Digital Commons Network^™

A Student’S Confidence And A Teacher’S Practice: Reflecting On Parallel Writing Journeys In A Theatre-Making Classroom In South Africa, Néka Da Costa

GHEA21 Publications

No abstract provided.

Slowing The Academic Treadmill: Writing, Reflection, And Resistance In The Neoliberal University, Birsha Ohdedar

GHEA21 Publications

No abstract provided.

Highly Confident But Slightly Uncertain: A Long Overdue Reinvention Of The School Scientific Method, Uncertainty And Error - Volume 3, Stephen Demeo

Publications and Research

Volume 3 explores the essential roles of uncertainty and error in scientific experimentation. It distinguishes between scientific error and scientific uncertainty: Scientific error refers to the difference between an experimental value and an accepted literature value, as well as the difference between data points in an x-y scatter plot and a predicted trendline. Scientific uncertainty, on the other hand, is associated with doubt arising from instrument limitations, variability within a data set, and psychological factors. Human error is set apart as mistakes or blunders, not to be conflated with scientific error.

Of utmost importance to the scientific investigator is the …

Impartial Intelligence? Evidence Of Country-Label Sensitivity In Ai Financial Analysis, Fabio Motoki, Jedson Pinto

School of Accountancy Faculty Publications

This study examines whether large language models exhibit systematic country-contingent differential treatment in financial fraud detection. Analyzing 30,000 synthetic transactions with identical statistical properties across three country attributions (United States, Great Britain, and China), we find LLMs assign significantly higher fraud probabilities to Chinese-attributed transactions (36.2%) compared to Western countries (≈30–31%), resulting in accuracy disparities of 67% versus 74%. The gap remains stable across five independent experimental replications and persists when using Chinese language prompts, ruling out linguistic effects. Bias mitigation strategies, such as requiring explanations or explicit country neutrality instructions, reduce but fail to eliminate these disparities. Testing across …

Diversity And Inclusivity In Australian Dementia Prevention Research: A Mixed Methods Review, Olivia E. Giameos, Maddison L. Mellow, Diana Karamacoska, Aaron Davis, Paul A. Gardiner, Eddy Roccati, Kaarin J. Anstey, Nicolas Cherbuin, Jessica M. Adsett, Nikki Anne Wilson, Kylie Radford, Louise Lavrencic, Perminder S. Sachdev, Simone Reppermund, Suraj Samtani, Annabel P. Matison, Zara A. Page, Philip J. Batterham, Sophie C. Andrews, Alex Bahar-Fuchs, Michelle K. Lupton, Andrew Pipingas, Adrienne Withall, Belinda M. Brown, Helen Macpherson, Hannah A.D. Keage, Britt Burton, James C. Vickers, David W. Dunstan, Ashleigh E. Smith

Research outputs 2022 to 2026

Minoritized communities are disproportionately impacted by modifiable dementia risk factors but are underrepresented in dementia research globally. In Australia, the number of dementia prevention cohort and intervention studies has rapidly increased in the past two decades, yet the representation of minoritized groups has not been synthesized. The aims of this mixed-methods review were to summarize the demographic characteristics of participants involved in Australian dementia prevention-focused cohort and intervention studies. A systematic search of published literature, funded grant outcomes, and clinical trial registrations was conducted in October 2023 and updated in February 2025 to identify any Australia-based cohort or intervention studies …

Rhetorical Physics And The Laws Of Language: A Comparative Analysis Of President Trump And President Macron At The United Nations 2025, David Edmund Allen

Research outputs 2022 to 2026

The paper features a textual analysis of the UN speeches made by the US President Donald Trump and by France’s President Macron. President Trump’s speech was made in the absence of a teleprompter and lasted almost an hour. President Macron’s speech was representative of a more standard diplomatic speech. Both speeches are analyzed using a variety of models and techniques. The analysis incorporates an exploration of Manin’s link of Zipf’s law to concepts from information theory and algorithmic complexity, Tao’s concepts applied to power laws, ‘E pluribus unum’, out of many, one, plus a completely new application of Villermaux’s universal …

Alumni Voices. Beyond Graduation: The Lifelong Global Impact Of A Uk Education, Sladana Krstic, Alexander Towne

Higher education research

The third round of the British Council Alumni Voices survey provides robust and timely evidence of the enduring value of a UK higher education experience. Drawing on three years of longitudinal survey data, supplemented by a number of interviews, the findings highlight how UK education continues to deliver skills, support professional progression, and foster long lasting international networks that extend well beyond graduation and national borders. Nearly three quarters of respondents report that in the last 12 months they have maintained contact with people they first met during their UK studies, and almost 84 percent have recommended a UK study …

