A Comparative Analysis of Traditional Vs. Digital Adult Literacy Models in Enhancing Agripreneurial Competencies Among Small-Scale Farmers in Lagos State, Nigeria

Abstract

The study evaluated the efficiency of using conventional models, which involve face-to-face and paper-based methods, against those using technological platforms to improve agripreneurial skills among smallholder farmers in Lagos State, Nigeria. As rural regions become more urbanized, and demands in the market increase, it is important to determine whether digital models will help farmers develop skills. A descriptive survey design was adopted. Two hundred questionnaires were distributed to purposively selected farmers across five communities (Ikorodu, Badagry, Epe, Agege, and Ajah) representing the IBILE divisions, with 98 valid responses (49 per group) analysed. Data were collected using a structured questionnaire with simple farmer-friendly language (validated by three experts from the Agricultural and Adult education Departments with a reliability coefficient of 0.87 using Cronbach’s Alpha) and analysed with descriptive statistics (mean and standard deviation) and independent samples t-test via SPSS version 27. Results showed that farmers exposed to the digital-first model acquired significantly higher agripreneurial competencies (Grand Mean = 3.40, SD = 0.66) compared to those in the traditional model (Grand Mean = 2.34, SD = 0.83). The independent samples t-test confirmed a statistically significant difference (t = -8.15, p < 0.001), with the digital-first model proving superior across all domains. The study concludes that digital-first adult literacy models are markedly more effective in building modern agripreneurial competencies. It recommends the adoption of hybrid or digital-first programmes, investment in rural digital infrastructure, and training of extension agents in digital facilitation skills to enhance small-scale farmers’ competitiveness in Lagos State.