IoT Technology and Digital Upskilling Framework for Farmers in the Northern Rural Area of Thailand
DOI:
https://doi.org/10.13052/jmm1550-4646.1952Keywords:
Smart farmer, digital farmer, project-based learning, problem-based learning, collaborative learning, Blended Learning, IoT technology, learning frameworkAbstract
One-third of Thailand’s workers are in agriculture, but the country’s agricultural GDP is still less than 10% of its total GDP. Most Thai farmers are smallholders with limited land and low incomes. To improve the agricultural GDP and the economic situation of smallholder farmers, the Thai Government has been trying for decades to encourage and support smallholder farmers to adopt modern farming methods and smart farming equipment, including digital technologies. However, the improvement is still sluggish due to a lack of an effective approach to delivering essential digital knowledge and skills, as well as investment support for smart farming equipment. These have hindered smallholder farmers’ digital farming skill progress. To address this issue, the Broadcasting and Telecommunications Research and Development Fund for Public Interest has funded a project to develop the Digital Farmer Development Framework. This framework provides essential digital knowledge, training, coaching, and fundamental resources to upgrade smallholder digital-farming literacy to become digital farmers using problem- or project-based learning approaches and collaborative blended learning theories. Bloom’s taxonomy is used as a guideline for evaluating the framework’s effectiveness. Implementation of the Digital Farmer Development Framework has shown that farmers can significantly improve their digital farming literacy and are capable of using digital technology to improve farm management and productivity. Based on Bloom classification guidelines, 100% of the farms in the project can apply digital skills and utilize fundamental smart farming equipment as well as able to evaluate and analyze data from IoT devices. Moreover, 66% can create their own smart-system solution from fundamental smart farming tools for their farm. The project has also created a digital farmer community that shares knowledge and resources with others.
Downloads
References
S. Wittayasin, “Education challenges to Thailand 4.0,” Int. J. Integr. Educ. Dev., vol. 2, no. 2, pp. 29–35, 2017.
P. Louangrath, “Thailand 4.0 Readiness,” 2017.
C. Jones and P. Pimdee, “Innovative ideas: Thailand 4.0 and the fourth industrial revolution,” Asian Int. J. Soc. Sci., vol. 17, no. 1, pp. 4–35, 2017.
P. Desatova, “Thailand 4.0 and the internal focus of nation branding,” Asian Stud. Rev., vol. 42, no. 4, pp. 682–700, 2018.
P. Potjanajaruwit and L. Girdwichai, “Creative innovation of startup businesses in Thailand 4.0 era,” J. Int. Stud., vol. 12, no. 3, 2019.
Kitja Srita, “The Employment of the Knowledge on Organic Agriculture of the Farmers in the Thailand 4.0 Era at Bang-Rachan District, Sing-Buri Province,” Tree-Science Journal, vol. 7, no. 1, pp. 37–46, 2021.
I. Zambon, M. Cecchini, G. Egidi, M. G. Saporito, and A. Colantoni, “Revolution 4.0: Industry vs. agriculture in a future development for SMEs,” Processes, vol. 7, no. 1, p. 36, 2019.
S. Wittayasin, “Education challenges to Thailand 4.0,” Int. J. Integr. Educ. Dev., vol. 2, no. 2, pp. 29–35, 2017.
P. Sethakul and N. Utakrit, “Challenges and future trends for Thai education: Conceptual framework into action,” 2019.
N. Phumma, “Various Understandings of ‘Thailand 4.0’: Hidden Conflicts,” 2019.
A. Lilavanichakul, “Development of agricultural e-commerce in Thailand,” FFTC J Agric Policy, vol. 1, pp. 7–16, 2020.
J. Leeka, P. B. N. Sachaiyan, and P. S. Sukprasert, “Community Strength Creation in Accordance with Thailand 4.0,” Multicult. Educ., vol. 7, no. 5, 2021.
C. Jones and P. Pimdee, “Innovative ideas: Thailand 4.0 and the fourth industrial revolution,” Asian Int. J. Soc. Sci., vol. 17, no. 1, pp. 4–35, 2017.
T. Berno, J. J. Wisansing, and G. Dentice, “Creative agritourism for development: Putting the ‘culture’into agriculture in Thailand,” in Tourism and Development in Southeast Asia, Routledge, 2020, pp. 197–213.
S. Apipattanavis, S. Ketpratoom, and P. Kladkempetch, “Water management in Thailand,” Irrig. Drain., vol. 67, no. 1, pp. 113–117, 2018.
B. Tarman and B. Kuran, “Examination of the cognitive level of questions in social studies textbooks and the views of teachers based on bloom taxonomy,” Educ. Sci. Theory Pract., vol. 15, no. 1, 2015.
W. Huitt, “Bloom et al.’s taxonomy of the cognitive domain,” Educ. Psychol. Interact., vol. 22, 2011.
I. Goksu, “The Evaluation of the Cognitive Learning Process of the Renewed Bloom Taxonomy Using a Web Based Expert System.,” Turk. Online J. Educ. Technol.-TOJET, vol. 15, no. 4, pp. 135–151, 2016.
