Digital Commons Network^™

Improve Mentor Communication And Listening By Implementing Jim Knight’S Impact Cycle With Preservice Teachers, Molly Montavon

Master's Theses & Capstone Projects

Early childhood education preservice teachers encounter a variety of mentors throughout their education journey with a varying degree of success. The problem is that early childhood education (ECE) students completing preservice teaching experiences within a community college lab school are not provided with equitable mentoring experiences, resulting from using inconsistent techniques across all classrooms and mentors. The purpose of the inquiry-based research is to explore the use of Jim Knight’s (2022) Impact Cycle to support the mentoring process for early childhood education preservice teachers. Consistent, high-quality coaching and mentoring are vital to the success of preservice teachers. This belief has …

Using Decodable Books For In-Class Independent Reading To Improve Accuracy, Lindsey Meyer

Master's Theses & Capstone Projects

Young children often receive time to read independently at school, so they can practice and apply the skills they are learning in the classroom to connected texts. It is important to be mindful of the types of books available to students during independent reading to ensure the books provide the proper amount of support for reading success and achievement. Most classrooms are filled with traditional books, which offer a wide range of text complexity, but decodable books, books that follow a phonetic scope and sequence, are being used now more than ever before, as teachers work to more closely align …

Digital Commons Statistics For July 2025, Liberty University

Digital Commons Statistics

No abstract provided.

Instructional Design: An Overview Of Critical Sources, Robyn Hartman

Library Faculty Publications

Instructional design serves as the backbone of effective education and training across diverse learning environments. From traditional classrooms to corporate training programs and online learning platforms, thoughtfully designed instruction creates the foundation for meaningful learning experiences. This essay provides a comprehensive overview of key resources in instructional design in higher education, offering both historical context and contemporary applications for professionals in the field. This essay is intended for novice higher education instructional designers seeking to build their foundational knowledge and experienced subject-matter educators looking to deepen their understanding of design principles and practices for their courses.

The Buzzard In The Abolitionist Sea; An Examination Of Maritime Suppression, Imperial Policy, And The Slave Trade Through The Royal Navy’S Hms Buzzard, 1830s-1840s, Sean Joaquim Coudray-Pereira

Master's Theses

Analysis of the Royal Navy through the microhistory of the HMS Buzzard following the abolition of the slave trade between 1807 and the 1840s by Great Britain offers insight into the moral ambiguities and complexities of the humanitarian mission. The historiography of the slave trade has primarily focused on the moral and economic ideology behind its abolition, pitting one against the other. Applying a micro-historic approach highlights the nuances of both arguments, and through the HMS Buzzard’s crew, captives, disease, voyages, and legal battles accentuates the blend of both argument approaches. The case study of its longevity through all six …

Governing Migration, Producing Skills: Emigration And Education In The Philippines, Yasmin Y. Ortiga, Roderick. Galam

Research Collection School of Social Sciences

This article examines skill as an integral yet understudied aspect of emigration governance. To date, migration studies have mainly focused on how the demand for migrant skills drive people's movements across borders, shaping the conditions for entry into popular destinations in the West. In contrast, less is known as to how skills also shape the way governments manage emigration, pushing would-be migrants to acquire certain capacities well before they leave their countries of origin. Drawing from the case of the Philippines, this article discusses how state agencies have used skills training to dominate specific markets for migrant professionals and demand …

Stockpiling, Forecasting And Protecting Skills: Skilling As Technique Of Preparedness In Times Of Crises, Rebecca Ye, Yasmin Y. Ortiga

Research Collection School of Social Sciences

In this comparative and situational analysis, we examine how nation-states use skilling as a technique of preparedness during crisis moments. By analysing two strategically selected country cases, Singapore and Sweden, during a critical phase of a global pandemic, we identify three techniques: stockpiling, forecasting, and protecting skills, and how these were enacted as a means to perform preparedness. Stockpiling skills was observed to take place as a rapid response; forecasting skills was a technique enacted with a view on the longer-term horizon and protecting skills was mobilised as a short-term future technique, where boundaries were assembled around skilling. While there …

The B2biers System: A Content-Based Perspective On Maximizing Influence And Subscription In Social Networks, Konstantinos Theocharidis, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

