During the last decade, information and communication technology has brought remarkable changes to the education style of developed countries, especially in the context of online learning materials accessibility. However, in developing nations such as the East African (EA) countries, university students may lack the necessary ICT training to take advantage of e-learning resources productively. Therefore, the comprehension of the key factors behind ICT fluency is a significant concern for this region and all the developing countries in general. This paper applies the Concentration Index and proposes a Logistic Regression based model to discover the key determinants of ICT fluency and to explore the evolution of the digital divide among EA students within the four years of undergraduate studies. To identify the principal determinants, data composing of 1237 participants is collected from three different universities in EA within a one year period. The experimental results indicate that the digital divide among students decreases quite fast from the first year to the fourth year. Regression computational findings show that the key determinants of ICT fluency are the student urban/rural origin, computer ownership, computer experience, class year, and major. The findings provide heuristic implications for developers, practitioners, and policy makers for an improved ICT environment implementation in EA and the developing nations in general.

This study focused on the relationships between knowledge mapping construction methods and learning performance. The different knowledge mapping methods (by experts vs. by self-learners) were assumed to achieve different learning performance levels. The results of this study show that neither different knowledge map construction methods nor learning styles significantly influenced individual learning performance. Either of the knowledge map construction methods applied to the programming language learning and the learning scores are significantly higher than average. Learning style does not moderate knowledge map construction methods on learning scores. However, learning style is a significant moderator of knowledge map construction methods on learning satisfaction. Different knowledge map construction methods should be considered with different learning styles to significantly increase learning satisfaction. The results could be used to design effective programming language learning materials.