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This content will become publicly available on December 10, 2024

Title: 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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NSF-PAR ID:
10480124
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  
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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