Authors : Ladan, E.O.; Oyefolahan, I.O.; Joseph, S.I.

Volume/Issue : Volume 11 - 2026, Issue 1 - January

Google Scholar : https://tinyurl.com/yecs8kv5

Scribd : https://tinyurl.com/ycx2xuww

DOI : https://doi.org/10.38124/ijisrt/26jan1093

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

Abstract : The research focuses on how RiceAdvisor, a mobile Knowledge-Based System (KBS), has been developed and used to improve agricultural extension education for rice farmers and extension workers in Kaduna State, Nigeria. It addresses the need for more digital innovation in the Nigerian agricultural extension service and the need to reduce the impact of the inefficiencies that face the extension education service, such as inadequate human resources, poor infrastructure, and the inefficiencies that come with face-to-face interactions. A mixed-method approach was used, with the 150 respondents (120 rice farmers and 30 agricultural extension agents) surveyed using structured questionnaires providing quantitative data, while in system testing, the qualitative data used were from expert interviews and users. Built using Flutter, Dart, and SQLite, the RiceAdvisor App provides offline/online Access to e-learning modules, real-time consulting, weather updates, and a chatbot providing conversational advisory services. The study having a sample size of 150 respondents in Kaduna State limits how the results of the study can be applied to other rice-producing areas in Nigeria with other socio-cultural and agro-ecological characteristics; therefore, these results being able to be generalized are weak, which means more studies with larger sample size and more varied diversity in the sample will improve the external validity of the studies. The App was assessed using the System Usability Scale (SUS) and the Technology Acceptance Model (TAM) was evaluated using PLS-SEM. This yielded a SUS score of 76.5, which is above the acceptable usability score of 70. Respondents rated rice production management (x̅=4.69, SD=0.47), disease diagnosis (x̅=4.65, SD=0.48) and the chatbot (x̅=4.65, SD=0.46) as the most valuable features. Results substantiated positive correlations among perceived usefulness, perceived ease of use, and behavioural intention. The findings indicate the growing potential of digital intelligent systems to augment the learning and decision-making opportunities available in agriculture. Knowledge-oriented digital platforms, like RiceAdvisor, can improve the efficiency of agricultural extension services by helping weaken the overburdened extension systems, improving the farmer-to-extension-agent ratio, and improving advisory service delivery. Integrating RiceAdvisor into national extension programs is suggested in the context of rural digital inclusion and Nigerian sustainable rice farming development.

Keywords : Knowledge-Based Systems, Agricultural Extension, RiceAdvisor, Digital Agriculture, Sustainable Development

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