A high-fidelity digital representation of the human body is a key enabler for integrating humans in a digital twin. Among different parts of human body, building the model of the hand can be a challenging task due to the posture deviations among collected scans. In this paper, we proposed a posture invariant hand statistical shape model (SSM) based on 59 3D scans of human hands. First, the 3D scans were spatially aligned using a Möbius sphere-based algorithm. An articulated skeleton, which contains 20 bone segments and 16 joints, was embedded for each 3D scan. Then all scans were aligned to the same posture using the skeleton and the linear blend skinning algorithm. Three methods, i.e. Principal Component Analysis (PCA), kernel-PCA with different kernel functions, and Independent Component Analysis, were evaluated in the construction of the SSMs regarding the compactness, the generalization ability and the specificity. The PCA-based SSM was selected, where 20 principal components were used as parameters for the model. Results of the leave-one-out validation indicate that the proposed model was able to fit a given 3D scan of the human hand at an accuracy of 1.21 ± 0.14 mm. Experiment results also indicated that the proposed SSM outperforms the SSM that was built on the scans without posture correction. It is concluded that the proposed posture correction approach can effectively improve the accuracy of the hand SSM, therefore enables its wide usage in human integrated digital twin applications.
little understood question that has motivated her program of research is: How can we effectively and efficiently promote cyberlearning in complex knowledge domains such as STEM (science, technology, engineering and mathematics)? Towards this direction, she (1) investigates the development of higher-order thinking and complex problem-solving competencies following a comprehensive framework that includes cognition, metacognition, cognitive regulation, motivation, emotion, and epistemic beliefs; (2) develops innovative assessment methods that can benchmark progress of learning and the development of complex problem-solving competencies; (3) develops new and effective approaches to design state-of-the-art digital learning environments (such as intelligent tutoring, system dynamics modeling, simulations, virtual reality, and digital games) to facilitate complex problem-solving competencies; and (4) investigates effective ways to prepare teachers and administrators for digital transformation of education to support effective integration and seamless adoption of advanced learning technologies into education. In addition to her work focusing on STEM learning in K-20 educational settings, her research was also carried out in professional contexts including army, aircraft maintenance, air-traffic control, emergency response, environmental sciences, climate change, medical education, instructional design, architecture, construction science, mechanical engineering, industrial engineering, and systems engineering. Cultivating Evidence-Based Pedagogies in STEM Education AbstractIn this paper, we report the findings of a study that explored the changes in STEM faculty's approaches to teaching and understanding of student learning because of their participation in an ongoing STEM education project. This three-year project is funded by the department of education and aimed at cultivating evidence-based pedagogies in STEM undergraduate education at an Historically Black College and University (HBCU) in US. Four STEM faculty members who were the study participants designed evidence-based instructional strategies that were learner-centered and student-focused. The faculty implemented these strategies in their undergraduate courses and systematically collected data from their students to capture the impact of the newly implemented strategies on students' learning outcomes and experiences. With consultation from the learning scientists of the project, the faculty analyzed the student data collected and reported the findings of their research studies. In the following semester, the faculty participants iterated their design efforts. Participants' approaches to teaching and understanding of student learning were captured prior to the project activities and one year after their participation in the project activities. Both quantitative and qualitative data were collected. Analyses revealed that faculty have improved their teaching approaches from a knowledge-centered and teacher-focused orientation to a learner-centered and student-foc...
This paper presents the preliminary work of implementing the learning by teaching approach, a student-centered pedagogy, in the Computer-Aided Design (CAD) education. Following an experimental study design, students were grouped into control section and experimental section. In the control section, students received the traditional instructor-centered instruction. In the experimental section, students were assigned into small groups and taught the course content to their peers during the class meeting. The students’ learning outcomes were evaluated, such as life-long learning skill, engineering attitude, and CAD modeling skills using NX. A CAD modeling test was used at the end of semester to assess the students’ CAD modeling skills. The engineering attitude survey and the life-long learning scale were conducted at the beginning and the end of semester. The statistical analyses were performed to examine the impact of activities. The results revealed that the students’ engineering attitude was significantly improved. In addition, experimental group students completed an exit survey that collected their feedback on the teaching activities.
The current paper presents a system for the dynamic simulation of the human hand. The simulation of the human hand offers the capability to acquire handshapes that correspond to letters of the finger alphabet, enabling an integrated representation of words and sentences. The hand model is designed using the Autodesk Inventor TM and Autodesk AutoCad TM design environments. The user is able to type words or sentences which are dynamically translated into postures according to the finger alphabet. The system is based on the physiometric characteristics of an average human hand. High precision design is utilized in every part through integration of all the necessary functionalities needed to perform the movements required. The system has been tested on more than 500 words with a letter representation success rate in the range of 95-97%.
To promote life-long learning skills in Computer-Aided Design (CAD) education, authors designed and implemented a student-centered instruction in the CAD courses. A quasi-experimental pre-and-post test research design was implemented. Experimental group students were asked to design screencast tutorials with their verbal explanations recorded. Students shared their screencast tutorials with their peers and provided feedback to each other’s video tutorials. Control group students were asked to review the instructor made screencast tutorials. A life-long learning survey, an engineering attitude survey, an exit project survey, and a CAD modeling exam were used as the study instruments. A total of 147 students participated in this study over three years. Findings indicated that female and first generation college students in the experimental group performed better than their peers in the control group in the CAD modeling exam. Our student-centered instruction was more affective on female students’ and first generation college students’ skills and knowledge than male students’ and not-first generation college students’ skills and knowledge.
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