Mobile technology has evolved systematically to attract millions of users over the past decade. The prominence of mobile technology can be pinned on three main areas as discussed by different authors. These areas include mobile cloud computing, mobile data mining, and mobile prediction analysis.
Mobile Cloud Computing
Mobile cloud computing continues to record success with the advent of smartphones. According to Hoang, Chonho, Wang (2013), the mobile cloud computing has significantly influenced various aspects of life especially in areas such as research. Individuals, as well as organizations, can carry out research activities with much ease. Increased usages of Smartphone among people from all over the world continue to enrich mobile computing.

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Mobile data mining
Sing and Ranjan (2016) conducted research involving university students to explore the concept of data mining that has been accelerated with the introduction of Internet-enabled phones, and the modern smartphones, which continue to be one of the receptors of mobile technology. The authors relied on qualitative research methods and established that mobile phones are the most popular and fast way of accessing a wealth of information among university students. The ability of internet-enabled phones to integrate information on a single platform has enhanced data mining with ease of access and retrieval of all sorts of data needed. Today, mobile phones continue to lead as a source of data among university students and fast changing pace in the corporate world.

Mobile Prediction Analysis
The use of cell phones cannot be underrated in the present society where many things are interlinked with the utilization of these valuable gadgets. In their work, Yang, Li, and Lu (2015) posit that mobile phones are very useful in predicting behavior. A qualitative research they conducted using university students showed that students demonstrated a high concentration behavior towards shared resources. Such observations made it possible for the researchers to conclude that many students can be pulled together through using a mobile platform to post information that interest them. Therefore, cell phones are effective in prediction analysis.

  • Hoang, T. D., Chonho, L., & Wang, P. (2013). A survey of mobile cloud computing: architecture, applications, and approaches. Wireless Communications and Mobile Computing Volume 13, Issue 18 , 1587–1611.
  • Singh, A., & Ranjan, J. (2016). A framework for mobile apps in colleges and universities: Data mining perspective . Education and Information Technologies. Vol. 21 Issue 3 , p643-655.
  • Yang, X., Li, X., & Lu, T. (2015). Using mobile phones in college classroom settings: Effects of presentation mode and interest on concentration and achievement. Computers & Education 88 , 292-302.