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The Impact Of Alexithymia On Body Image: The Mediating Role Of Rumination Among Students At Sultan Qaboos University, Fatima Alrahbi, Mai Helmy, Amal Alhadabi Jul 2026

The Impact Of Alexithymia On Body Image: The Mediating Role Of Rumination Among Students At Sultan Qaboos University, Fatima Alrahbi, Mai Helmy, Amal Alhadabi

Journal of Educational and Psychological Studies

The study aimed to examine the mediating role of rumination in the relationship between the dimensions of alexithymia and body image among first-year students at Sultan Qaboos University in the Sultanate of Oman. The descriptive method was employed, and the sample consisted of 310 male and female first-year students at Sultan Qaboos University, who were selected using a convenience sampling method. The study instruments included three scales: the Body Image Scale, the Toronto Alexithymia Scale, and the Rumination Scale. The results indicated the presence of statistically significant direct effects of the dimensions of alexithymia on rumination. The findings showed that …

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The Effectiveness Of A Digital Game-Based Learning Environment In Developing Problem- Solving Skills Among Primary School Students, Ayda Abdulkareem Aleidan Jul 2026

The Effectiveness Of A Digital Game-Based Learning Environment In Developing Problem- Solving Skills Among Primary School Students, Ayda Abdulkareem Aleidan

Journal of Educational and Psychological Studies

The study aimed to examine the effectiveness of a digital learning environment based on educational games in developing problem-solving skills among female elementary school students. The digital environment was designed using educational game tools (ClassCraft, Kahoot!, Scratch) within interactive activities that consider learners’ characteristics and the requirements for developing problem-solving skills. The sample consisted of 64 fifth-grade students, divided into two groups: an experimental group (n = 31) that learned through the game-based digital environment, and a control group (n = 33) that learned through traditional instruction. An electronic game-based training program was implemented, along with an observation checklist to …

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The Machiavellian Personality And Its Relationship With Research Self-Efficacy Among Graduate Students, Zuhair Abdul Hamid El-Nawajha Jul 2026

The Machiavellian Personality And Its Relationship With Research Self-Efficacy Among Graduate Students, Zuhair Abdul Hamid El-Nawajha

Journal of Educational and Psychological Studies

The research aimed to identify the level of Machiavellian personality and research self-efficacy, as well as the correlation between them. It also sought to reveal the differences in Machiavellian personality and research self-efficacy according to the variables of gender and academic degree.The researcher used the descriptive correlational approach. The research sample consisted of 103 male and female graduate students, from universities in the Gaza Strip. To achieve the research objectives, the researcher used the Machiavellian Personality Scale, prepared by (Dahling et al., 2009), and developed the Research Self-Efficacy Scale.The results of the study showed that the level of Machiavellian personality …

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Mechanistic And Spatio-Temporal Modelling Of Cassava Whitefly (Bemisia Tabaci) Risk Under Climate Change: Projections For Africa With Case Evidence From Malawi, Lumbani Benedicto Banda, Frank Thomas Ndjomatchoua, Ritter A. Guimapi, Komi Mensah Agboka, Abdelmutalab G.A. Azrag, Wezi G. Mhango, Trust Kasambala Donga, Chikondi Makwiza, Karl H. Thunes, Elfatih M. Abdel-Rahman Jul 2026

Mechanistic And Spatio-Temporal Modelling Of Cassava Whitefly (Bemisia Tabaci) Risk Under Climate Change: Projections For Africa With Case Evidence From Malawi, Lumbani Benedicto Banda, Frank Thomas Ndjomatchoua, Ritter A. Guimapi, Komi Mensah Agboka, Abdelmutalab G.A. Azrag, Wezi G. Mhango, Trust Kasambala Donga, Chikondi Makwiza, Karl H. Thunes, Elfatih M. Abdel-Rahman

All Peer-Reviewed Publications

The cassava whitefly (Bemisia tabaci) greatly constrains cassava production across Africa due to its role as a vector of viral diseases that cause substantial yield losses. Effective management of this insect pest requires detailed knowledge of its spatio-temporal distribution, however long-term datasets are scarce. Mechanistic models circumvent these long-term data needs by modelling temperature-dependent processes that govern population dynamics. Nevertheless, their application to B. tabaci remains poorly explored. Here, we developed a mechanistic model to derive a risk index (RI) for B. tabaci across Africa, focusing on Malawi. The model integrates the effects of temperature on the life stages of …

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Environmental And Socioeconomic Effects Of Roundtable On Sustainable Palm Oil Certification: A Systematic Review And Meta-Analysis, Kibrom T. Sibhatu, Matin Qaim Jul 2026