J. R. Colder, “In the Cells of the ‘Bloom Taxonomy ‘,” J. Curric. Stud., vol. 15, no. 3, pp. 291–302, 1983.
I. M. Alkhasawneh, M. T. Mrayyan, C. Docherty, S. Alashram, and H. Y. Yousef, “Problem-based learning (PBL): assessing students’ learning preferences using VARK,” Nurse Educ. Today, vol. 28, no. 5, pp. 572–579, 2008.
C. Bereiter and M. Scardamalia, “Commentary on part I: Process and product in problem-based learning (PBL) research,” Probl.-Based Learn. Res. Perspect. Learn. Interact., pp. 185–195, 2000.
D. A. Kilroy, “Problem based learning,” Emerg. Med. J., vol. 21, no. 4, pp. 411–413, 2004.
S. Wells, P. Warelow, and K. Jackson, “Problem based learning (PBL): A conundrum,” Contemp. Nurse, vol. 33, no. 2, pp. 191–201, 2009.
D. F. Wood, “Problem based learning,” Bmj, vol. 326, no. 7384, pp. 328–330, 2003.
Adrian Ashman and Robyn Gillies, Cooperative Learning: The Social and Intellectual Outcomes of Learning in Groups. London: Routledge, 2003. Accessed: Sep. 03, 2022. [Online]. Available: https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=102587&site=eds-live&authtype=ip,uid
C. Nguyen, T. Trinh, D. Le, and T. Nguyen, “Cooperative Learning in English Language Classrooms: Teachers’ Perceptions and Actions,” Anatol. J. Educ., vol. 6, no. 2, pp. 89–108, Oct. 2021.
Nagata, K., and S. Ronkowski., “Collaborative learning: differences between collaborative and cooperative learning.,” 1998.
P. Baligar, G. Joshi, A. Shettar, and R. Kandakatla, “Penetration for Cooperative Learning in Engineering Education: A Systematic Literature Review,” 2022 IEEE Glob. Eng. Educ. Conf. EDUCON Glob. Eng. Educ. Conf. EDUCON 2022 IEEE, pp. 610–619, Mar. 2022, doi: 10.1109/EDUCON52537.2022.9766551.
W. Musalamani, R. M. Yasin, and K. Osman, “The Effectiveness of the School Based-Cooperative Problem Based Learning (SB-CPBL) Model in Improving Students’ Achievement in Science: Keberkesanan Model Pembelajaran Berasaskan Masalah Berasaskan Sekolah (SB-CPBL) dalam Meningkatkan Pencapaian Pelajar dalam Sains.,” Malays. J. Educ. 0126-6020, vol. 47, no. 1, pp. 75–87, May 2022, doi: 10.17576/JPEN-2022-47.01SI-06.
Y. Seyoum and S. Molla, “Teachers’ and Students’ Roles in Promoting Cooperative Learning at Haramaya, Dire Dawa, and Jigjiga Universities, Ethiopia,” Educ. Res. Int., pp. 1–11, Mar. 2022, doi: 10.1155/2022/7334592.
K. Thorne, Blended Learning: How to Integrate Online & Traditional Learning. London: Kogan Page, 2003. Accessed: Sep. 03, 2022. [Online]. Available: https://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=81879&site=eds-live&authtype=ip,uid
B. Allan, Blended learning: tools for teaching and training. Facet, 2007.
Blended learning systems. The handbook of blended learning: Global perspectives, local designs 1. 2006.
R. P. Antonio, “Effectiveness of Blended Instructional Approach in Improving Students’ Scientific Learning Outcomes: A Meta-Analysis,” J. High. Educ. Theory Pract., vol. 22, no. 5, pp. 225–243, Apr. 2022.
N. Huda, Mustaji, F. Arianto, and N. Ayubi, “The Application of Blended Learning with a Community Science Technology Approach to Improve Student Learning Outcomes in Higher Education,” Int. J. Emerg. Technol. Learn., vol. 17, no. 14, pp. 246–252, Jul. 2022, doi: 10.3991/ijet.v17i14.32927.
Handbook Digital Farming: Digital Transformation for Sustainable Agriculture. 2022.
P. O. Noack, Precision Farming – Smart Farming – Digital Farming: Grundlagen und Anwendungsfelder. 2019.
I. Aisenberg, Precision Farming Enables Climate-Smart Agribusiness. Web server without geographic relation, Web server without geographic relation (org): International Finance Corporation, Washington, DC, 2017.
Sensors Application in Agriculture. Basel, Switzerland: MDPI – Multidisciplinary Digital Publishing Institute, 2020. doi: 10.3390/books978-3-03943-259-2.
D. Honc and J. Merta, Smart, Precision or Digital Agriculture and Farming – Current State of Technology. United States, North America: Springer International Publishing, 2020. doi: 10.1007/978-3-030-57802-2_24.