The popular problem of Influence Maximization (IM) asks for the k users who can maximize the influence of a fixed post in a social network. In contrast, the problem of Content- Aware Influence Maximization (CAIM) asks for the k features to form a viral tunable post in a social network starting its diffusion from a fixed set of initial adopters. CAIM paves the way for a number of novel problems to be studied that altogether can lead to the development of a system that would be valuable for advertisers who manage social network pages. This holds since features (brands) in …

Prompttutor: Effects Of An Llm-Based Chatbot On Learning Outcomes And Motivation In Flipped Classrooms, Yuhao Zhang, Eng Lieh Ouh, Chong Jee Adam Ho, Siaw Ling Lo, Kar Way Tan, Feng Lin

Research Collection School Of Computing and Information Systems

This study explores the integration of a Large Language Model (LLM) based chatbot, PromptTutor, into flipped classrooms (FC) for undergraduate Computer Science (CS) education. PromptTutor is designed to provide personalized, immediate feedback to support student learning in FC by incorporating reflective learning and scaffolding strategies. The traditional FC typically lacks this immediate feedback during the pre-class learning phase, risking decreased student motivation according to existing literature. This study examines if students improve in learning outcomes and motivation after using PromptTutor. Through a controlled crossover experiment with 50 students, the study demonstrates statistically significant improvements in students' quiz performance and motivation …

An On-The-Fly Synthesis Framework For Ltl Over Finite Traces, Shengping Xiao, Yongkang Li, Shufang Zhu, Jun Sun, Jianwen Li, Geguang Pu, Moshe Vardi

Research Collection School Of Computing and Information Systems

We present an on-the-fly synthesis framework for Linear Temporal Logic over finite traces (LTLf) based on top-down deterministic automata construction. Existing approaches rely on constructing a complete Deterministic Finite Automaton (DFA) corresponding to the LTLf specification, a process with doubly exponential complexity relative to formula size in the worst case. In this case, the synthesis cannot be conducted until the entire DFA is constructed. This inefficiency is the main bottleneck of existing approaches. To address this challenge, we first present a method for converting LTLf into Transition-based DFA (TDFA) by directly leveraging LTLf semantics, incorporating intermediate results as direct components …

Instruct2see: Learning To Remove Any Obstructions Across Distributions, Junhang Li, Yu Guo, Chuhua Xian, Shengfeng He

Research Collection School Of Computing and Information Systems

Images are often obstructed by various obstacles due to capture limitations, hindering the observation of objects of interest. Most existing methods address occlusions from specific elements like fences or raindrops, but are constrained by the wide range of real-world obstructions, making comprehensive data collection impractical. To overcome these challenges, we propose Instruct2See, a novel zero-shot framework capable of handling both seen and unseen obstacles. The core idea of our approach is to unify obstruction removal by treating it as a soft-hard mask restoration problem, where any obstruction can be represented using multi-modal prompts, such as visual semantics and textual instructions, …

Action Dubber: Timing Audible Actions Via Inflectional Flow, Wenlong Wan, Weiying Zheng, Tianyi Xiang, Guiqing Li, Shengfeng He

Research Collection School Of Computing and Information Systems

We introduce the task of Audible Action Temporal Localization, which aims to identify the spatiotemporal coordinates of audible movements. Unlike conventional tasks such as action recognition and temporal action localization, which broadly analyze video content, our task focuses on the distinct kinematic dynamics of audible actions. It is based on the premise that key actions are driven by inflectional movements; for example, collisions that produce sound often involve abrupt changes in motion. To capture this, we propose T A2Net, a novel architecture that estimates inflectional flow using the second derivative of motion to determine collision timings without relying on audio …

Unambiguous Granularity Distillation For Asymmetric Image Retrieval, Hongrui Zhang, Yi Xie, Haoquan Zhang, Cheng Xu, Xuandi Luo, Donglei Chen, Xuemiao Xu, Huaidong Zhang, Pheng Ann Heng, Shengfeng He

Research Collection School Of Computing and Information Systems

Previous asymmetric image retrieval methods based on knowledge distillation have primarily focused on aligning the global features of two networks to transfer global semantic information from the gallery network to the query network. However, these methods often fail to effectively transfer local semantic information, limiting the fine-grained alignment of feature representation spaces between the two networks. To overcome this limitation, we propose a novel approach called Layered-Granularity Localized Distillation (GranDist). GranDist constructs layered feature representations that balance the richness of contextual information with the granularity of local features. As we progress through the layers, the contextual information becomes more detailed, …