Environmental And Socioeconomic Effects Of Roundtable On Sustainable Palm Oil Certification: A Systematic Review And Meta-Analysis, Kibrom T. Sibhatu, Matin Qaim

All Peer-Reviewed Publications

Palm oil is the most widely produced and consumed vegetable oil worldwide, but its production is associated with deforestation and other environmental and social problems. Roundtable on Sustainable Palm Oil (RSPO) is the only internationally-recognized voluntary certification standard aimed at mitigating such problems. Many studies examine RSPO’s effects on particular outcomes in specific contexts, but a consolidated global assessment is lacking. Here, we systematically review the literature and identify 53 original studies covering RSPO effects in various countries of Asia, Africa, and Latin America. Where data availability permits, we also conduct meta-analysis. Results reveal that RSPO can lead to environmental …

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Larger Is Not Always Better: Exploring Small Open-Source Language Models In Logging Statement Generation, Renyi Zhong, Yichen Li, Guangba Yu, Wenwei Gu, Jinxi Kuang, Yintong Huo, Michael R. Lyu Jul 2026

Larger Is Not Always Better: Exploring Small Open-Source Language Models In Logging Statement Generation, Renyi Zhong, Yichen Li, Guangba Yu, Wenwei Gu, Jinxi Kuang, Yintong Huo, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Developers use logging statements to create logs that document system behavior and aid in software maintenance. As such, high-quality logging is essential for effective maintenance; however, manual logging often leads to errors and inconsistency. Recent methods emphasize using large language models (LLMs) for automated logging statement generation, but these present privacy and resource issues, hindering their suitability for enterprise use. This paper presents the first large-scale empirical study evaluating small open-source language models (SOLMs) for automated logging statement generation. We evaluate four prominent SOLMs using various prompt strategies and parameter-efficient fine-tuning techniques, such as Low-Rank Adaptation (LoRA) and Retrieval-Augmented Generation …

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Multicbr: Multi‑View Contrastive Learning For Bundle Recommendation, Yunshan Ma, Yingzhi He, Xiang Wang, Yinwei Wei, Xiaoyu Du, Yuyangzi Fu, Tat‑Seng Chua Jul 2026

Multicbr: Multi‑View Contrastive Learning For Bundle Recommendation, Yunshan Ma, Yingzhi He, Xiang Wang, Yinwei Wei, Xiaoyu Du, Yuyangzi Fu, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Bundle recommendation seeks to recommend a bundle of related items to users to improve both userexperience and the profits of platform. Existing bundle recommendation models have progressed from capturing only user-bundle interactions to the modeling of multiple relations among users, bundles, and items.CrossCBR, in particular, incorporates cross-view contrastive learning into a two-view preference learningframework, significantly improving SOTA performance. It does, however, have two limitations: (1) the twoview formulation does not fully exploit all the heterogeneous relations among users, bundles, and items; and(2) the “early contrast and late fusion” framework is less effective in capturing user preference and difficultto generalize to …

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Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models, Chunyan Liu, Yan Lei, Huan Xie, Jinping Wang, Yue Yu, David Lo Jul 2026

Survey On Learning-Based Dynamic Fault Localization: From Traditional Machine Learning To Large Language Models, Chunyan Liu, Yan Lei, Huan Xie, Jinping Wang, Yue Yu, David Lo

Research Collection School Of Computing and Information Systems

Learning-based dynamic fault localization techniques play a crucial role in the field of software engineering. These techniques dynamically execute test cases to meticulously extract useful knowledge from the execution information in the program, with the aim of identifying fault locations by leveraging machine learning, deep learning, and large language models. Currently, there is already a flourishing body of research that is intensely focused on learning-based dynamic fault localization. Research literature can be categorized into two main aspects for learning-based dynamic fault localization: data-based enhancements (i.e., the datasets) and model-based enhancements (i.e., the suspiciousness algorithms). Thus, we conduct an extensive literature …

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Deep Learning For Video Anomaly Detection: A Review, Peng Wu, Chengyu Pan, Yuting Yan, Guansong Pang, Qingsen Yan, Peng Wang, Yanning Zhang Jul 2026

Deep Learning For Video Anomaly Detection: A Review, Peng Wu, Chengyu Pan, Yuting Yan, Guansong Pang, Qingsen Yan, Peng Wang, Yanning Zhang

