Authors : Dr. Kosea Erasto Muwanga; Amoah John

Volume/Issue : Volume 11 - 2026, Issue 9 - September

Google Scholar : https://tinyurl.com/dm2mmrxj

DOI : https://doi.org/10.38124/ijisrt/26sep1318

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Digital tools can make livestock information easier to reach, but simply putting information on a phone does not guarantee that farmers will find it useful, understandable, or trustworthy. This study examined CARE4ANIMALS, a multilingual mobile microlearning platform designed to provide short, practical animal-welfare lessons through a Progressive Web App (PWA) and Short Message Service (SMS). The study involved 150 livestock farmers from Central, Western, Eastern, and Northern Uganda and combined quantitative measures with interviews and focus-group discussions. The quantitative assessment covered perceived usefulness, ease of use, accessibility, language suitability, content relevance, satisfaction, trust, intention to continue, and overall usability measured with the System Usability Scale (SUS)

Keywords : Digital Agricultural Extension; Mobile Microlearning; Animal Welfare; Technology Acceptance; Livestock Farmers; Uganda; System Usability Scale; Digital Inclusion.

References :

1. Aker, J. C. (2011). Dial “A” for agriculture: A review of information and communication technologies for agricultural extension in developing countries. Agricultural Economics, 42(6), 631–647. https://doi.org/10.1111/j.1574-0862.2011.00545.x
2. Brooke, J. (1996). SUS: A “quick and dirty” usability scale. In P. W. Jordan, B. Thomas, B. A. Weerdmeester, & I. L. McClelland (Eds.), Usability evaluation in industry (pp. 189–194). Taylor & Francis. https://doi.org/10.1201/9781498710411-35
3. Chenais, E., Fischer, K., Kagolobya, R., Dione, M., Ståhl, K., & Sternberg-Lewerin, S. (2025). Drama-based mobile phone-delivered virtual learning as a way to support improved biosecurity in smallholder pig farming. Discover Viruses, 2, Article 25. https://doi.org/10.1007/s44370-025-00031-y
4. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
5. Muromba, P., Keeni, M., & Fuyuki, K. (2025). A systematic review of mobile agricultural service applications for smallholder farmers in sub-Saharan Africa: Perspectives from the technology acceptance model. Agriculture & Food Security, 14, Article 34. https://doi.org/10.1186/s40066-025-00563-y
6. Padmaningrum, D., Mani, L., Retnaningtyas, T. A., Sujatmiko, T., Subejo, S., & Widiyanti, E. (2024). A perspective of technology acceptance model on the agriculture extension staffs using cyber extension. Agrisocionomics: Jurnal Sosial Ekonomi Pertanian, 8(3), 637–656.
7. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186–204.
8. Welttierschutzstiftung. (2025). Research grants 2025: CARE4ANIMALS: A microlearning platform for empowering farmers with bite-sized animal wellness knowledge.
9. World Bank. (2025). Can AI give small-scale producers the right advice? World Bank Blogs.