Shield: Multi-Task Multi-Distribution Vehicle Routing Solver With Sparsity And Hierarchy, Yong Liang Goh, Zhiguang Cao, Yining Ma, Jianan Zhou, Mohammed Haroon Dupty, Wee Sun Lee

Research Collection School Of Computing and Information Systems

Recent advances toward foundation models for routing problems have shown great potential of a unified deep model for various VRP variants. However, they overlook the complex real-world customer distributions. In this work, we advance the Multi-Task VRP (MTVRP) setting to the more realistic yet challenging Multi-Task Multi-Distribution VRP (MTMDVRP) setting, and introduce SHIELD, a novel model that leverages both sparsity and hierarchy principles. Building on a deeper decoder architecture, we first incorporate the Mixture-of-Depths (MoD) technique to enforce sparsity. This improves both efficiency and generalization by allowing the model to dynamically select nodes to use or skip each decoder layer, …

Ts-Diff: Two-Stage Diffusion Model For Low-Light Raw Image Enhancement, Yi Li, Zhiyuan Zhang, Jiangnan Xia, Jianghan Cheng, Qilong Wu, Junwei Li

Research Collection School Of Computing and Information Systems

This paper presents a novel Two-Stage Diffusion Model (TS-Diff) for enhancing extremely low-light RAW images. In the pre-training stage, TS-Diff synthesizes noisy images by constructing multiple virtual cameras based on a noise space. Camera Feature Integration (CFI) modules are then designed to enable the model to learn generalizable features across diverse virtual cameras. During the aligning stage, CFIs are averaged to create a target-specific CFIT, which is fine-tuned using a small amount of real RAW data to adapt to the noise characteristics of specific cameras. A structural reparameterization technique further simplifies CFIT for efficient deployment. To address color shifts during …

Simulating Before Planning: Constructing Intrinsic User World Model For User-Tailored Dialogue Policy Planning, Tao He, Lizi Liao, Ming Liu, Bing Qin

Research Collection School Of Computing and Information Systems

Recent advancements in dialogue policy planning have focused on optimizing system agent policies to achieve predefined goals, emphasizing strategy design, trajectory acquisition, and training efficiency. However, these approaches often overlook the critical role of user characteristics, which are essential in real-world scenarios like conversational search and recommendation, where interactions must adapt to individual user traits such as personality, preferences, and goals. To address this gap, we conduct a comprehensive study using task-specific user personas to evaluate dialogue policy planning under diverse user behaviors. Our analysis, based on these user profiles, reveals significant shortcomings in existing approaches, underscoring the necessity for …

Generalization Analysis For Supervised Contrastive Representation Learning Under Non‑Iid Settings, Minh Hieu Nong, Antoine Ledent

Research Collection School Of Computing and Information Systems

Contrastive Representation Learning (CRL) has achieved impressive success in various domains in recent years. Nevertheless, the theoretical understanding of the generalization behavior of CRL has remained limited. Moreover, to the best of our knowledge, the current literature only analyzes generalization bounds under the assumption that the data tuples used for contrastive learning are independently and identically distributed. However, in practice, we are often limited to a fixed pool of reusable labeled data points, making it inevitable to recycle data across tuples to create sufficiently large datasets. Therefore, the tuple-wise independence condition imposed by previous works is invalidated. In this paper, …

Grokformer: Graph Fourier Kolmogorov‑Arnold Transformers, Guoguo Ai, Guansong Pang, Hezhe Qiao, Yuan Gao, Hui Yan

Research Collection School Of Computing and Information Systems

Graph Transformers (GTs) have demonstrated remarkable performance in graph representation learning over popular graph neural networks (GNNs). However, self-attention, the core module of GTs, preserves only low-frequency signals in graph features, leading to ineffectiveness in capturing other important signals like high-frequency ones. Some recent GT models help alleviate this issue, but their flexibility and expressiveness are still limited since the filters they learn are fixed on predefined graph spectrum or spectral order. To tackle this challenge, we propose a Graph Fourier Kolmogorov-Arnold Transformer (GrokFormer), a novel GT model that learns highly expressive spectral filters with adaptive graph spectrum and spectral …

Cracking Aegis: An Adversarial Llm-Based Game For Raising Awareness Of Vulnerabilities In Privacy Protection, Jiaying Fu, Yiyang Lu, Zehua Yang, Fiona Fui-Hoon Nah, Ray Lc