Research Collection School Of Computing and Information Systems

Video anomaly detection (VAD) aims to discover behaviors or events deviating from the normality in videos. As a long-standing task in the field of computer vision, VAD has witnessed much good progress. In the era of deep learning, with the explosion of architectures of continuously growing capability and capacity, a great variety of deep learning-based methods are constantly emerging for the VAD task, greatly improving the generalization ability of detection algorithms and broadening the application scenarios. Therefore, such a multitude of methods and a large body of literature make a comprehensive survey a pressing necessity. In this article, we present …

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Anomaly Management In Unmanned Aerial Vehicles: A Systematic Literature Review, Ivan Tan Wei Han, Christopher M. Poskitt, Lingxiao Jiang, Lwin Khin Shar Jul 2026

Anomaly Management In Unmanned Aerial Vehicles: A Systematic Literature Review, Ivan Tan Wei Han, Christopher M. Poskitt, Lingxiao Jiang, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Unmanned Aerial Vehicles (UAVs) are increasingly deployed in safety-critical applications such as logistics, surveillance, disaster response, and urban air mobility. While their autonomy enables powerful capabilities, it also introduces vulnerabilities due to hardware faults, software defects, communication failures, and adversarial interference. This survey presents a comprehensive review of research studies closely related to UAV anomalies published between 2015 and 2025, covering 111 papers from academic and industrial sources. We introduce a unified five-pillar taxonomy—anomaly generation, prevention, detection, recovery, and analysis—that organizes existing work across the full anomaly management lifecycle. In contrast to prior surveys that focus primarily on detection algorithms, …

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Configuring Agentic Ai Coding Tools: An Exploratory Study, Matthias Galster, Seyedmoein Mohsenimofidi, Jai Lal Lulla, Muhammad Auwal Abubakar, Christoph Treude, Sebastian Baltes Jul 2026

Configuring Agentic Ai Coding Tools: An Exploratory Study, Matthias Galster, Seyedmoein Mohsenimofidi, Jai Lal Lulla, Muhammad Auwal Abubakar, Christoph Treude, Sebastian Baltes

Research Collection School Of Computing and Information Systems

Agentic AI coding tools increasingly automate software development tasks. Developers can configure these tools through versioned repository-level artifacts such as Markdown and JSON files. We present a systematic analysis of configuration mechanisms for agentic AI coding tools, covering Claude Code, GitHub Copilot, Cursor, Gemini, and Codex. We identify eight configuration mechanisms spanning from static context to executable and external integrations and, in an empirical study of 2,853 GitHub repositories, examine whether and how they are adopted, with a detailed analysis of Context Files, Skills, and Subagents. First, Context Files dominate the configuration landscape and are often the sole mechanism in …

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Towards Uniformity And Alignment For Multimodal Representation Learning, Wenzhe Yin, Pan Zhou, Zehao Xiao, Jie Liu, Shujian Yu, Jan-Jakob Sonke, Efstratios Gavves Jul 2026

Towards Uniformity And Alignment For Multimodal Representation Learning, Wenzhe Yin, Pan Zhou, Zehao Xiao, Jie Liu, Shujian Yu, Jan-Jakob Sonke, Efstratios Gavves

Research Collection School Of Computing and Information Systems

Multimodal representation learning aims to construct a shared embedding space in which heterogeneous modalities are semantically aligned. Despite strong empirical results, InfoNCE-based objectives introduce inherent conflicts that yield distribution gaps across modalities. In this work, we identify two conflicts in the multimodal regime, both exacerbated as the number of modalities increases: (i) an alignment–uniformity conflict, whereby the repulsion of uniformity undermines pairwise alignment, and (ii) an intra-alignment conflict, where aligning multiple modalities induces competing alignment directions. To address these issues, we propose a principled decoupling of alignment and uniformity for multimodal representations, providing a conflict-free recipe for multimodal learning that …

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Air: Improving Agent Safety Through Incident Response, Zibo Xiao, Jun Sun, Junjie Chen Jul 2026

Air: Improving Agent Safety Through Incident Response, Zibo Xiao, Jun Sun, Junjie Chen

Research Collection School Of Computing and Information Systems

Large Language Model (LLM) agents are increasingly deployed in practice across a wide range of autonomous applications. Yet current safety mechanisms for LLM agents focus almost exclusively on preventing failures in advance, providing limited capabilities for responding to, containing, or recovering from incidents after they inevitably arise. In this work, we introduce AIR, the first incident response framework for LLM agent systems. AIR defines a domain-specific language for managing the incident response lifecycle autonomously in LLM agent systems, and integrates it into the agent's execution loop to (1) detect incidents via semantic checks grounded in the current environment state and …

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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 Jul 2026

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 …

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Dual-Diffusional Generative Fashion Recommendation, Mingzhe Yu, Lei Wu, Qianru Sun, Yunshan Ma Jul 2026

