Enhancing E-Learning Using Smart Mobile English Learning Tool (SMELT)

  • Nnaekwe Uchenna Kingsley
  • Norlia Mustaffa
  • Pantea KeikhosrokianiEmail author
  • Keyvan Azimi


With the recent advancement in the technological world and the adult learners’ growing desire to have flexibility with their learning tool, such that it allows them to learn even while on the move and while they play games, hence the need for mobile devices that enhances teaching and learning in a virtual classroom environment. Mobile devices can be used in both online setting and in the brick-and-mortar (traditional setting). Different people are able to learn in different ways. People tend to learn better, when they are made to discover learning themselves. In line with this, a design of a mobile app known as Smart Mobile English Learning Tool (SMELT) for adult learners is presented here. This application is intended to help second language speakers to improve their English communication ability. It will also be useful for adults looking for job placements or moving up the corporate ladder in their workplaces. In order to develop SMELT, we have conducted a preliminary study and illustrated the results in this paper. The preliminary study enable us to determine the need of such a learning tool that will aid learners improve their English, even while on the move. Based on these results, a conceptual model on the proposed SMELT application to enhance E-Education is described here. The proposed application hopefully can improve the efficiency, robustness, and reliability of E-Education for the adult learners to improve their English communication ability.


Mobile device Location-based services Mobile learning (M-learning) E-learning 



The authors are grateful to School of Computer Sciences of Universiti Sains Malaysia (USM) for their support in the form of incentive grant and dedication in producing research papers.


  1. Easton, M. (1980). Batch throughput efficiency of ADCCP/HDLC/SDLC selective reject protocols. Communications, IEEE Transactions on, 28(2), 187–195.CrossRefGoogle Scholar
  2. Huanglingzi, L., Ronghuai, H., Salomaa, J., & Ding, M. (2008, March 23–26). An activity-oriented design framework for mobile learning experience. Paper presented at the Wireless, Mobile, and Ubiquitous Technology in Education, 2008. WMUTE 2008. Fifth IEEE International Conference on.Google Scholar
  3. Ktoridou, D., & Eteokleous, N. (2005). Adaptive m-learning: Technological and pedagogical aspects to be considered in Cyprus tertiary education. Recent Research Developments in Learning Technologies, 676–683.Google Scholar
  4. Neo, M. (2003). Developing a collaborative learning environment using a web‐based design. Journal of Computer Assisted Learning, 19, 462–473.CrossRefGoogle Scholar
  5. Patten, B., Arnedillo Sánchez, I., & Tangney, B. (2006). Designing collaborative, constructionist and contextual applications for handheld devices. Computers & Education, 46(3), 294–308.CrossRefGoogle Scholar
  6. Sandberg, J., Maris, M., & de Geus, K. (2011). Mobile English learning: An evidence-based study with fifth graders. Computers & Education, 57(1), 1334–1347.CrossRefGoogle Scholar
  7. Shute, V., & Towle, B. (2003). Adaptive e-learning. Educational Psychologist, 38(2), 105–114.CrossRefGoogle Scholar
  8. Wickremaratne, J., Wimalaratne, G., & Goonetilleke, V. (2008). A blend of adaptive and digital learning towards language oroficiency. Paper presented at the Information and Automation for Sustainability, 2008. ICIAFS 2008. 4th International Conference on.Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  • Nnaekwe Uchenna Kingsley
    • 1
  • Norlia Mustaffa
    • 1
  • Pantea Keikhosrokiani
    • 1
    Email author
  • Keyvan Azimi
    • 2
  1. 1.School of Computer SciencesUniversiti Sains MalaysiaGelugorMalaysia
  2. 2.School of Electrical EngineeringUniversiti Sains MalaysiaGelugorMalaysia

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