Technology-Enhanced Learning in Agricultural Extension and Farmers' Economic Performance: The Mediating Role of Digital Literacy
Postgraduate School, Universitas Pendidikan Ganesha, Singaraja 81116, Indonesia
Universitas Pendidikan Ganesha, 81116 Bali, Indonesia
Universitas Pendidikan Ganesha, 81116 Bali, Indonesia
Universitas Pendidikan Ganesha, 81116 Bali, Indonesia
DOI: https://doi.org/10.36956/rwae.v7i3.2941
Received: 24 November 2025; Published: 14 July 2026
Copyright © 2026 Jiaming Yang Yang, Luh Putu Artini, I Wayan Sukra Warpala, Made Hery Santosa. Published by Nan Yang Academy of Sciences Pte. Ltd..
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Abstract
The digital transformation of agriculture has created new opportunities for smallholder farmers, yet the mechanisms through which technology-enhanced learning (TEL) translates into economic gains remain underexplored. This study investigates how technology-enhanced learning in agricultural extension education affects farmers' economic performance, with a specific focus on digital literacy as a mediating mechanism and the moderating roles of education level and extension service contact. Using survey data from 486 farmers across three provinces in China (2024), we employ hierarchical regression analysis, mediation analysis with bootstrapping, and heterogeneity analysis through group-wise regressions, with digital literacy measured as a composite index capturing information acquisition ability and technology adoption willingness. Results show that TEL participation significantly enhances farmers' annual income (β = 0.285, p < 0.01), with digital literacy mediating 30.2% of this total effect through two pathways: information acquisition (accounting for 53.5% of the mediated effect) and technology adoption (accounting for 46.5% of the mediated effect). Heterogeneity analysis reveals significant education-based gradients (Chow test F = 8.42, p < 0.001), with effects increasing from β = 0.218 (p < 0.05) for low-educated farmers to β = 0.395 (p < 0.001) for highly educated farmers, while age-based differences are also significant (Wald test χ² = 9.18, p = 0.002) and regional effects remain stable (p = 0.596). Digital literacy serves as a critical mediator in converting technology-enhanced learning into economic outcomes, with education and age significantly moderating this process, suggesting that policy interventions should prioritize digital skill development, particularly for low-educated and older farmers who face greater barriers to digital transformation.
Keywords: Technology‑Enhanced Learning; Information Acquisition; Technology Adoption; Human Capital; Medi‑ ation Analysis; Rural Development; China