Research Collection School Of Computing and Information Systems

Traditional methods for raising awareness of privacy protection often fail to engage users or provide hands-on insights into how privacy vulnerabilities are exploited. To address this, we incorporate an adversarial mechanic in the design of the dialogue-based serious game Cracking Aegis. Leveraging LLMs to simulate natural interactions, the game challenges players to impersonate characters and extract sensitive information from an AI agent, Aegis. A user study (n=22) revealed that players employed diverse deceptive linguistic strategies, including storytelling and emotional rapport, to manipulate Aegis. After playing, players reported connecting in-game scenarios with real-world privacy vulnerabilities, such as phishing and impersonation, and …

Exploring The Capabilities Of Llms For Code-Change-Related Tasks, Lishui Fan, Jiakun Liu, Zhongxin Liu, David Lo, Xin Xia, Shanping Li

Research Collection School Of Computing and Information Systems

Developers deal with code-change-related tasks daily, e.g., reviewing code. Pre-trained code and code-change-oriented models have been adapted to help developers with such tasks. Recently, large language models (LLMs) have shown their effectiveness in code-related tasks. However, existing LLMs for code focus on general code syntax and semantics rather than the differences between two code versions. Thus, it is an open question how LLMs perform on code-change-related tasks.To answer this question, we conduct an empirical study using 1B parameters LLMs on three code-change-related tasks, i.e., code review generation, commit message generation, and just-in-time comment update, with in-context learning (ICL) and parameter-efficient …

Sleep Variability And Time To Achieving Pregnancy: Findings From A Pilot Cohort Study Of Women Desiring Pregnancy, Peinan Zhao, Emily S Jungheim, Bronwyn S Bedrick, Leping Wan, Patricia T Jimenez, Ronald Mccarthy, Jessica Chubiz, Justin C Fay, Erik D Herzog, Siobhan Sutcliffe, Sarah K England

2020-Current year OA Pubs

OBJECTIVE: To determine whether chronodisruption is associated with achieving pregnancy.

DESIGN: Pilot prospective cohort study.

SETTING: Academic Medical Center.

SUBJECTS: One hundred eighty-three women desiring pregnancy were recruited from the local community of an academic medical center located in the Midwest and provided sleep information between February 1, 2015, and November 30, 2017.

EXPOSURE: Sleep and activity data were obtained via actigraphy watches worn continuously for 2 weeks to assess measures of chronodisruption, including sleep period onset, offset, midtime, and duration; as well as variability in each of these measures.

MAIN OUTCOME MEASURES: Time to becoming pregnant over 1-year of …

Diversity Optimization For Travelling Salesman Problem Via Deep Reinforcement Learning, Qi Li, Zhiguang Cao, Yining Ma, Yaoxin Wu, Yue-Jiao Gong

Research Collection School Of Computing and Information Systems

Existing neural methods for the Travelling Salesman Problem (TSP) mostly aim at finding a single optimal solution. To discover diverse yet high-quality solutions for Multi-Solution TSP (MSTSP), we propose a novel deep reinforcement learning based neural solver, which is primarily featured by an encoder-decoder structured policy. Concretely, on the one hand, a Relativization Filter (RF) is designed to enhance the robustness of the encoder to affine transformations of the instances, so as to potentially improve the quality of the found solutions. On the other hand, a Multi-Attentive Adaptive Active Search (MA3S) is tailored to allow the decoders to strike a …

Wild Hogs In The Water: Contested Infrastructural Ecologies Of Reservoir Storage In Texas, Sayd Randle

Research Collection College of Integrative Studies

Reservoirs are developed to store water in reserve for future use. But once built, reservoir sites inevitably hold more than just water, often serving as a key habitat for a range of species. This paper examines how one such animal has transformed water storage facilities and nearby landscapes into contested ground in urbanising areas of Texas, USA. Living around the reservoirs, feral hogs complicate the process of urbanisation by degrading the stockpiled water and infrastructure at the storage sites themselves and by damaging private property throughout the surrounding landscape. Tracking local efforts to manage the hogs, the case study illustrates …

The Miseducation Of Model Minorities: The Gospel Of ‘Schoolvation’ And The Myth Of The Schooled Society, Justin Kh Tse

