Universal Access in the Information Society

, Volume 17, Issue 2, pp 325–334 | Cite as

An analysis of the influence of a mobile learning application on the learning outcomes of higher education students

  • Aijaz Ahmed Arain
  • Zahid Hussain
  • Wajid H. Rizvi
  • Muhammad Saleem Vighio
Long Paper


This study investigated the influence of a mobile learning (M-Learning) application on the learning outcomes of university students. The learning outcomes were assessed in terms of secured score in the Communication Skills course using the App for the period of one semester. The M-Learning App was developed for university students to make learning possible from anywhere, at anytime, and through any smartphone. An experiment was conducted to measure the learning outcomes of the students. In each group (experimental and control), 106 students were randomly selected using SPSS random sample cases. The learning outcomes were measured by means of a standard test designed by three course experts. Both groups took the test at the start of the semester; the results were recorded as pre-test. However, both groups undertook the same test again at the end of the semester as a post-test; this time the questions were shuffled. The results of the experiment revealed that there is statistically significant difference between the experimental and control groups in their post-test results. The experimental group secured higher score in the post-test as compared to the control group. The findings of this study suggest that the App has positive influence on the learning outcomes of the students.


Universal accessibility M-Learning Experimental design Learning outcomes 


  1. 1.
    Crompton, H., Burke, D., Gregory, K.H., Grabe, C.: The use of mobile learning in science: a systematic review. J. Sci. Educ. Technol. 25(2), 149–160 (2016)CrossRefGoogle Scholar
  2. 2.
    Sung, Y.T., Chang, K.E., Liu, T.C.: The effects of integrating mobile devices with teaching and learning on students’ learning performance: a meta-analysis and research synthesis. Comput. Educ. 94, 252–275 (2016)CrossRefGoogle Scholar
  3. 3.
    Pimmer, C., Mateescu, M., Grohbiel, U.: Mobile and ubiquitous learning in higher education settings. A systematic review of empirical studies. Comput. Hum. Behav. 63, 490–501 (2016)CrossRefGoogle Scholar
  4. 4.
    Martin, F., Ertzberger, J.: Here and now mobile learning: an experimental study on the use of mobile technology. Comput. Educ. Chicago 68, 76–85 (2013)CrossRefGoogle Scholar
  5. 5.
    Tsai, C.W.: The use of mobile technology and ubiquitous computing for universal access in online education. Univ. Access Inf. Soc. 15, 1–2 (2014)Google Scholar
  6. 6.
    Gikas, J., Grant, M.M.: Mobile computing devices in higher education: student perspectives on learning with cellphones, smartphones & social media. Internet High. Educ. 19, 18–26 (2013)CrossRefGoogle Scholar
  7. 7.
    Matias, A., Wolf, D.F.: Engaging students in online courses through the use of mobile technology. Cutting-edge Technol. High. Educ. 6, 115–142 (2013)CrossRefGoogle Scholar
  8. 8.
    Ali, R.A., Arshad, M.R.M.: Perspectives of students’ behavior towards mobile learning (M-learning) in Egypt: an extension of the UTAUT model. Eng. Technol. Appl. Sci. Res. 6(4), 1109 (2016)Google Scholar
  9. 9.
    Al Emran, M., Shaalan, K.: E-podium technology: a medium of managing knowledge at Al Buraimi University College via M-learning. In: BCS International IT Conference, pp. 1–4 (2014)Google Scholar
  10. 10.
    Tseng, H.W., Tang, Y., Morris, B.: Evaluation of iTunes University courses through instructional design strategies and M-learning framework. J. Educ. Technol. Soc. 19(1), 199–210 (2016)Google Scholar
  11. 11.
    Meiselwitz, G., Sadera, W.: Investigating the connection between usability and learning outcomes in online learning environments. J. Online Learn. Teach. 4(2), 9 (2008)Google Scholar
  12. 12.
    Hoehle, H., Aljafari, R., Venkatesh, V.: Leveraging Microsoft’s mobile usability guidelines: conceptualizing and developing scales for mobile application usability. Int. J. Hum. Comput. Stud. 89, 35–53 (2016)CrossRefGoogle Scholar
  13. 13.
