Full Title: Using augmented reality models, customized analog LED point cube tools, and behavioral spectrometer active analysis examples to facilitate a student’s learning of abstract concepts, such as volumetric visualization and subjective thinking required in applied engineering, and techniques of estimating analysis.
We will address challenges instructors face when teaching engineering rigor while introducing students to applied abstract thinking and visualization skills, which are difficult to grasp, but necessary in several technical disciplines related to predictive analysis.
Engineering undergraduate students are trained in objective analysis based on prescribed values and closed-ended solutions. It is crucial for reliable predictive analysis to apply calculations and real-world applications. However, in some cases, an acceptable variance to the actual outcomes may depend on subjective considerations. In such instances, open-ended and subjective analysis is likely required. The challenge in teaching certain forms of analysis lies in the student's ability to visualize in a multi-dimensional state. Additionally, demonstrating and teaching subjective and open-ended solutions is difficult, as most models used for demonstration are typically 2D interaction with a 3D state.
We will discuss modality and student internalization methods using volumetric interactive tools, visualization of 3D state from 2D source, subjective vs objective ratio analysis, closed loop and opened loop problem solving.
