geographical boundaries [1; 2]. At present, ICT usage has proliferated in many developed countries, owing to the fact of its potential to facilitate learning, even reduce poverty, foster growth, and increase the living standards. However, despite its achievement in developed countries, ICT still holds an enormous pledge for the future world generations in developing countries, especially in African nations, by promising a favorable education [3].  
Numerous studies have shown that technology usage is not equal or proportionate all over the world. [PERSON] [4] and [PERSON] [5] point out that there is a tangible digital divide in technology across the world where some factors (e.g., continent, country, personal income level or capacity, educational background, gender, and age), among students, specifically impact the access to and usage of online learning resources. In addition, given the pace at which technology has been adopted, several people in the developing countries have had little (or no formal) education or preparation on how to use it effectively. Many people have a limited understanding of the technologies they use and/or they are often underutilizing them. Even when in a group of people, all have access to technology, it is very likely that only a small portion may be able to use it fluently [6].  
In developed countries, ICT skills significantly help the students to benefit from the distribution of education especially in the context of the higher education sector. However, in developing nations, numerous research indicate that most university students lack the necessary technology skills to take similar advantages and the digital divide is still an issue (EA as an example) [7; 8; 9]. On this account, an in-depth understanding of the determinants of ICT fluency and an investigation into the evolution of the digital divide are significant concerns for the EA and the developing countries in general.  
In regard to ICT fluency and digital divide in EA, few studies have been conducted in the context of higher education, but no study predicted the determinants of technology fluency to understand better the influences of EA regional local characteristics on undergraduate students' technology skills. Most of the studies used, instead, empirical descriptive statistic methods that describe the undergraduate students' barriers and enablers to technology skills [10; 11; 12; 13]. This paper claims that further studies are needed to understand the reality better and it steps forward by developing one model to study the determinants of ICT fluency and the other to explore the evolution of digital inequalities by class year (1 st year to 4 th year). The two models are assessed on EA undergraduate students considering the local characteristics.  
The contribution of this article is to, by integrating individual local characteristics, achieve a better understanding of the determinants of ICT fluency among EA undergraduate students. Moreover, it documents the evolution of the digital divide among them, which is beneficial to educational practitioners and policy makers in getting insights into their role to play, thus, providing excellent ICT infrastructures, increasing Internet penetration, and motivating the students to adopt technology more.