## 4 Results
### Measurement Model Validation  
The quality of the items was assessed in terms of their reliability and validity. Reliability refers to the extent to which a test is likely to yield the same results in case of repetition. On the other hand, the validity reflects the level at which an item effectively measures what it wants to measure [81]. Construct validity and reliability were evaluated in terms of internal consistency through Cronbach's Alpha (CA), the Average Variance Extracted (AVE), and the composite reliability (CR). Similarly to the study by [PERSON] and [PERSON] [82], we verified the following criteria suggested by [PERSON] et al. [83] to ensure the validity and reliability of the measured constructs in the present study. * Item loadings should exceed 0.7 [84; 85]. * Composite reliability (CR) must be greater than 0.7 [86; 87]. * The average variance extracted (AVE) for each factor should be larger than 0.5 [88]. \begin{table}
\begin{tabular}{l l c c} \hline \hline \multicolumn{2}{c}{**Characteristic**} & \multicolumn{1}{c}{**Frequency**} & \multicolumn{1}{c}{**Percentage**} \\ \hline Gender & Female & 23 & 58\% \\  & Male & 19 & 45\% \\ Age & 20–35 years & 19 & 45\% \\  & 36–50 years & 8 & 19\% \\  & More than 50 years & 15 & 36\% \\ Education Level & Literature w/o qualification & 3 & 7\% \\  & School & 5 & 12\% \\  & Graduate & 16 & 38\% \\  & Post-Graduate & 18 & 43\% \\ Frequency of computer use & High & 24 & 57\% \\  & Moderate & 9 & 21\% \\  & Low & 6 & 14\% \\  & Sparse & 3 & 7\% \\ Experience in similar systems & No & 13 & 31\% \\  & Yes & 29 & 69\% \\ Experience in agro-activities & More than 20 years & 9 & 21\% \\  & 11–20 years & 6 & 14\% \\  & 5–10 years & 8 & 19\% \\  & Less than 5 years & 19 & 45\% \\ Total of participants & & 42 & 100.0\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Basic information of the sample. * Cronbach's coefficient alpha (CA) should be above 0.7 [89]. The discriminant validity (DV) is also frequently reported in similar TAM validations as in the work by [PERSON] et al. [90]. The discriminant validity examines the extent to which the scale measuring a specific construct is different from the ones of other constructs [88]. Based on the criterion established by [PERSON] and [PERSON] [88], a model has acceptable discriminant validity if the variance that a variable has with its constructs is higher than the variance shared by the variable with the others. After running the PLS algorithm, some of the items showed loadings below 0.7, the minimum suggested to ensure reliability, and therefore were no longer considered. A second calculation was run after dropping the items EXP2, EXP3, and PEOU3. Results of the second run are depicted in Table 5.  
Mean scores for almost all the variables were higher than the midpoint value of the scale, 3.5, except for anxiety. This indicates that most of the respondents did not experience stress of negative feelings when interacting with the e-learning tool. Standard deviation values ranged from 1.002 to 1.661, showing that values are moderately spread around the mean. All the constructs showed satisfactory levels of validity and reliability. Loadings of all items were higher than 0.7. Composite reliability for all constructs was above the 0.7 threshold, with values from 0.870 to 1.000. AVE scores ranged from 0.692 to 1.000, exceeding the 0.5 as suggested by the literature. [PERSON]'s Alphas were higher than 0.7, ranging from 0.777 to 1.000. Discriminant validity of the model was also satisfactory as shown in Table 6. The square root of the AVE of each variable (value in the diagonal) is higher than the other correlation values. Therefore, the measurement model was validated.