Veribrief: A Multi-Agent Retrieval-Augmented Generation System For Policy Decision Support, Imane Bahji

Electrical and Computer Engineering ETDs

VeriBrief is a multi-agent retrieval-augmented generation (RAG) system for evidence-grounded economic policy analysis. The system orchestrates a five-stage LangGraph pipeline, retrieval, research, analysis, synthesis, and critique, to produce cited, structured responses while detecting out-of-scope queries. An empirical evaluation on eight questions drawn from official U.S. macroeconomic releases compared VeriBrief against a single-pass RAG baseline. The multi-agent system achieved 100% refusal precision on unanswerable analytical queries versus 0% for the baseline. Unsupported claims fell substantially on answerable factual questions. A context-propagation defect discovered during evaluation was diagnosed and corrected. Limitations include failure of the evidence gate on policy-counterfactual queries and a …

The Anatomy Of Earnings Conference Calls: An Integrative Framework For Management Research, Matthew P. Mount, Gokhan Ertug, Wei Shi, Tengjian Zou

Research Collection Lee Kong Chian School Of Business

Over the last decade, there has been an explosion in the use of diverse data sources by management scholars to observe and capture managerial and organizational constructs that have historically been difficult to access. This surge has been driven by the growing availability of rich, multi-modal data—textual, image, and audio (Luo, Jia, Ouyang, & Fang, 2024)—together with advances in analytical techniques to process and analyze data, such as computer-aided text analysis (Harrison, Thurgood, Boivie, & Pfarrer, 2019), machine learning (Choudhury, Wang, Carlson, & Khanna, 2019; Harrison, Josefy, Kalm, & Krause, 2023), and deep learning (Gouvard, Goldberg, & Srivastava, 2023). These …

Knowledge-State Generative Agents For Pre-Assessment Question Evaluation, Ping Fan Ke, Yi Meng Lau, Siaw Ling Lo

Research Collection School Of Computing and Information Systems

This paper introduces a Knowledge‑State Generative Agent framework for evaluating the quality of pre‑assessment questions. The framework employs large language model (LLM)–based agents prompted to adopt a teacher persona to simulate the responses of students with and without mastery of targeted knowledge components. A preliminary empirical study using archival data from 424 students enrolled in an Information Systems Management course indicates that the proposed approach yields interpretable metrics under Classical Test Theory. Results further show that agents instantiated with the relevant mastered knowledge components exhibit systematically higher performance than agents lacking such mastery. In addition, the study suggests that teacher-persona …

Dual-Diffusional Generative Fashion Recommendation, Mingzhe Yu, Lei Wu, Qianru Sun, Yunshan Ma

Research Collection School Of Computing and Information Systems

Personalized generative recommender systems have emerged as a promising solution for fashion recommendation. However, existing methods primarily rely on implicit visual embeddings from historical interactions, which often contain preference-irrelevant information and result in insufficient user behavior modeling. Moreover, these models typically generate only item images, providing limited interpretability. To address these limitations, we propose DualFashion, a Dual-Diffusional Generative Fashion Recommendation Architecture that jointly models image and text modalities for personalized and explainable recommendation. DualFashion adopts a dual-diffusion Transformer with image and text branches, where structured attribute-level captions and visual outfit information are jointly used as conditioning signals to model user …

Scattered Hypothesis Generation For Open-Ended Event Forecasting, He Chang, Zhulin Tao, Lifang Yang, Xianglin Huang, Yunshan Ma

Research Collection School Of Computing and Information Systems

Despite the importance of open-ended event forecasting for risk management, current LLM-based methods predominantly target only the most probable outcomes, neglecting the intrinsic uncertainty of real-world events. To bridge this gap, we advance open-ended event forecasting from pinpoint forecasting to scatter forecasting by introducing the proxy task of hypothesis generation. This paradigm aims to generate an inclusive and diverse set of hypotheses that broadly cover the space of plausible future events. To this end, we propose SCATTER, a reinforcement learning framework that jointly optimizes inclusiveness and diversity of the hypothesis. Specifically, we design a novel hybrid reward that consists of …

Mab-Dqa: Addressing Query Aspect Importance In Document Question Answering With Multi-Armed Bandits, Yixin Xiang, Yunshan Ma, Xiaoyu Du, Yibing Chen, Yanxin Zhang, Jinhui Tang

