## 6 Conclusions  
The present study corresponds to the validation phase of a project aimed at evaluating farmers and agricultural entrepreneurs' intention to use an e-learning platform. This paper's general objective was to assess technology acceptance through the validation of an extended TAM version previously proposed by [PERSON] et al. for the specific context of FARMER 4.0. After an initial analysis of the TAM proposed by [PERSON] et al., almost all the relationships were validated except for the effect of perceived ease of use (PEOU) on the attitude (ATT). Findings suggest that the degree to which farmers perceive the system as easy to use (PEOU) will affect their idea about its usefulness (PU). If they perceive the tool as useful (PU), they will have a positive attitude towards it (ATT) and therefore will have the intention to use it (BI). As a technology acceptance measurement tool, the TAM provides flexibility to explore several extensions and find the one that better fits the technology context. This aspect of the model is advantageous considering the increasing complexity and variety of contexts in which e-learning tools are being applied. Although the initial TAM extension provided a neutral fit for FARMER 4.0, it offers a handy starting point to assess technology acceptance in agriculture, e-learning, and similar sectors. In our case study, further analysis showed that farmers perceived the tool to be useful (PU) based on the content's quality (CQ). On the other hand, the perception about ease of use (PEOU) was influenced by farmers' experience with similar systems (EXP) and their confidence in their skills to explore and use the system and overcome any problem they might face when using the platform (SE). Positive perceptions about the usefulness of the tool (PU) have a positive effect on farmer's attitudes (ATT). Subsequently, the attitude (ATT) stands out as the main driver of intention to use (BI). The ease of use (PEOU) will also reinforce the intention to use FARMER 4.0 (BI). The design and development of future e-learning initiatives should give special attention to the identified factors to increase the likelihood of technology adoption. Although the sample size of 42 was suitable for the PLS assessment, replicating the analysis with a larger sample size is advisable to confirm and complement the obtainedresults once all the modules in the five languages are complete. However, infrastructure and resource-related barriers should be overcome to make the most out of the platform. [PERSON] et al. (2010) pointed out the importance of facilitating access to electricity and internet connectivity in rural areas where target users develop their daily activities. Improvements in those directions will increase the incentives to adopt technological tools like e-learning in the agricultural context. Finally, it is crucial to consider the ongoing generational shift in farming activities and how tools like FARMER 4.0 can support it. [PERSON] et al. (2012) found out that high levels of education among farmers can accelerate generational changes. In this sense, access to e-learning tools with farming-related content could speed up the transition to the so-called agriculture 4.0, taking advantage of young people's propensity to adopt technological solutions in their daily lives. The increasing interest of young adults in farming-related activities, as evidenced by 45% of respondents with ages between 20 and 35 years, represents an opportunity to further develop e-learning applications in the agricultural sector. Conceptualization, L.C.C.G., I.A.C.J., F.M. and M.G.V. ; data curation, L.C.C.G. and I.A.C.J. ; formal analysis, L.C.C.G., I.A.C.J., F.M., and M.G.V. ; funding acquisition, M.G.V. ; investigation, L.C.C.G. and I.A.C.J. ; methodology, I.A.C.J. and L.C.C.G. ; supervision, F.M., M.G.V., I.A.C.J., and E.V. ; visualization, F.M., I.A.C.J., and L.C.C.G. ; writing--original draft, L.C.C.G. and I.A.C.J. ; writing--review and editing, L.C.C.G., I.A.C.J., F.M., M.G.V., and E.V.