Augmented reality learning environment to aid engineering students in performing practical laboratory experiments in electronics engineering
Year: 2022
Type: article
Study design: Clinical Trial
Abstract: In an era where technology is being used more and more in daily life, the potential and effective use of technology is becoming increasingly vital in education. Engineering education necessitates the use of technology to assist students in understanding abstract concepts and principles. Augmented reality (AR) is a technology that can be used to create effective and engaging technology-based solutions and instructional materials. This research aims to develop an augmented reality-based learning experience to teach students about electronics engineering concepts and determine the impact of AR intervention on students' academic achievement levels, learning attitudes toward the subject, and individual attitudes toward AR technology. A quasi-experimental research design was used on 107 first-year engineering students who were grouped into control and experimental groups. The control group consisted of 53 students who learned the fundamentals of electronics using existing techniques, while experimental group consisted of 54 students who learned the same subject using an Augmented Reality-based Lab Manual. The experimental outcomes indicate that the experimental group performed better in the post-test and obtained higher academic scores compared to the control group. In addition, AR intervention has a substantial positive effect on students' learning attitudes. The study also found that students' learning attitudes towards electronics courses and their academic achievement have a significant positive relationship. Additionally, there is a correlation between a student's academic achievement and their attitude toward AR technology. As a result, students who studied using AR technology had a more optimistic perspective about the electronics course and AR technology.
Source: Smart Learning Environments
Institution: Chitkara University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid:
Funder: Chitkara University
OpenAlex ID: W4291633262