Research Collection School Of Computing and Information Systems

Document Question Answering (DQA) involves generating answers from a document based on a user’s query, representing a key task in document understanding. This task requires interpreting visual layouts, which has prompted recent studies to adopt multimodal Retrieval-Augmented Generation (RAG) that processes page images for answer generation. However, in multimodal RAG, visual DQA struggles to utilize a large number of images effectively, as the retrieval stage often retains only a few candidate pages (e.g., Top-4), causing informative but less visually salient content to be overlooked in favor of common yet low-information pages. To address this issue, we propose a Multi-Armed Bandit–based …

The Narrative Dynamics Of Special Books By Special Kids Youtube Videos And Comments: A Study Of Disability Rhetoric And Public Narrative Engagement, Jessica Louise Allee

Graduate Theses and Dissertations

Digital media has expanded disability advocacy and community building by enabling accessible, visual storytelling and connection. Special Books by Special Kids (SBSK), a YouTube channel using interview-based disability storytelling, foregrounds people’s experiences with disabilities in the videos, while inviting viewers to interpret, identify with, and respond in the comments. As a participatory storytelling space, SBSK offers a site for examining how disability meanings are constructed, negotiated, and transformed through narratives, multimodal practices, and audience uptake, while revealing how dominant disability rhetoric or ableist discourse that positions people with disabilities as burdens, inherently deficient, or socially devalued, can be reproduced, complicated, …

Purifai: Detecting And Fixing Search-Induced Distortions In Web-Augmented Llms, Guoqing Wang, Zhao Zhang, Zeyu Sun, Xiaofei Xie, Yizhou Chen, Yanchao Tan, Dan Hao

Research Collection School Of Computing and Information Systems

As Large Language Models (LLMs) increasingly serve as interfaces for proprietary data (e.g., enterprise knowledge bases, legal statutes), ensuring their fidelity to trusted internal information is paramount. While integrating real-time web search can enhance model utility, it introduces a critical vulnerability: the ingestion of conflicting, misleading, or hallucinated content from the open web can override the model's adherence to its verified internal knowledge. We define this failure mode as search-induced distortion, a significant risk in high-stakes domains where the internal knowledge base serves as the absolute ground truth.To address this challenge, we present PurifAI, a proactive, model-agnostic, cache-level purification system …

Verbalizing Lightgcn: Direct Learning Of Textual Representations From User-Item Interaction Graph Via Llms, Manh-Khanh Ngo Huu, Hady Wirawan Lauw

Research Collection School Of Computing and Information Systems

In this work, we propose VerbaLightGCN, a novel LLM-based recommendation framework that integrates the semantic understanding of LLMs with user-item interaction modeling. Traditional collaborative filtering (CF) models typically embed user and item IDs into a latent space to capture interaction signals. However, pretrained LLMs cannot natively interpret these learned embeddings. To bridge this gap, VerbaLightGCN adopts a CF-as-text paradigm, in which collaborative signals are encoded in textual form and directly learned from the user–item interaction graph, and are then combined with semantic information to construct user and item profiles that function as latent embeddings. Inspired by LightGCN, our method retains …

Generation-Augmented Video Corpus Moment Retrieval, Mingjin Kuai, Qianyin Xiao, Juncheng Li, Jin Peng, Lizi Liao, Wei Ji

Research Collection School Of Computing and Information Systems

Video Corpus Moment Retrieval (VCMR) requires models to efficiently retrieve and precisely locate specific moments relevant to natural language queries within a massive, untrimmed video corpus. However, existing discriminative approaches typically rely on shallow visual-textual feature matching mechanisms, which often struggle to capture fine-grained semantic differences. To address this limitation, we propose Video-GAR, a novel framework that reframes the conventional retrieval task from superficial matching to generative understanding, positing that the capability for query reconstruction evidences deep semantic comprehension. Specifically, Video-GAR orchestrates three synergistic components: To overcome the computational efficiency bottleneck, we construct a Bi-Mamba backbone that leverages the linear …

Do I Fit In Here? How Immigrants’ Endorsement Of Social Markers Is Related To Their Wellbeing In Three Migrant Receiving Societies, Justine Dandy, Chan Hoong Leong, Adam Komisarof, Travis Lim, Krystal Perkins

