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Designing and evaluating an augmented reality system for an engineering drawing course.

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Title: Designing and evaluating an augmented reality system for an engineering drawing course.
Authors: Tiwari, Ajay Shankar1 (AUTHOR), Bhagat, Kaushal Kumar1 (AUTHOR) kaushal.dgp@gmail.com, Lampropoulos, Georgios2 (AUTHOR)
Source: Smart Learning Environments. 1/3/2024, Vol. 11 Issue 1, p1-19. 19p.
Subject Terms: *Engineering education, *Engineering students, Engineering drawings, Technological innovations, Spatial ability, Augmented reality
Abstract: Currently, augmented reality (AR) is one of the emerging technologies which is being widely used in the education sector. In engineering drawing, AR has been implemented to enhance learners' spatial ability but not their conceptual knowledge yet. Therefore, this study aims to evaluate the effect of AR on engineering drawing students' learning performance. In this study, we developed an AR-based application EDINAR to learn engineering drawing concepts for undergraduate engineering students. The study included 392 first-year students from an engineering institution. The control group (N = 196) studied engineering drawing using traditional methods, whereas the experimental group (N = 196) used an AR-based engineering drawing application (EDINAR) to learn engineering drawing. One-way ANOVA was used to analyse the performances of both groups. The findings revealed that students studying engineering drawing with the help of EDINAR outperformed those using traditional approaches. In addition, we received positive feedback about the AR application from the experimental group about their learning experience. Based on these results, it is recommended to incorporate AR in engineering education to improve the learning performance and students' learning experience. [ABSTRACT FROM AUTHOR]
Copyright of Smart Learning Environments is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: <searchLink fieldCode="JN" term="%22Smart+Learning+Environments%22">Smart Learning Environments</searchLink>. 1/3/2024, Vol. 11 Issue 1, p1-19. 19p.
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  Data: Currently, augmented reality (AR) is one of the emerging technologies which is being widely used in the education sector. In engineering drawing, AR has been implemented to enhance learners' spatial ability but not their conceptual knowledge yet. Therefore, this study aims to evaluate the effect of AR on engineering drawing students' learning performance. In this study, we developed an AR-based application EDINAR to learn engineering drawing concepts for undergraduate engineering students. The study included 392 first-year students from an engineering institution. The control group (N = 196) studied engineering drawing using traditional methods, whereas the experimental group (N = 196) used an AR-based engineering drawing application (EDINAR) to learn engineering drawing. One-way ANOVA was used to analyse the performances of both groups. The findings revealed that students studying engineering drawing with the help of EDINAR outperformed those using traditional approaches. In addition, we received positive feedback about the AR application from the experimental group about their learning experience. Based on these results, it is recommended to incorporate AR in engineering education to improve the learning performance and students' learning experience. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Smart Learning Environments is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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