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    Making Archival Collections Accessible: Using CollectionBuilder to Create Digital Databases

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    Kean University’s Holocaust Education and Resource Center undertook the digitization of the Goldsmith Archival Collection. Using CollectionBuilder, a static site generator that generates digital collections, the HERC successfully digitized and published the collection. Representatives from the Center will present on CollectionBuilder and its use for libraries and archives. The site: https://kyradezjot.github.io/Goldsmith-Collection

    Technology, Equity, and OER: Building Pathways to Global Collaboration and Social Mobility

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    This workshop focuses on the connection between Open Educational Resources (OER), technology integration, and equity in education. It highlights how schools and districts can use OER to strengthen professional learning, build community partnerships, and expand access to high-quality resources. The session draws from my doctoral research on how closing the digital divide can promote social mobility, alongside case studies from district leadership and nonprofit initiatives. Participants will examine practical strategies for designing professional development that leverages OER and technology to address inequities, with attention to inclusive design and cross-border collaboration. An interactive design challenge will engage participants in applying frameworks such as the ISTE Standards, the SAMR model, and Design Thinking to create OER-based professional learning models tailored to their own contexts. The session emphasizes how open pedagogy, when linked to technology integration and equity, can support both local practices and global knowledge sharing

    SBA-Backed NJRIC Offering Free Accelerator Program and Cyber Risk Assessments

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    Small Businesses Wanted: SBA-Backed New Jersey AI, Cybersecurity, and IT Cluster Offers Free Accelerator Program and Cybersecurity Risk Assessments | ROI-NJ https://njbmagazine.com/njb-news-now/sba-backed-njric-offering-free-accelerator-program-and-cyber-risk-assessments

    George van Brugh Brown to Susan Niemcewicz, February 26, 1806

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    George Van Brugh Brown wrote Exmouth, Devonshire, England to Susan Niemcewicz in Elizabethtown, New Jersey. Susan would likely be surprised when seeing the address of George’s letter. He and his wife, Elizabeth, left Bath in January. Elizabeth’s complaints have continued nearly the same. When she thinks about the distance between herself and all of her friends, it falls naturally upon her spirits, which have kept up most wonderfully when considering the long and tedious illness she endured. The physicians would not allow her to see people, and the room was kept quiet so that their friends were prevented from being with them. Sorry to hear of such bad accounts of both his cousins Houston and Rutgers.https://digitalcommons.kean.edu/lhc_1800s/1548/thumbnail.jp

    Time to Open Health Professions Education: A Guide to Open Pedagogy in HPE

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    This presentation introduces a collaborative initiative to create a practical guide on Open Pedagogy in Health Professions Education (HPE). Developed by an international team of students, early-career professionals, and educators, the guide addresses the lack of shared definitions and practical direction on openness in the field. It explores open pedagogy in HPE, the use and creation of health-related Open Educational Resources (OER), and strategies to foster advocacy and faculty engagement. This session will share the co-creation process, highlight key content, and invite HPE educators to see how open practices can take shape in their context—laying the groundwork for broader participation and future initiatives in the field. Health Professions Education (HPE) remains one of the least explored fields in open education. Yet, the need for adaptable, participatory learning models in HPE has never been greater. Our session introduces a collaboratively authored Open Pedagogy Guide for HPE—developed by an international team of students, educators, and early-career professionals—to bridge gaps in shared definitions, practical strategies, and advocacy for openness in the field. We will explore the guide’s development, highlighting its key themes: redefining open pedagogy in HPE, integrating health-specific OERs, & fostering faculty engagement. Attendees will gain insights into the co-creation process, including challenges and successes of coordinating across time zones, disciplines, and professional hierarchies. By showcasing this initiative, we aim to inspire educators to adapt open practices in their contexts, laying the groundwork for broader participation and future initiatives in the field

    Open Networked Learning (ONL): A Global, Scalable, Transformative Model for Equity-Focused Staff Development

