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1. Enhancing student experience and learning with iterative design in an intelligent educational game

   https://doi.org/10.1111/bjet.13526  

   Hare, Ryan; Ferguson, Sarah; Tang, Ying (October 2024, British Journal of Educational Technology)

   With increasing interest in computer‐assisted educa‐ tion, AI‐integrated systems become highly applicable with their ability to adapt based on user interactions. In this context, this paper focuses on understanding and analysing first‐year undergraduate student responses to an intelligent educational system that applies multi‐agent reinforcement learning as an AI tutor. With human–computer interaction at the centre, we discuss principles of interface design and educational gamification in the context of multiple years of student observations, student feedback surveys and focus group interviews. We show positive feedback from the design methodology we discuss as well as the overall process of providing automated tutoring in a gamified virtual environment. We also discuss students' thinking in the context of gamified educational systems, as well as unexpected issues that may arise when implementing such systems. Ultimately, our design iterations and analysis both offer new insights for practical implementation of computer‐assisted educational systems, focusing on how AI can augment, rather than replace, human intelligence in the classroom. Practitioner notesWhat is already known about this topicAI‐integrated systems show promise for personalizing learning and improving student education.Existing research has shown the value of personalized learner feedback.Engaged students learn more effectively.What this paper addsStudent opinions of and responses to an HCI‐based personalized educational system.New insights for practical implementation of AI‐integrated educational systems informed by years of student observations and system improvements.Qualitative insights into system design to improve human–computer interaction in educational systems.Implications for practice and/or policyActionable design principles for computer‐assisted tutoring systems derived from first‐hand student feedback and observations.Encourage new directions for human–computer interaction in educational systems. 

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2. The Lake Urmia vignette: a tool to assess understanding of complexity in socio‐environmental systems

   https://doi.org/10.1002/sdr.1659  

   Davis, Kirsten; Ghaffarzadegan, Navid; Grohs, Jacob; Grote, Dustin; Hosseinichimeh, Niyousha; Knight, David; Mahmoudi, Hesam; Triantis, Konstantinos (August 2020, System Dynamics Review)

   Abstract We introduce the Lake Urmia Vignette (LUV) as a tool to assess individuals' understanding of complexity in socio‐environmental systems. LUV is based on a real‐world case and includes a short vignette describing an environmental catastrophe involving a lake. Over a few decades, significant issues have manifested themselves at the lake because of various social, political, economic, and environmental factors. We design a rubric for assessing responses to a prompt. A pilot test with a sample of 30 engineering graduate students is conducted. We compare responses to LUV with other measures. Our findings suggest that students' understanding of complexity is positively associated with their understanding of systems concepts such as feedback loops but not with other possible variables such as self‐reported systems thinking skills or systems‐related coursework. Based on the provided instructions, researchers can use LUV as a novel assessment tool to examine understanding of complexity in socio‐environmental systems. © 2020 System Dynamics Society 

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3. Free‐space Optical Computing Systems

   https://doi.org/10.1002/andp.202400390  

   Chen, Ruiyang; Gao, Weilu (March 2025, Annalen der Physik)

   Abstract Free‐space optical systems are emerging as a hardware platform for high‐throughput and energy‐efficient computing. In this review, the pioneering works are first introduced to lay the foundation for the principles and architectures of systems. The modern hardware implementations of two types of optical computing systems, matrix, and vector multiplication systems and diffractive optical neural network systems, are covered from material, device, and system perspectives. Further, the system deployment to various applications is also discussed. This review serves as an introduction and guideline to the current progress of developing and utilizing free‐space optical computing systems in various domains. 

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4. System-level investigation of cognitive adaptation in incident management.

   Moon, J (July 2019, Resilience Engineering Association (REA) Symposium)

   My dissertation research to date has focused on understanding how incident management teams (IMTs), hastily formed multidisciplinary multiteam systems, cognitively function together as adaptive, joint cognitive systems-of-systems embedded in complex sociotechnical systems. Catastrophic disasters such as Hurricane Harvey highlight the importance of collective efforts for adaptive incident management. Team cognition has emerged as a coordinating mechanism in safety-critical disciplines; however, little is known about cognition in IMTs. Through a scoping review of existing definitions, I proposed an expanded definition that deliberately takes into account IMT’s unique contextual characteristics, based on three premises: cognition in IMTs (1) manifests as interactions among humans, teams, and technologies at multiple levels of multiteam systems, (2) aims to achieve the system-level cognitive goals of perceiving (P), diagnosing, (D), and adapting (A) to information, and (3) serves as an open communication platform for adaptive coordination.Then, I operationalized our proposed definition in a simulated environment as an initial attempt to model IMTs’ system-level cognition. Based on several observations of IMTs’ naturalistic interactive behaviors under different types of disaster scenarios, I proposed a model that can capture how IMTs as joint cognitive systems (or systems-of-systems) perceive (P), diagnose, (D), and adapt (A) to information, i.e., perceive, diagnose, adapt (P, D, A) model. With an emphasis on system-level cognitive goals that applies to multiple units of analysis (e.g., individuals, dyads, teams, and multiteam systems), I could gain an understanding of system-level cognitive adaptation in incident management. Using the P, D, A model as a base platform, I expect to discuss resilience as cognitive adaptation processes along with its implications on human information processing and joint cognitive systems theories.I became a Ph.D. candidate after successfully proposing my dissertation research in last June. After completing data collection and processing, I am currently working on data analysis and manuscript preparation. As a part of NSF-funded project (NSF EArly-concept Grant for Exploratory Research, #1724676), I believe my dissertation work has a potential to practically impact scenario-based training practices of incident management, and thereby lead to a more rapid and better coordinated decision-making in saving lives and infrastructures. 

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5. Strongly hyperbolic quasilinear systems revisited, with applications to relativistic fluid dynamics

   https://doi.org/10.3233/ASY-241919  

   Disconzi, Marcelo M; Shao, Yuanzhen (November 2024, Asymptotic Analysis)

   We revisit the theory of first-order quasilinear systems with diagonalizable principal part and only real eigenvalues, what is commonly referred to as strongly hyperbolic systems. We provide a self-contained and simple proof of local well-posedness, in the Hadamard sense, of the Cauchy problem. Our regularity assumptions are very minimal. As an application, we apply our results to systems of ideal and viscous relativistic fluids, where the theory of strongly hyperbolic equations has been systematically used to study several systems of physical interest. 

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