## 2 Research Background
### The Technology Acceptance Model  
The adoption of new products and systems is the pinnacle of a successful design process. To increase the likelihood of success, in the last few decades, designers and academics have developed human-centered approaches to better understand what moves users to accept innovation, especially considering the fast pace of development of ICTs and their increasing influence in daily activities [19]. The pioneering theories and frameworks in the literature explaining user's motivations towards technology use based their hypotheses on the field of psychology [19]. The frameworks that have received more attention from the academic community are the Theory of Reasoned Act (TRA) [20]; the Model of PC Utilization (MPCU) [21], the Technology Acceptance Model (TAM) [17], the Social Cognitive Theory (SCT) [22], the Theory of Planned Behavior (TPB) [23], the Innovation Diffusion Theory (IDT) [24], the Theory of Task-technology fit (TTF) [25], and the Unified Theory of Acceptance and Use of Technology (UTAUT) [26]. Very often, the above-mentioned models and theories borrow elements from previous and complementary frameworks to achieve a better prediction of technology adoption as the Unified Theory of Acceptance and Use of Technology. However, for the assessment of Information Systems acceptance, the most diffused model is the TAM and its subsequent versions [11; 27]. The Technology Acceptance Model (TAM) was initially proposed by [PERSON] [17] to explain and predict computer technology adoption. In this model, [PERSON] stated that for technology to be accepted, the performance of a given activity should be superior with the use of the technology than without it, and the value-added should be easy to identify. Furthermore, the second determinant of acceptance was the easiness of use of the technology; the more effortless the use, the higher the chances of using it daily. Those two main determinants, namely _perceived usefulness_ (PU) and _perceived ease of use_ (PEOU), are responsible for the attitude users formed about the convenience of the technology, which in turn shape their intention to adopt it or not. The strength of the intention will determine the final acceptance. In the initial TAM version, highly influenced by the TRA [20], [PERSON] theorized the existence of a causal relationship between the two main determinants, PU and PEOU, and the Attitude towards use (ATT). The role of Behavioral Intention (BI) was considered in a subsequent TAM version thanks to the contributions of the authors of the TPB. BI  
Figure 2: FARMER 4.0 Moodle. was included to represent humans' rational behavior of using the available information to decide whether to do something or refrain themselves. The first modified version of the TAM is shown in Figure 3.  
As TAM research's body increased, so did the exploration of the social and cognitive processes responsible for PU and PEOU. Subsequent work by [PERSON] and [PERSON] [28] complemented the framework by going further on the analysis of Perceived Usefulness. Their findings suggest that social factors such as social pressure or social norm and image, as well as result-oriented aspects such as job relevance, output quality, and result demonstrability could have an incidence in the perception of usefulness, mediated in some cases for previous experience with similar technologies. This extended model is known as TAM 2. A third general version, TAM 3, was proposed by [PERSON] and [PERSON] [29]. This version posits computer self-efficacy, external control, anxiety, playfulness, perceived enjoyment, and usability, as determinants of PEOU. Moreover, TAM 3 provides theoretical support indicating the mutual independence of factors influencing Perceived Ease of Use and those determining Perceived Usefulness. Thanks to the flexibility of the TAM, several different extensions have been proposed based on the research objectives, context, and the nature of the technology.