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This paper describes an initial pilot study of Rimac, a natural-language tutoring system for physics. Rimac uses a student model to guide decisions about "what content to discuss next" during reflective dialogues that are initiated after students solve quantitative physics problems, and "how much support to provide" during these discussions, that is, domain contingent scaffolding and instructional contingent scaffolding, respectively. The pilot study compared an experimental and control version of Rimac. The experimental version uses students' responses to pretest items to initialize the student model and dynamically updates the model based on students' responses to tutor questions during reflective dialogues. It then decides what and how to discuss the next question based on the model predictions. The control version initializes its student model based on students' pretest performance but does not update the model further and assigns students to a fixed line of reasoning level based on the student model predictions. We hypothesized that students who used the experimental version of Rimac would achieve higher learning gains than students who used the control version. Although we did not find a significant difference in learning between conditions, the experimental group took significantly less time to complete the pilot study dialogues than did the control group. That is, the experimental condition led to more efficient learning, for both low and high prior knowledge level learners. We discuss this finding and describe future work to improve the tutor's potential to support student learning.

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The construction industry presents its problems regarding safety maintenance, particularly in matters of worker falls. In this case, falls are projected to grow from 33-38%. This project intends to reduce these dangers by developing a vision-based real-time worker’s safety monitoring system that ensures proper use of Personal Fall Arrest Systems (PFAS) on scaffolding. PFAS patients must wear helmets, harnesses, and lanyards because their proper placement is critical in avoiding injury due to falls. The methodology starts with collecting an image dataset. Every image is painstakingly labelled to show all instances of the specific PFAS components and their relevant states. Normalization is performed to match the standards of image inputs with the selected object detection algorithm, YOLOv11. The dataset is divided into training, validation, and testing units, which is representative of the actual situation. This guarantees effective training and testing of the YOLOv11 model for reliable and accurate real-time detection. The verification tests are conducted using the F1 score metric, which evaluates the model in a holistic way. After configuration, the trained YOLOv11 model is deployed on Open CV in the Visual Studio Code (VS Code) environment to enable real-time detection. The ultimate objective is to deliver a system that significantly reduces fall accidents, enhances worker safety, and facilitates compliance with stringent construction site safety standards.

This paper looks at the analysis leading to and design of a Web-based "hint system." The hints are designed to help middle-grade teachers participating in a mathematics professional development effort, called InterMath, achieve a high degree of success when working open-ended mathematical investigations. The model upon which InterMath is based assumes that teachers who experience learning in a rich, exploration-based environment will more readily transfer these kinds of experiences to their classrooms. The centerpiece of the InterMath experience and Web site is an extensive set of open-ended mathematical investigations that can be explored using various technologies. These investigations form the central experience of the 15-week workshop as teachers are encouraged to explore a particular set of explorations, choose problems that intrigue them, work those investigations, and write-up the solutions, along with extensive activities. The paper discusses the issues and processes involved with designing this system, paying special attention to the different types of hints and the limitations of the system. It concludes that the use of a Web-based hints system is a potentially valuable tool for supporting teachers in tackling complex math problems, that there are limitations with this plan, but the just-in-time help of a static system can be combined with the asynchronous support of a wider community as a viable option for promoting the development of mathematical thinking. (Contains 19 references.) (Author/AEF)