Research outputs 2022 to 2026

Social markers of acceptance are the attributes seen as important for immigrants to achieve or display in order to be accepted similarly to a local-born citizen. In research on constructions of national identity, factor analysis reveals a culture-specific, two-factor structure akin to the ethnic–civic distinction observed. In this paper, we extend this work by examining the relationship between social markers of acceptance and immigrants’ well-being in three national contexts: Australia, Japan, and the U.S. Specifically, in study 1 we examined the factor structure of social markers in non-immigrant samples in each context (Australia, n = 1357; Japan, n = 2000; …

Variational Speculative Decoding: Rethinking Draft Training From Token Likelihood To Sequence Acceptance, Xiandong Zou, Jianshu Li, Jing Huang, Pan Zhou

Research Collection School Of Computing and Information Systems

Speculative decoding accelerates inference for (M)LLMs, yet a training-decoding discrepancy persists: while existing methods optimize single greedy trajectories, decoding involves verifying and ranking multiple sampled draft paths. We propose Variational Speculative Decoding (VSD), formulating draft training as variational inference over latent proposals (draft paths). VSD maximizes the marginal probability of target-model acceptance, yielding an ELBO that promotes high-quality latent proposals while minimizing divergence from the target distribution. To enhance quality and reduce variance, we incorporate a path-level utility and optimize via an Expectation-Maximization procedure. The E-step draws MCMC samples from an oracle-filtered posterior, while the M-step maximizes weighted likelihood using …

Train In Vain: Functionality-Preserving Poisoning To Prevent Unauthorized Use Of Code Datasets, Yuan Xiao, Yuchen Chen, Jiaming Wang, Wei Song, Jun Sun, Shiqing Ma, Yanzhou Mu, Juan Zhai, Chunrong Fang, Jin Song Dong, Zhenyu Chen

Research Collection School Of Computing and Information Systems

The widespread availability of large-scale code datasets has accelerated the development of code large language models (CodeLLMs), raising concerns about unauthorized dataset usage. Dataset poisoning offers a proactive defense by reducing the utility of such unauthorized training. However, existing poisoning methods often require full-dataset poisoning and introduce transformations that break code compilability. In this paper, we introduce FunPoison, a functionality-preserving poisoning approach that injects short, compilable weak-use fragments into executed code paths. FunPoison leverages reusable statement-level templates with automatic repair and conservative safety checking to ensure side-effect freedom, while a type-aware synthesis module preserves type correctness, suppresses static-analysis warnings, and …

Itimo: An Llm-Empowered Synthesis Dataset For Travel Itinerary Modification, Zhuoxuan Huang, Yunshan Ma, Hongyu Zhang, Hua Ma, Zhu Sun

Research Collection School Of Computing and Information Systems

Addressing itinerary modification is crucial for enhancing the travel experience as it is a frequent requirement during traveling. However, existing research mainly focuses on fixed itinerary planning, leaving modification underexplored due to the scarcity of shape need-to-modify itinerary data. To bridge this gap, we formally define the itinerary modification task and propose a general pipeline to construct the corresponding dataset, namely iTIMO. This pipeline frames the generation of shape need-to-modify itinerary data as an intent-driven perturbation task. It instructs large language models to perturb real-world itineraries using three operations: REPLACE, ADD, and DELETE. Each perturbation is grounded in three intents: …

Universal Rules Of The Russian Sound Verbs’ Synthesis: Representation In A Matrix Of Forms, Irina V. Ivliyeva

Arts, Languages and Philosophy Faculty Research & Creative Works

English Abstract:

The article is devoted to the construction of a system of universal rules for the synthesis of modified verbs of the Russian language and ways of presenting them in a matrix table of forms. The aim of the study is to identify parameters of the sound process relevant for predicting the composition of modified sound verbs’ nests, and in developing a system of rules of word-formation synthesis. The research material consisted of 152 base verbs of sound in the Russian language and their 880 modified derivatives.

Methods of lexical-semantic, word-formation (WF) and component analysis are used in the …

The Use Of Assisted Repeated Reading To Increase Fluency And Comprehension Among Adolescent English Language Learners, Matthew J. Wentzell

School of Education and Leadership Student Capstone Theses and Dissertations

Wentzell, M. (2026). The Use of Assisted Repeated Reading to Increase Fluency and Comprehension Among Adolescent English Language Learners

The purpose of this study was to examine the impact of audio-assisted repeated reading on fluency and comprehension among adolescent English learners and gauge their opinions on the intervention and its impact on their reading ability. Areas of exploration within the literature review included the evolution of fluency research, the relationship between fluency, prosody, and comprehension, and fluency within the context of English learners. Additionally, the literature review encompassed the strategy of repeated reading with and without audio-assistance and its …

