A Scalable Online Platform for Evaluating and Training Visuospatial Skills of Engineering Students

• Published in: Association for Engineering Education - Engineering Library Division Papers
• Main Authors: Xiao, Ziang, Yao, Yuqi, Chi-Hsien Yen, Dey, Sanorita, Wauck, Helen, Leake, James M, Woodard, Brian, Wolters, Angela, Wai-Tat Fu
• Format: Conference Proceeding
• Language: English
• Published: Atlanta American Society for Engineering Education-ASEE 24.06.2017
• Subjects: Colleges & universities; Engineering; Engineering education; Error analysis; Flow charts; Identification methods; Infrastructure; Problem solving; Schedules; Skills; Students; Training

Previous research has shown that the visuospatial skills, which refer to a person’s ability to understand visual and spatial relationship among objects, increase the capacity to reason and solve complex problems in the engineering field. Although the impact of training visuospatial skills on engineering education is well documented, there has not been online tools that can scale well to large classes, and help the creation of a large nationwide database to allow comparisons across classes, departments, and universities. The automatic grading feature of the online platform can also help early assessment of spatial skills, which enables early intervention for students who want to pursue a career in engineering before the lack of good visuospatial skills becomes a barrier. In practice, early assessment can customize the flowchart of a student’s course schedules to better prepare them to develop the necessary visuospatial skills before they take courses that have heavy demand on these skills. In this study, we design and evaluate an innovative online infrastructure which aims to efficiently evaluate the visuospatial skills of a large group of students and help them to improve their visuospatial skills. The infrastructure offers a comprehensive assessment of visuospatial skills with multiple choice questions and free-hand sketching, as well as, exercises that help students to acquire strategies to more effective perform visuospatial problem solving. The data recorded by the infrastructure allow researchers to analyze the responses in details, including error analysis and stroke-by-stroke analysis of sketching behavior. The platform is also capable of keeping track of a student’s response in each test and the performance in courses in order to identify potential difficulties the student may encounter so as to provide assistance as early as possible. This function provides the possibility to build up a large database which allows data analytic techniques to be deployed to identify patterns that are otherwise difficult to achieve with traditional methods, such as paper test. We tested our online infrastructure over 600 students from four entry-level engineering courses in a large mid-west university. The students were from 17 different engineering-related majors or with the intention to pursue an engineering major. The pilot study shows a great potential of our online tools in testing and improving students’ visuospatial skills in large classes.