Research Collection College of Integrative Studies

The ‘model minority’, the phenomenon of some ‘minority’ communities (or some members within them) achieving social and economic advancement despite encountering the difficulties of assimilating into a mainstream society, is often described as a myth, especially as one of the central problematics in Asian American studies. Usually, the modern use of the word myth is pejorative: the model minority in this sense refers to a false empirical description of some minorities and should be quantitatively disaggregated and qualitatively debunked. In this article, I want to explore the model minority as another kind of myth, in the classical sense of mythos, …

A New City For A New Era: Xiong'an As Showcase Of China's Evolving Urban Ideology, Andrew Stokols

Research Collection College of Integrative Studies

Cities have long been expressions of political ideology in China and elsewhere. During China’s rapid urbanization over the past few decades, “new areas” became popular strategies to promote urban growth, following the success of Shenzhen, widely regarded as China’s first special economic zone. Today under Xi, Xiong’an New Area has become the latest “new area of national significance.” But unlike previous new areas in China, Xiong’an has become wedded to a distinct vision of the urban in Xi Jinping’s China, one in which the excesses of reform-era urbanization are controlled through new forms of affordable housing and finance, new ecological …

Network And Tree-Based Approaches To Data-Driven Modeling Of Complex Climate Systems, Adam M. Giammarese

Theses

The guiding thread throughout this thesis work is data-driven modeling of Earth's climate. We investigate a variety of settings within the field of complex climate systems, such as gridded, high-resolution reanalysis data, lower-resolution climate indices, and incomplete paleoclimate records with missing values. We begin with reanalysis data of high spatial and temporal resolution, and use climate network analysis to uncover hidden trends in the data in regards to the Amazon rainforest and its changing role in the global climate system. We introduce a novel formulation of k-nearest neighbors climate networks to study changing trends at a local level, and apply …

Consumer Behavior Of Gen Z In Kosovo: Purchasing Preferences And Brand Engagement, Sara Dumani

Theses

This capstone project examines the consumer behavior of Generation Z in Kosovo by analyzing their purchasing preferences and brand engagement. The Generation Z demographic, which includes individuals born between 1996 and 2010, is the focus of this study. This generation is characterized by digital savviness and a significant influence from social media platforms, shaping their purchasing decisions and brand engagement. Generation Z’s behavior is often marked by a preference for online shopping, collaborative marketing approaches, and sustainability, making it essential to understand these factors in the context of Kosovo. The data for analyzing Generation Z’s consumer behavior were collected through …

Utilizing Natural Language Processing To Optimize Business Processes, Olt Kondirolli

Theses

This Capstone project explores the potential of Natural Language Processing (NLP) techniques in optimizing decision-making and organizational workflows across various domains. The Capstone project uses three case studies to demonstrate how sentiment analysis, frequency analysis, and topic modeling can analyze unstructured textual data to provide insightful findings. The first case study evaluates employee satisfaction using sentiment analysis, uncovering trends across departments and roles to guide targeted organizational interventions. The second case study focuses on student feedback at a higher education institution, using sentiment and frequency analyses to identify key areas for improvement in academic programs and services. The third case …

The Transition Of The Ict Sector In Kosovo From Service-Based Companies To Product-Based Companies, Erinda Elezaj

Theses

The capstone project will discuss the barriers and opportunities of the ICT sector of Kosovo to shift its business models into the product-based models, with an emphasis on the economic, social, and cultural determinants of the shift. ICT sector in Kosovo has been dominated long by outsourcing and service provision, yet the world trends and local ambitions require a shift towards innovation-based scalable product models that would create sustainable growth and competitiveness. The study is of qualitative nature and it takes the form of semi-structured interviews with 13 main stakeholders representing government, industry, education and cultural sectors. These interviews provide …

Exploring Kosovo's Need For A Technology-Driven Offset Strategy, Alba Cikaqi

Theses

At a time where technological innovation is redefining national security, Kosovo risks falling behind by failing to adopt emerging technologies for defense and security. This research addresses that vulnerability by exploring the need for a dedicated national strategy as a solution. Drawing on global best practices, including the United States Offset Strategy, NATO frameworks, and innovation models from the Baltic countries, the study outlines a potential path forward. Additionally, through qualitative analysis, including interviews with key stakeholders across public, private, and academic sectors, this study looks into the opportunities and challenges of developing a context-specific strategy for integrating emerging technologies …