The Limits Of Disclosure: Artificial Intelligence, Arbitration, And The Illusion Of Informed Consent, Rishi Batra

Journal of Dispute Resolution

Consider the following scenario: A warehouse worker brings a wage and hour claim against her employer under her state's labor code. Her employment contract, which she signed on her first day of work, contains a mandatory arbitration clause that she did not negotiate, did not fully read, and — like most employees in her situation — did not fully understand. An arbitrator is appointed, a hearing is held, and an award is issued in the employer's favor several weeks later, denying the employee's claims entirely. The award is well-organized and internally consistent, addressing each of the worker's claims with what …

A Decade Of Change: Technology’S Impact On Negotiation Deepens In The Age Of Ai, Noam Ebner

Journal of Dispute Resolution

When people consider the notion of negotiation changing, they tend to look first toward that magnificent negotiation construct, “the table.” Here are some immediately apparent areas of table-novelty: • There is often a screen on our table, rather than another person sitting across from us. • The table we “go” to negotiate at is not in our office or that of our counterpart; rather, it is a communications system such as email or an online platform developed by a third-party provider. • The table, in its online-platform form, sometimes structures process and facilitates communication in ways that our trusty old …

Mirror, Mirror On My Screen, Can You Feel Like A Human Being?, Lauren A. Newell

Journal of Dispute Resolution

We cannot go anywhere without encountering artificial intelligence (AI) these days. AI has infiltrated our phones, our cars, and our washing machines. It is with us in doctors’ offices, at the drive-through, and at sporting events. It has taken over our calendars and our inboxes and our videoconferences, and it would like to help us brush our teeth, too.

Evaluating Special Education Teachers’ Competence In Inclusive Education: A Study Of Behavior Management, Level Of Confidence, And Training Needs, Kourtney Guthrie

Electronic Theses and Dissertations

The purpose of this mixed-methods study is to examine the competence of special education teachers in rural East Texas, focusing on their experiences, perceptions, and professional development needs related to behavior management and inclusive education. Quantitative data were gathered through questionnaires given to special education teachers and elaborated upon through focus group interviews, where themes emerged. An explanatory sequential mixed-methods design was used to develop a better understanding of teachers’ preparedness and the problems involved in the implementation of inclusive practices. The findings may inform more effective teacher training, policy-making, and support systems in rural educational settings by highlighting professional …

Can Ai-Generated Ads With Future Predictions Drive Higher Donations Than Human-Created Ads?, Chaewon Song, Sujin Song

Asia Marketing Journal

The use of AI in generating ads offers benefits for NPOs, such as enhanced cost efficiency and personalized content. However, consumers often exhibit algorithm aversion when AI performs subjective tasks, like ad creation. According to mind perception theory, AI is seen as high in agency but low in experience. Given this, we hypothesized that including future predictions in AI-generated ads would mitigate this aversion. Across four studies, we found that AI-generated donation ads were generally perceived as less credible and elicited lower donation intentions than human-created ones. Crucially, when future predictions were included, the credibility and donation gap between AI …

From Emotions To Impulse: A Serial Mediation Approach In Tiktok Live Commerce, Amrul Asraf Mohd-Any, Moniruzzaman Sarker, Shaoxuan Lu

Asia Marketing Journal

Based on social exchange theory, this study investigates how interactions between influencers and followers during live streaming impact impulse buying behaviour. It explores how perceived influencer traits, namely authenticity, expertise, attractiveness, and homophily, influence trust, emotional attachment, and para-social interaction, which in turn drive impulsive purchases. Using PLS-SEM technique, a survey of 303 Chinese TikTok users reveals that emotional factors, particularly para-social interaction and attachment, have a stronger effect on impulse buying than trust. Authenticity and homophily emerge as essential in fostering emotional engagement, emphasising the importance of relatability over authority. The findings suggest that successful influencer marketing in live …

Inspiring Multilingual Children To Explore The Natural World Using Nature-Based Literature, Jennifer Hill, Deborah Wheeler

Journal of English Learner Education

Nature-based learning has become more popular in the United States since COVID-19, and incorporating nature-based learning including books about the natural world aligns with children’s natural curiosity, and desire to actively explore through play. Indeed, nature-based learning has many benefits ranging from supporting child development, promoting social-emotional well-being, and creating an inclusive learning environment for multilingual students. Reading nature-based literature and providing access to nature-based literature is a holistic methodology teachers should include in their classroom. This paper highlights the benefits of nature-based learning and provides a variety of topics and resources teacher can utilize.