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 …

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Avadclip: Audio-Visual Collaboration For Robust Video Anomaly Detection, Peng Wu, Wanshun Su, Guansong Pang, Yujia Sun, Qingsen Yan, Peng Wang, Yanning Zhang Jul 2026

Avadclip: Audio-Visual Collaboration For Robust Video Anomaly Detection, Peng Wu, Wanshun Su, Guansong Pang, Yujia Sun, Qingsen Yan, Peng Wang, Yanning Zhang

Research Collection School Of Computing and Information Systems

With the increasing adoption of video anomaly detection in intelligent surveillance domains, conventional visual-only detection approaches often struggle with information insufficiency and high false-positive rates in complex environments. To address these limitations, we present a novel weakly supervised framework that leverages audio-visual collaboration for robust video anomaly detection. Capitalizing on the exceptional cross-modal representation learning capabilities of Contrastive Language-Image Pretraining (CLIP) across visual, audio, and textual domains, our framework introduces two major innovations: an efficient audio-visual fusion that enables adaptive cross-modal integration through lightweight parametric adaptation while maintaining the frozen CLIP backbone, and a novel audio-visual prompt that dynamically enhances …

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Generation-Augmented Video Corpus Moment Retrieval, Mingjin Kuai, Qianyin Xiao, Juncheng Li, Jin Peng, Lizi Liao, Wei Ji Jul 2026

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 …

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Zero-Shot Transfer Of Foundation Time-Series Forecasters To Datacenter Operational Telemetry: Mapping A Domain Nobody Gets To Study, David Pace Jr Jul 2026

Zero-Shot Transfer Of Foundation Time-Series Forecasters To Datacenter Operational Telemetry: Mapping A Domain Nobody Gets To Study, David Pace Jr

LSU New Orleans Theses and Dissertations

This thesis asks how best to forecast real datacenter operational telemetry. Can pretrained foundation time-series forecasters do it zero-shot, or do trained classical baselines perform best? On a single-site benchmark of eight audited targets and four horizons (32 slices), the zero-shot foundation forecasters Moirai, Chronos, and TimesFM win 26 of 32 slices against multivariate classical baselines. However, the foundation wrappers operate per-channel on the target history, while classical baselines consume the full feature tensor. When the same classical models are retrained univariate, the foundation lead persists (27 of 32 slices) and a 3-seed rerun of a classical challenger reproduces it; …

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Learning-Based Multi-Objective Operation Of Microgrid With Renewable Uncertainty And Demand-Side Management, Zeina Bahij Jul 2026

Learning-Based Multi-Objective Operation Of Microgrid With Renewable Uncertainty And Demand-Side Management, Zeina Bahij

Theses

A microgrid is a small-scale power grid that can operate in either the grid-connected mode or the islanded mode. It consists of energy generation and storage devices for both power and thermal demands, where the thermal energy from the exhaust heat that cannot be transmitted over long distances can be utilized locally. The supply side may include dispatchable generation units with adjustable outputs and energy storage, alongside non-dispatchable renewables that depend entirely on resource availability. On the demand side, thermal loads are satisfied through waste heat recovery from exhaust gas (to maximize overall system efficiency) and direct fuel combustion. Electrical …

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Marketplace Summer 2026, Southern Adventist University Jul 2026

Marketplace Summer 2026, Southern Adventist University

MarketPlace - School of Business Newsletter

The Summer 2026 issue of MarketPlace features an article about Ruth McKee's legacy. Additional articles explore interdisciplinary student exploration of challenges and possibilities in rural Kenya and fundraising projects for local non-profits.

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Assessing The Imprint Of Eccentricity In Gravitational-Wave Signatures, Natalie Malagon Jul 2026

Assessing The Imprint Of Eccentricity In Gravitational-Wave Signatures, Natalie Malagon

Theses

The gravitational wave signal from merging compact binaries encodes information about their orbital and intrinsic properties. Over the last few years, state-of-the-art waveform models have begun to incorporate the effects of orbital eccentricity into their estimated signal. Over a similar period, many groups have applied these waveforms to characterize whether the imprint of eccentricity is present and, if so, measure this time-evolving property (at a suitably-defined reference point). In this work, we present a comprehensive analysis of 173 confident sources identified in the O1 through O4a observing runs of the International Gravitational Wave Network (LIGO-Virgo-KAGRA). Using the RIFT parameter inference …

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Butte Reclamation Evaluation System Corrective Action Plans For Reclaimed Sites 2025 Bres Site Specific Corrective Action Plans For Quadrant 2, Butte-Silver Bow Department Of Reclamation And Environmental Services Jul 2026

