Dr. James DeVita, assistant vice president for academic partnerships and high-impact experiences, will co-present at the American Association of Colleges and Universities'  International Society for the Scholarship of Teaching and Learning, Inc. (ISSOTL) annual conference in Christchurch, New Zealand this November in partnership with the University of Canterbury. Dr. DeVita will co-present "Large-Scale Assessment as SoTL: An Emerging Structure that Supports Data-Driven Practices in Higher Education" with Dr. Megan Bolden, University of North Carolina at Wilmington, and Dr. Kristi Wiley, Lenoir Community College.

During their session, they will "explore how the Scholarship of Teaching and Learning (SoTL) has evolved from reflective practice to a systematic, research-based approach to improving student learning. We argue that more emphasis should be placed on applying SoTL principles to large-scale assessment initiatives across institutions. Drawing from examples like the National Survey of Student Leaders and Queen's University Assessment Redesign Project, we showcase how SoTL frameworks can drive institutional change. We will present large-scale assessments that have led to meaningful reforms in undergraduate social work programs, multi-institutional research initiatives, and campus-wide career-readiness outcome mapping."

ISSOTL serves faculty members, staff, and students who care about teaching and learning as serious intellectual work. Through building intellectual and collaborative infrastructure, the Society supports the associational life that fosters scholarly work about teaching and learning. The Society provides this support by:

• recognizing and encouraging scholarly work on teaching and learning in each discipline, within scholarly societies and across educational levels,

• promoting cross-disciplinary conversations to create synergy and prompt new lines of inquiry,

• facilitating the collaboration of scholars in different countries and the flow of new findings and applications across national boundaries,

• encouraging the integration of discovery, learning, and public engagement, and

• advocating for support, review, recognition, and appropriate uses of the scholarship of teaching and learning.

The UMBC Cyber Defense Lab presents

Self-Defending Ledgers: Automating Distributed Ledger Security Using Multi-Agent Reinforcement Learning and Game Theory

Md Tariqul Islam 'Pavel'
Assistant Professor of Cybersecurity
UMBC Department of Information Systems

12–1pm EDT, Friday, October 3, 2025 via Webex

Distributed ledger technologies (DLTs) continue to face significant security challenges. While attackers constantly adapt their strategies, governance mechanisms often remain static. Our work addresses this critical gap by introducing a framework for self-defending ledgers, where nodes enforce ledger security through adaptive governance driven by multi-agent reinforcement learning (MARL) grounded in game-theoretic principles. We model DLT consensus as a repeated Bayesian game, in which participants hold probabilistic beliefs about peer behavior, allowing agents to make strategic decisions under partial observability of adversarial actions. Our framework enables nodes to model, detect, and respond to a wide range of malicious behaviors, including bribery, selfish mining, equivocation, Sybil attacks, and collusive voting, by continuously updating Bayesian trust beliefs and governance policies based on network observations. We formally prove that networks with an honest majority reach stable equilibria and provide bounds on adversarial influence. Experiments across five major protocols show that agents effectively identify attacks with high accuracy while substantially reducing adversarial success. This work demonstrates the potential of game-theoretic MARL to provide robust, self-adaptive security in varied DLT environments, paving the way for resilient and autonomous ledger governance.

Md Tariqul Islam 'Pavel' is an assistant professor of cybersecurity in UMBC's Department of Information Systems. His research centers on the security, efficiency, and fault-tolerance of distributed computing systems, with a strong emphasis on blockchain, cloud, and vehicular networks. He develops formal models, algorithms, and protocols that address critical vulnerabilities in decentralized ecosystems, spanning inter-blockchain communication, smart contract migration, and trustworthy governance. His work combines cryptography, game theory, and system design to build scalable, resilient infrastructures. He earned his PhD and MS from the University of Kentucky and BS from the University of Dhaka, Bangladesh.

The UMBC Cyber Defense Lab presents

Self-Defending Ledgers: Automating Distributed Ledger Security Using Multi-Agent Reinforcement Learning and Game Theory

Md Tariqul Islam 'Pavel'
Assistant Professor of Cybersecurity
UMBC Department of Information Systems

12–1pm EDT, Friday, October 3, 2025 via Webex

Distributed ledger technologies (DLTs) continue to face significant security challenges. While attackers constantly adapt their strategies, governance mechanisms often remain static. Our work addresses this critical gap by introducing a framework for self-defending ledgers, where nodes enforce ledger security through adaptive governance driven by multi-agent reinforcement learning (MARL) grounded in game-theoretic principles. We model DLT consensus as a repeated Bayesian game, in which participants hold probabilistic beliefs about peer behavior, allowing agents to make strategic decisions under partial observability of adversarial actions. Our framework enables nodes to model, detect, and respond to a wide range of malicious behaviors, including bribery, selfish mining, equivocation, Sybil attacks, and collusive voting, by continuously updating Bayesian trust beliefs and governance policies based on network observations. We formally prove that networks with an honest majority reach stable equilibria and provide bounds on adversarial influence. Experiments across five major protocols show that agents effectively identify attacks with high accuracy while substantially reducing adversarial success. This work demonstrates the potential of game-theoretic MARL to provide robust, self-adaptive security in varied DLT environments, paving the way for resilient and autonomous ledger governance.

Md Tariqul Islam 'Pavel' is an assistant professor of cybersecurity in UMBC's Department of Information Systems. His research centers on the security, efficiency, and fault-tolerance of distributed computing systems, with a strong emphasis on blockchain, cloud, and vehicular networks. He develops formal models, algorithms, and protocols that address critical vulnerabilities in decentralized ecosystems, spanning inter-blockchain communication, smart contract migration, and trustworthy governance. His work combines cryptography, game theory, and system design to build scalable, resilient infrastructures. He earned his PhD and MS from the University of Kentucky and BS from the University of Dhaka, Bangladesh.