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    Open Networked Learning (ONL) is a decade-long collaborative professional development initiative that harnesses the principles of openness, networked learning, and problem-based pedagogy to support higher education staff around the world. Unlike localized programs, ONL functions as both a course and a global community of practice—participants from many countries engage in small facilitated groups, share resources openly, and often transition into facilitator or co-design roles in later iterations. Over 17 cycles, ONL has refined a scalable structure that balances institutional participation with open access to external learners. ONL is especially relevant to the OER community because it models how equity and open access can operate in staff development itself. By offering participation beyond institutional borders, supporting diverse digital literacies, and adhering to layered openness, ONL reduces traditional barriers to professional development. Participants report profound shifts in digital competences, reflective teaching practices, and confidence to experiment with open pedagogies in their own contexts. In effect, ONL is transformational—educators become innovators rather than consumers of open materials. But the model is not without challenges: ensuring institutional buy-in, managing participant diversity (in language, access, experience), and demonstrating recognized value within formal reward structures remain persistent issues. ONL addresses these via distributed facilitation, continuous evaluation, adaptive course design, and embedding alumni engagement for sustainability. Key lessons include: (1) community drives continuity; (2) openness must be intentional and scaffolded; (3) transformation emanates from experience, not just theory; and (4) sustainability depends on replenishing leadership and renewing partnerships. For the OER community, ONL offers a replicable, equity-aligned blueprint—not merely for open educational resources, but for open staff development itself

    Utilizing a Virtual Firewall Appliance for Introducing and Reinforcing the Concepts and Implementation of Devices to Improve Security in a Computing Environment

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    The educational realm of higher education cybersecurity curriculum continues to evolve to provide more opportunities for experiential hands-on and work role-related practical applications of technology solutions. Gaining greater competencies is quickly becoming a normal requirement for such programs that are designated by the National Security Agency Center of Academic Excellence programs. The work roles of cybersecurity include a variety of knowledge, skills, and abilities, depending on the category of the activity or task. Firewalls have been a staple cybersecurity, network security, and information security device and strategy to protect organization networks and computing environments. This paper will provide details and a description of the effort and project to utilize a professionally available virtual firewall to provide introductory students with an opportunity to get an authentic and practical experience. The purpose of this paper is to demonstrate to other faculty interested in holding a firewall class a chance to share and review the process, tools, and implementation used with students that resulted in a positive outcome. This write-up will demonstrate the potential for using virtual firewalls as a learning tool in information technology security learning. In addition, further content is provided as a plan for the next steps and other ideas and technologies that can be used to further the “hands-on” learning of such security technology systems

    AdversaGuard: A Distributed Data-Poisoning Benchmark for Parallel AI

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    As organizations scale model training across large clusters and clouds, data poisoning has emerged as a significant practical threat. Most existing research focuses on data poisoning in single-node environments. Far fewer studies have compared the effectiveness of attacks across parallel training strategies, where factors like gradient aggregation and distributed memory ceilings fundamentally alter attack detectability and its impacts. To address this gap, we introduce AdversaGuard, a reproducible benchmark and accompanying application designed specifically for distributed settings to protect AI training pipelines. This research makes the following key contributions: (1) A comprehensive Distributed Data Poisoning (DDP) benchmark spanning seven distributed systems (leveraging data, model, and hybrid parallelism) and a non-distributed baseline. (2) A standardized attack suite implementing eight poisoning methods with consistent budgets for fair comparison. (3) An analysis of how different parallel strategies modulate attack impacts, demonstrating that design choices can either mask or amplify vulnerabilities. (4) A publicly available interactive application for live testing and method comparison. And (5) A novel evaluation metric, the AdversaGuard Efficiency Index (AEI), which provides a composite score for DDP robustness considering accuracy, attack success, model size, and computational overhead. To evaluate AdversaGuard as an HPC-oriented framework for benchmarking adversarial robustness and training efficiency in distributed data poisoning (DDP) settings, we experimented with eight system configurations—seven distributed regimes and a baseline—across three food-domain image datasets and four model families, ranging from compact CNNs to large Vision Transformers. Within AdversaGuard framework, we implemented eight common adversarial attacks, such as FGSM, PGD, DeepFool, and Carlini-Wagner, and analyzed how data, model, nd hybrid parallelism affect scalability, memory consumption, and vulnerability. Our key findings are that while data parallelism’s gradient averaging can mask low-budget perturbations, larger models consistently exhibit greater susceptibility to poisoning. To quantify these trade-offs, we introduce the AdversaGuard Efficiency Index (AEI), a composite metric for evaluating parallelism-aware robustness. Our implementation of a companion AdversaGuard application enables live testing (GitHub repository) with the help of a live demo (YouTube). This work underscores the critical need for scalable, adaptive defenses in modern, distributed AI training pipeline

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