Leveraging Virtual Reality in Engineering Education to Optimize Manufacturing Sustainability in Industry 4.0
Abstract
:1. Introduction
Research Hypotheses
2. Methodology
2.1. Sample Size Determination
- Effect size (d): 0.5 (this effect size is considered to have a medium impact and is frequently used in educational and psychological studies).
- Significance level (α): 0.05 (conventionally accepted level of significance).
- Power (1 − β): 0.80 (80%, which means they are likely to detect an effect if it is at 80%).
- Zα/2 is the z-score equivalent to the chosen significance level (α = 0.05 equals 1.96).
- Zβ is the z-score associated with the selected power (0.84 at 80% power).
- d is the effect size (0.5 in this case).
2.2. Data Collection
2.3. Intervention
2.4. Analysis
3. Results and Discussions
3.1. Results
3.2. Discussion
3.2.1. Implications
3.2.2. Limitations and Future Directions
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Criteria | Inclusion | Exclusion |
---|---|---|
Academic Program | Undergraduate engineering | Non-engineering disciplines |
Course Enrollment | Enrolled in sustainability course | Not enrolled in sustainability course |
Age | No age restrictions | Age below 18 years |
Consent | Consented to participate | Did not provide consent |
Language Proficiency | Proficient in the language of the survey | Lack of proficiency in the survey language |
Correlations | |||||||||
---|---|---|---|---|---|---|---|---|---|
Age | Gender | VR Experience | Pre-Test Score | Post-Test Score | Sustainability Attitude | Learning Outcomes | |||
Spearman’s rho | Age | Correlation Coefficient | 1.000 | 0.631 ** | 0.410 ** | 0.193 ** | 0.130 * | 0.140 * | 0.295 ** |
Sig. (2-tailed) | . | 0.000 | 0.000 | 0.002 | 0.039 | 0.026 | 0.000 | ||
N | 250 | 250 | 250 | 250 | 250 | 250 | 250 | ||
Gender | Correlation Coefficient | 0.631 ** | 1.000 | 0.334 ** | 0.172 ** | 0.154 * | 0.038 | 0.099 | |
Sig. (2-tailed) | 0.000 | . | 0.000 | 0.006 | 0.014 | 0.001 | 0.002 | ||
N | 250 | 250 | 250 | 250 | 250 | 250 | 250 | ||
VR Experience | Correlation Coefficient | 0.410 ** | 0.334 ** | 1.000 | 0.197 ** | 0.547 ** | 0.182 ** | 0.064 | |
Sig. (2-tailed) | 0.000 | 0.000 | . | 0.002 | 0.000 | 0.004 | 0.031 | ||
N | 250 | 250 | 250 | 250 | 250 | 250 | 250 | ||
Pre-Test Score | Correlation Coefficient | 0.193 ** | 0.172 ** | 0.197 ** | 1.000 | 0.335 ** | 0.323 ** | 0.019 | |
Sig. (2-tailed) | 0.002 | 0.006 | 0.002 | . | 0.000 | 0.000 | 0.002 | ||
N | 250 | 250 | 250 | 250 | 250 | 250 | 250 | ||
Post-Test Score | Correlation Coefficient | 0.130 * | 0.154 * | 0.547 ** | 0.335 ** | 1.000 | 0.481 ** | 0.417 ** | |
Sig. (2-tailed) | 0.039 | 0.014 | 0.000 | 0.000 | . | 0.000 | 0.000 | ||
N | 250 | 250 | 250 | 250 | 250 | 250 | 250 | ||
Sustainability Attitude | Correlation Coefficient | 0.140 * | 0.038 | 0.182 ** | 0.323 ** | 0.481 ** | 1.000 | 0.400 ** | |
Sig. (2-tailed) | 0.026 | 0.001 | 0.004 | 0.000 | 0.000 | . | 0.000 | ||
N | 250 | 250 | 250 | 250 | 250 | 250 | 250 | ||
Learning Outcomes | Correlation Coefficient | 0.295 ** | 0.099 | 0.064 | 0.019 | 0.417 ** | 0.400 ** | 1.000 | |
Sig. (2-tailed) | 0.000 | 0.002 | 0.031 | 0.002 | 0.000 | 0.000 | . | ||
N | 250 | 250 | 250 | 250 | 250 | 250 | 250 |
Type III Tests of Fixed Effects | ||||
---|---|---|---|---|
Source | Numerator df | Denominator df | F | Sig. |
Intercept | 1 | 250.000 | 8.954 | 0.003 |
Age | 1 | 250.000 | 17.578 | 0.000 |
Gender | 1 | 250.000 | 0.713 | 0.001 |
VR Experience | 1 | 250.000 | 0.773 | 0.003 |
Pre-Test Score | 1 | 250.000 | 2.828 | 0.002 |
Post-Test Score | 1 | 250.000 | 33.390 | 0.000 |
Sustainability Attitude | 1 | 250.000 | 1.218 | 0.002 |
Estimates of Fixed Effects | |||||||
---|---|---|---|---|---|---|---|
Parameter | Estimate | Std. Error | df | t | Sig. | 95% Confidence Interval | |
Lower Bound | Upper Bound | ||||||
Intercept | 4.901534 | 1.638003 | 250.000 | 2.992 | 0.003 | 1.675615 | 8.127453 |
Age | 0.153924 | 0.036713 | 250.000 | 4.193 | 0.000 | 0.081621 | 0.226227 |
Gender | 0.093569 | 0.110824 | 250.000 | 1.844 | 0.000 | 0.124690 | 0.311828 |
VR Experience | 0.060241 | 0.068498 | 250.000 | −2.879 | 0.001 | 0.195142 | 0.074661 |
Pre-Test Score | 0.033349 | 0.019830 | 250.000 | 1.682 | 0.002 | 0.005705 | 0.072402 |
Post-Test Score | 0.081134 | 0.014041 | 250.000 | 5.778 | 0.000 | 0.108786 | −0.053481 |
Sustainability Attitude | 0.079448 | 0.072001 | 250.000 | 1.103 | 0.002 | 0.221248 | 0.062353 |
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Share and Cite
Bano, F.; Alomar, M.A.; Alotaibi, F.M.; Serbaya, S.H.; Rizwan, A.; Hasan, F. Leveraging Virtual Reality in Engineering Education to Optimize Manufacturing Sustainability in Industry 4.0. Sustainability 2024, 16, 7927. https://doi.org/10.3390/su16187927
Bano F, Alomar MA, Alotaibi FM, Serbaya SH, Rizwan A, Hasan F. Leveraging Virtual Reality in Engineering Education to Optimize Manufacturing Sustainability in Industry 4.0. Sustainability. 2024; 16(18):7927. https://doi.org/10.3390/su16187927
Chicago/Turabian StyleBano, Farheen, Madani Abdu Alomar, Faisal Mohammed Alotaibi, Suhail H. Serbaya, Ali Rizwan, and Faraz Hasan. 2024. "Leveraging Virtual Reality in Engineering Education to Optimize Manufacturing Sustainability in Industry 4.0" Sustainability 16, no. 18: 7927. https://doi.org/10.3390/su16187927