## 6 Results Analysis
### RQ1: Determinants of ICT Fluency  
The assumption of the study was that ICT fluency among students is represented by proxy variables of ICT usage and ICT access (computer ownership and Internet connection); and increasing level of education and training on computer knowledge. In Table 7, logistic regression estimates of the determinants of Internet access indicate that, in general, computer experience, capacity levels, computer property, and class year proxy variables increase in probabilities from the 1 st year to the 4 th year. Apart from that, more significant changes (from negative to positive) are occurring, especially when referring to the likelihood of Internet access by the females and no PC owners students during the four years. For example, there is higher Internet access among 3 rd and 4 th years' students. The students from rural areas show a reduced likelihood of Internet access, more significant in the 1 st year, which is possibly because of a lack of prior computer experience. \begin{table}
\begin{tabular}{l c c c} \hline \hline \multicolumn{1}{c}{**Dep. Variable**} & \multicolumn{3}{c}{**Variation of Determinants**} \\ \hline  & **1 st Year** & **2 nd Year** & **3 rd Year** & **4 th Year** \\ \hline Female & \(-\)0.080 *** (0.010) & \(-\)0.057 *** (0.008) & \(-\)0.008 *** (0.008) & 0.048 *** (0.008) \\ Age \(>\)18 & \(1.865\) *** (0.031) & \(1.626\) *** (0.032) & \(1.371\) *** (0.033) & \(1.571\) *** (0.034) \\ Age \(>\) 30 & \(-\)0.632 *** (0.022) & \(-\)0.693 *** (0.025) & \(-\)0.737 *** (0.028) & \(-\)0.828 *** (0.037) \\ Computer owners & \(0.208\) *** (0.026) & \(0.264\) *** (0.026) & \(0.260\) *** (0.027) & \(0.264\) *** (0.029) \\ Computer experience & \(0.230\) *** (0.013) & \(0.243\) *** (0.013) & \(0.252\) *** (0.013) & \(0.270\) *** (0.014) \\ Class year size & \(0.229\) *** (0.019) & \(0.225\) *** (0.018) & \(0.197\) *** (0.018) & \(0.166\) *** (0.017) \\ No PC owners within class & \(0.122\) *** (0.032) & \(-\)0.197 *** (0.031) & \(-\)0.012 *** (0.031) & \(-\)0.116 *** (0.029) \\ PC owners within class & \(-\)0.248 *** (0.032) & \(-\)0.364 *** (0.032) & \(-\)0.311 *** (0.032) & \(-\)0.256 *** (0.036) \\ Computer Attitude & \(0.985\) *** (0.024) & \(0.994\) *** (0.025) & \(1.044\) *** (0.025) & \(1.248\) *** (0.026) \\ Urban & \(-\)0.092 *** (0.046) & \(0.212\) *** (0.047) & \(0.223\) *** (0.048) & \(0.267\) *** (0.049) \\ Rural & \(-\)1.295 *** (0.079) & \(-\)1.300 *** (0.057) & \(-\)1.440 *** (0.046) & \(-\)1.271 *** (0.043) \\ Parents & \( \begin{array}{c}\text{Educational attainment}\\ \text{Family size}\\ \text{Income per capita}\\ \text{Employment status}\\ \text{Employed}\\ \text{Umemployed}\\ \text{Retiered}\\ \text{Constant}\\ \text{R}^{2}\\ \text{Observations}\\ \text{477}\end{array} \) & \  
By examining empirical data in Table 2, there is evidence of improvements in Internet access from the 1 st year to the 4 th year: there are higher rates of computer owners, computer experience, and capacity in income among EA university students. Moreover, regarding the proxy variables of access to ICT, Internet access and PC property are increasing significantly. Relating to the main determinants of computer property, similar effects like those observed for Internet access are identified. Higher capacity in income and prior computer experience, being urban as well, affect the likelihood of computer property in EA undergraduate students positively, as shown in Table 8. Moreover, from the 1 st year to the 4 th year, there is an increasing likelihood of computer ownership among the students that are no computer owners, but with higher prior computer experience (i.e., as they get in the 2 nd, 3 rd, and 4 th year), while the effect of rural origin is declining. Contrariwise, we found evidence of declining influences for some determinants (e.g., class year and being female) of computer property.