment, Yibo Li, Yuan Fang, Mengmei Zhang, Chuan Shi

Research Collection School Of Computing and Information Systems

Understanding molecular structure and related knowledge is crucialfor scientific research. Recent studies integrate molecular graphswith their textual descriptions to enhance molecular representationlearning. However, they focus on the whole molecular graph andneglect frequently occurring subgraphs, known as motifs, whichare essential for determining molecular properties. Without suchfine-grained knowledge, these models struggle to generalize to un-seen molecules and tasks that require motif-level insights. To bridgethis gap, we propose FineMolTex, a novel Fine-grained Moleculargraph-Text pre-training framework to jointly learn coarse-grainedmolecule-level knowledge and fine-grained motif-level knowledge.Specifically, FineMolTex consists of two pre-training tasks: a con-trastive alignment task for coarse-grained matching and a maskedmulti-modal modeling task for …

Cultivating Identity, Workforce Readiness, And Heutagogical Lifelong Learning: The Case For Student-Trained Ai Agents In Postsecondary Education, James Hutson

Faculty Scholarship

The accelerated integration of human-centered artificial intelligence and human-computer intelligent interaction (HCII) into postsecondary education has inaugurated a paradigm shift in how learners develop cognitive, socio emotional, and professional competencies. This article argues that requiring students to iteratively build and refine custom AI agents—digital “clones” or GPTs trained on their evolving beliefs, knowledge, values, and interests addresses three pressing challenges facing contemporary higher education. First, the process of self-modeling via agent training compels deep self-reflection, fostering socio-economic development and identity formation during the critical neurodevelopmental period that extends into the mid-twenties. Second, as industry trends increasingly prioritize the creation of …

A Study Of Urban High School Teachers' Perceptions Of Multicultural Education, Clifford D. Alexander

Electronic Theses and Dissertations

This dissertation investigated urban high school teachers’ perceptions of multicultural education and how those perceptions related to instructional practices. Guided by culturally responsive pedagogy, the study addressed the persistent achievement gap among minority students and the limited integration of multicultural education in U.S. public schools. The purpose of this study was to evaluate teachers’ perceptions of multicultural education and examine their connection to teaching practices and cultural background. A quantitative cross-sectional survey design was employed with a sample of 331 urban high school teachers. Findings indicated that the majority of participants held positive views toward multicultural education, recognizing its role …

A Relational Forestsoft Set Approach To Modeling And Optimizing Teaching Quality In University English Translation Programs Amid Digital Transformation, Jianguo Liu, Ruohan Liu

Neutrosophic Sets and Systems

No abstract provided.

A Plithogenic Neutrosophic Hypersoft Set-Based Framework With Comparative Analysis For Measuring Teaching Practice Effectiveness In University-Level Vocal Music Instruction, Huiqiu Du

Neutrosophic Sets and Systems

No abstract provided.

Adaptive Neutrosophic Integration And Trust Modeling: A New Framework For Evaluating Mobile Communication Network Migration Perception, Ke Li

Neutrosophic Sets and Systems

No abstract provided.

A New Hybrid Deep Learning Method With Neutrosophic Sets For Social Media Sentiment Analysis Of The Covid-19 Vaccine,, Tasneem Abdelrahman, Mohamed El-Rashidy, Mohamed Marie

Neutrosophic Sets and Systems

No abstract provided.