The Interactive Virtual Reality Learning Platform for Rice Milling Process
An Empirical Study of Rice Cooperative in Vientiane, Lao PDR
DOI:
https://doi.org/10.13052/jmm1550-4646.2231Keywords:
Virtual Reality, agricultural training, knowledge transfer, rice milling process, immersive learning, IVRLPAbstract
Rice production plays a vital role in the economies of Southeast Asia; however, the increasing adoption of automated and digitally integrated rice milling systems has posed significant challenges for workforce training, particularly for inexperienced operators. To address this gap, this study proposes an Interactive Virtual Reality Learning Platform (IVRLP) designed to support immersive, experiential training for rice milling operations. The study adopts a mixed-methods approach, integrating quantitative pre- and post-training assessments with qualitative user feedback to evaluate the platform’s effectiveness. A total of 31 participants from rice milling cooperatives in Vientiane, Lao PDR, engaged with the IVRLP, which simulates key operational processes such as cleaning, separation, and polishing. Statistical analysis using a paired-samples t-test revealed significant improvements in learning outcomes. Specifically, process familiarity increased from M = 3.12 (SD = 0.84) to M = 4.08 (SD = 0.63), with a paired-samples t-test result of t = 6.85, df = 30, p < 0.001, while operational confidence improved from M = 3.05 (SD = 0.91) to M = 4.15 (SD = 0.58), t = 7.42, df = 30, p < 0.001. In addition, descriptive findings indicate high levels of user satisfaction, with 80.9% of participants reporting enhanced understanding and 78.5% expressing willingness to recommend the system.
Downloads
References
Ministry of Industry and Commerce. “Strategic plan for digital transformation in agricultural cooperatives” [in Lao]. Vientiane, Lao PDR: Ministry of Industry and Commerce, 2023.
FAO. “Digitalization in agriculture: Driving efficiency and sustainability in Southeast Asia” (FAO Agricultural Development Report No. 12). Food and Agriculture Organization of the United Nations, 2021. https://www.fao.org/publications.
NNT. “Smart agriculture initiatives: Scaling up digital solutions for smallholder farmers.” National News Bureau of Thailand, 2022. https://thainews.prd.go.th.
A. John and M. Fielding, “Rice production constraints and ‘new’ challenges for South Asian smallholders: Insights into de facto research priorities,” J. Agric. Sci. Technol., vol. 12, no. 4, pp. 233–245, 2021.
P. Cuaton and L. L. Delina, “Two decades of rice research in Indonesia and the Philippines: A systematic review and research agenda for the social sciences,” Asian J. Agric. Develop., vol. 18, no. 1, pp. 45–63, 2022.
M. Amiri-Zarandi, M. H. Fard, S. Yousefinaghani, M. Kaviani, and R. Dara, “A platform approach to smart farm information processing,” Comput. Electron. Agric., vol. 194, Art. no. 107678, 2022.
V. Moysiadis, P. Sarigiannidis, V. Vitsas, and A. Khelifi, “Smart farming in Europe: An overview of emerging technologies,” Comput. Electron. Agric., vol. 196, Art. no. 106891, 2022.
S. Wolfert, L. Ge, C. Verdouw, and M. J. Bogaardt, “Big data in smart farming: A review,” Agric. Syst., vol. 153, pp. 69–80, 2017.
R. Dagar, S. Som, and S. K. Khatri, “Smart farming - IoT in agriculture,” Int. J. Comput. Appl., vol. 180, no. 44, pp. 19–23, 2018.
R. Varghese and S. Sharma, “Affordable smart farming using IoT and machine learning,” J. Appl. Comput. Inf. Technol., vol. 28, no. 2, pp. 111–123, 2020.
D. Weichert, P. Link, A. Stoll, S. Rüping, S. Ihlenfeldt, and S. Wrobel, “A review of machine learning for the optimization of production processes,” Int. J. Adv. Manuf. Technol., vol. 104, no. 9, pp. 3185–3200, 2019.
J. P. U. Cadavid, S. Lamouri, B. Grabot, R. Pellerin, and A. Fortin, “Machine learning applied in production planning and control: A state-of-the-art in the era of Industry 4.0,” J. Intell. Manuf., vol. 31, pp. 1531–1558, 2020.
A. D. Kaplan, J. Cruit, and P. A. Hancock, “The effects of virtual reality, augmented reality, and mixed reality as training enhancement methods: A meta-analysis,” Hum. Factors, vol. 63, no. 4, pp. 706–718, 2021.
H. Li, “Analysis of virtual reality technology applications in agriculture,” IEEE Access, vol. 9, pp. 12547–12560, 2021.
Y. Wang, “The influence of virtual reality technology on the cultivation of agricultural students,” J. Agric. Educ. Ext., vol. 28, no. 3, pp. 377–391, 2022.
A. K. Singh, B. K. Singh, and S. K. Singh, “Optimization of rice milling parameters for improved head rice yield and quality,” J. Food Sci. Technol., vol. 49, no. 6, pp. 787–792, 2012.
M. A. Rahman, M. A. Islam, and M. A. Rahman, “Energy efficiency of rice milling machines: A review,” Int. J. Agric. Eng., vol. 6, no. 2, pp. 97–104, 2013.
M. A. Rahman, M. A. Islam, and M. A. Rahman, “Rice milling byproducts: Potential for value-added products,” Proc. Int. Conf. Food Sci. Technol., pp. 234–239, 2015.
Kumar, A., and Singh, R. Predictive maintenance in rice milling using machine learning techniques: A review. International Journal of Engineering Research & Technology (IJERT), vol. 9, no. 7, pp. 123–128, 2020.
Smith, J., and Jones, M. (2021). Modelling and analysis of a rice mill production system using a combination of dynamic simulation and data mining. Computers and Electronics in Agriculture, 180, Art. no. 105859.
J. Smith and K. Lee, “Virtual reality in agricultural training: A systematic review,” Comput. Electron. Agric., vol. 210, Art. no. 107976, 2023.
Y. Chen, L. Zhao, P. Liu, and M. Lin, “Immersive VR for industrial and farming skills development: Comparative effectiveness study,” J. Agric. Educ., vol. 63, no. 4, pp. 341–355, 2022.
R. Johnson, T. Pham, and S. Nguyen, “Effectiveness of immersive VR training in resource-constrained settings: A case study of smallholder farms,” Int. J. Agric. Educ. Ext., vol. 27, no. 2, pp. 89–104, 2021.
S. Getahun, H. Kefale, and Y. Gelaye, “Application of precision agriculture technologies for sustainable crop production and environmental sustainability: A systematic review,” The Scientific World Journal, Art. no. 2126734, 2024.
