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The objective of this paper is to provide a holistic summary of ongoing research related to the development, implementation, assessment, and continuous refinement of an augmented reality (AR) app known as Vectors in Space. This Unity-based app was created by the authors and provides a self-guided learning experience for students to learn about fundamental vector concepts routinely encountered in undergraduate physics and engineering mechanics courses. Vectors are a fundamental tool in mechanics courses as they allow for the precise and comprehensive description of physical phenomena such as forces, moments, and motion. In early engineering coursework, students often perceive vectors as an abstract mathematical concept that requires spatial visualization skills in three dimensions (3D). The app aims to allow students to build these tacit skills while simultaneously allowing them to learn fundamental vector concepts that will be necessary in subsequent coursework. Three self-paced, guided learning activities systematically address concepts that include: (a) Cartesian components of vectors, (b) unit vectors and directional angles, (c) addition, (d) subtraction, (e) cross product using the right-hand rule, (f) angle between vectors using the dot product, and (g) vector projections using the dot product. The authors first discuss the app's scaffolding approach with special attention given to the incorporation of Mayer's principles of multimedia learning as well as the use of animations. The authors' approach to develop the associated statics learning activities, practical aspects of implementation, and lessons learned are shared. The effectiveness of the activities is assessed by applying analysis of covariance (ANCOVA) to pre- and post-activity assessment scores for control and treatment groups. Though the sample sizes are relatively small (less than 50 students), the results demonstrate that AR had a positive impact on student learning of the dot product and its applications. Larger sample sizes and refinements to the test instruments will be necessary in the future to draw robust conclusions regarding the other vector topics and operations. Qualitative feedback from student focus groups conducted with undergraduate engineering students identified the app's strengths as well as potential areas of improvement.
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An active learning approach to teach distributed forces using augmented reality with guided inquiry
Abstract Mastering the concept of distributed forces is vital for students who are pursuing a major involving engineering mechanics. Misconceptions related to distributed forces that are typically acquired in introductory Physics courses should be corrected to increase student success in subsequent mechanics coursework. The goal of this study was to develop and assess a guided instructional activity using augmented reality (AR) technology to improve undergraduate engineering students' understanding of distributed forces. The AR app was accompanied by a complementary activity to guide and challenge students to model objects as beams with progressively increasing difficulty. The AR tool allowed students to (a) model a tabletop as a beam with multiple distributed forces, (b) visualize the free body diagram, and (c) compute the external support reactions. To assess the effectiveness of the activity, 43 students were allocated to control and treatment groups using an experimental nonequivalent groups preactivity/postactivity test design. Of the 43 students, 35 participated in their respective activity. Students in the control group collaborated on traditional problem‐solving, while those in the treatment group engaged in a guided activity using AR. Students' knowledge of distributed forces was measured using their scores on a 10‐item test instrument. Analysis of covariance was utilized to analyze postactivity test scores by controlling for the preactivity test scores. The treatment group demonstrated a significantly greater improvement in postactivity test scores than that of the control group. The measured effect size was 0.13, indicating that 13% of the total variance in the postactivity test scores can be attributed to the activity. Though the effect size was small, the results suggest that a guided AR activity can be more effective in improving student learning outcomes than traditional problem‐solving.
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- Award ID(s):
- 2141984
- PAR ID:
- 10480124
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Computer Applications in Engineering Education
- ISSN:
- 1061-3773
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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