Butte Reclamation Evaluation System Corrective Action Plans For Reclaimed Sites 2025 Bres Site Specific Corrective Action Plans For Quadrant 2, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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The Effectiveness Of Writing Professional Development For Instructional Leaders On Student Academic Outcomes, Kourtney Y. Lavergne Jul 2026

The Effectiveness Of Writing Professional Development For Instructional Leaders On Student Academic Outcomes, Kourtney Y. Lavergne

Electronic Theses and Dissertations

The purpose of this qualitative case study was to explore how elementary instructional leaders in a Southeast Texas school district perceived and utilized the R.A.C.E. (Restate, Answer, Cite, Explain) professional development training as an instructional tool to improve student writing performance. The study was guided by two research questions: (a) How do elementary instructional leaders perceive the R.A.C.E. professional development training as an effective English writing curriculum tool to improve student performance? and (b) How do instructional leaders utilize the R.A.C.E. professional development training to improve student writing performance in their classrooms? The study was grounded in adult learning theory …

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Draft Final 2023 Insufficiently Reclaimed Sites Sampling: Bres No. 93 – Soudan Dump Site Evaluation Summary Report, Pioneer Technical Services, Inc. Jul 2026

Draft Final 2023 Insufficiently Reclaimed Sites Sampling: Bres No. 93 – Soudan Dump Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Draft Final 2023 Unreclaimed Sites Sampling: Ur-42 Site Evaluation Summary Report, Pioneer Technical Services, Inc. Jul 2026

Draft Final 2023 Unreclaimed Sites Sampling: Ur-42 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Medical Monitoring Working Group Meeting Minutes, Mike Mcanulty, Eric Hassler Jul 2026

Medical Monitoring Working Group Meeting Minutes, Mike Mcanulty, Eric Hassler

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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2026 Final Insufficiently Reclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc. Jul 2026

2026 Final Insufficiently Reclaimed Sites Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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Advancing Imbalanced Classification Through Representation Learning, Morteza Mohammady Gharasuie Jul 2026

Advancing Imbalanced Classification Through Representation Learning, Morteza Mohammady Gharasuie

Computer Science Theses & Dissertations

Real-world datasets frequently exhibit severe class imbalance, where certain categories are significantly underrepresented relative to others, leading standard empirical risk minimization to bias learning toward majority classes and degrade performance on minority categories. This dissertation addresses imbalanced classification across both structured tabular data and long-tailed visual recognition by developing methods that improve representation learning and decision reliability under skewed distributions. For tabular data, it introduces Conditional Probability Representation (CPR), a target-based encoding framework that embeds feature–label relationships directly into the representation space, enhanced by a progressive feature upgrading mechanism for semi-supervised settings and a class-frequency–aware extension that improves robustness to …

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System For Privacy-Preserving Cryptographic Auditing Using Zero-Knowledge Proofs, N/A Jun 2026

System For Privacy-Preserving Cryptographic Auditing Using Zero-Knowledge Proofs, N/A

Defensive Publications Series

Systems for enterprise security may rely on high (fidelity) logging, which can involve collecting and storing large volumes of sensitive event metadata, creating security and privacy liabilities. A cryptographic auditing framework may be utilized where, instead of storing raw event data, a system can generate and store a succinct cryptographic proof, such as a zero-knowledge proof. This proof can serve as a mathematical attestation that a permitted action occurred in compliance with a governing policy, potentially without revealing the specific details of the user or the action. This approach can be used to generate a tamper-evident, privacy-preserving, and space-efficient audit …

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Establishing New Territorializations In A Community-Engaged Tesol Program: Insights From College Student Experiences, Lourdes Cardozo-Gaibisso, Savanah Stewart, Daniela Coral Patino, Haylee Morman Jun 2026

Establishing New Territorializations In A Community-Engaged Tesol Program: Insights From College Student Experiences, Lourdes Cardozo-Gaibisso, Savanah Stewart, Daniela Coral Patino, Haylee Morman

Journal of English Learner Education

This article presents a community engaged learning experience and its instructional implications for TESOL. The instructional cultures established in policies and practices that dictate college students’ engagement with the “real world” are dependent upon the ways they respond to and translate existing territories in social, cultural, political, and linguistic interactions with multilingual learners and communities. From a Deleuzoguattarian perspective on territorialization and deterritorialization, this article problematizes how college students perceive, and question established norms and taken-for-granted ways of doing emphasizing the importance of reflective practices, ongoing supports for all participants involved, and partnerships with local communities, advocating for a nuanced …

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