    Fetaji, B., Ebibi, M., Fetaji, M.: Assessing effectiveness in mobile learning by devising MLUAT (mobile learning usability attribute testing) methodology. Int. J. Comput. Commun. 5(3), 178–187 (2011)Google Scholar
  14. 14.
    Arain, A.A., Hussain, Z., Rizvi, W.H., Vighio, M.S.: Evaluating usability of M-learning application in the context of higher education institute. In: Proceedings of the 3rd International Conference on Learning and Collaboration Technologies, LNCS, vol. 9753, pp. 259–268. Springer (2016)Google Scholar
  15. 15.
    Tsai, C.W., Shen, P.D., Tsai, M.C., Chen, W.Y.: Exploring the effects of web-mediated computational thinking on developing students’ computing skills in a ubiquitous learning environment. Interact. Learn. Environ. 25, 1–16 (2016)Google Scholar
  16. 16.
    Huang, C.S., Yang, S.J., Chiang, T.H., Su, A.Y.: Effects of situated mobile learning approach on learning motivation and performance of EFL students. J. Educ. Technol. Soc. 19(1), 263–276 (2016)Google Scholar
  17. 17.
    Harley JM, Poitras EG, Jarrell A, Duffy MC, Lajoie SP.: Comparing virtual and location-based augmented reality mobile learning: emotions and learning outcomes. Educ. Technol. Res. Dev. 64(3), 359 (2016)CrossRefGoogle Scholar
  18. 18.
    Andujar, A.: Benefits of mobile instant messaging to develop ESL writing. System 62, 63–76 (2016)CrossRefGoogle Scholar
  19. 19.
    So, S.: Mobile instant messaging support for teaching and learning in higher education. Internet High. Educ. 31, 32–42 (2016)CrossRefGoogle Scholar
  20. 20.
    Telecom Indicators: Pakistan Telecommunication Authority, Govt. of Pakistan, pp. 2–3 (2017).
  21. 21.
    Goundar, S.: What is the potential impact of using mobile devices in education. In: Proceedings of SIG GlobDev Fourth Annual Workshop, pp. 1–30 (2011)Google Scholar
  22. 22.
    Mahmoud, Q.H.: Integrating mobile devices into the computer science curriculum. In: 2008 38th Annual Frontiers in Education Conference, pp. S3E-17–22. IEEE (2008)Google Scholar
  23. 23.
    Adorni, G., Bergenti, F., Poggi, A., Rimassa, G.: Enabling FIPA agents on small devices. In: International Workshop on Cooperative Information Agents, pp. 248–257. Springer, Berlin (2001)Google Scholar
  24. 24.
    Briz-Ponce, L., Juanes-Mendez, J.A., Garcia-Penalvo, F.J., Pereira, A.: Effects of mobile learning in medical education: a counterfactual evaluation. J. Med. Syst. 40(6), 1–6 (2016)CrossRefGoogle Scholar
  25. 25.
    Jou, M., Lin, Y.T., Tsai, H.C.: Mobile APP for motivation to learning: an engineering case. Interact. Learn. Environ. 24(8), 2048–2057 (2016)CrossRefGoogle Scholar
  26. 26.
    Rahimi, M., Miri, S.S.: The impact of mobile dictionary use on language learning. Elsevier’s Procedia Soc. Behav. Sci. 98, 1469–1474 (2014)CrossRefGoogle Scholar
  27. 27.
    Rees, C., Sheard, C., Davies, S.: The development of a scale to measure medical students’ attitudes towards communication skills learning: the Communication Skills Attitude Scale (CSAS). Med. Educ. 36(2), 141–147 (2002)CrossRefGoogle Scholar
  28. 28.
    Jahan, F., Norrish, M., Jasim, N.S., Abbas, Z.: Undergraduate medical students attitudes towards learning communication skills. Sci. J. Med. Sci. 3(11), 371–377 (2015)Google Scholar
  29. 29.
    Loureiro, E., Severo, M., Ferreira, M.A.: Attitudes of Portuguese medical residents’ towards clinical communication skills. Patient Educ. Couns. 98(8), 1039–1043 (2015)CrossRefGoogle Scholar
  30. 30.
    Haveri, S.P., Sebastian, N.M., Nath, A.S.: Attitude of medical students towards learning communication skills. Int. J. Community Med. Public Health 3(1), 157–160 (2016)CrossRefGoogle Scholar
  31. 31.
    Alotaibi, F.S., Alsaeedi, A.: Attitudes of medical students toward communication skills learning in Western Saudi Arabia. Saudi Med. J. 37(7), 791 (2016)CrossRefGoogle Scholar
  32. 32.
    Dochy, F., Segers, M., Buehl, M.M.: The relation between assessment practices and outcomes of studies: the case of research on prior knowledge. Rev. Educ. Res. 69(2), 145–186 (1999)CrossRefGoogle Scholar
  33. 33.
    Hailikari, T.K., Nevgi, A.: How to diagnose at risk students in chemistry: the case of prior knowledge assessment. Int. J. Sci. Educ. 32(15), 2079–2095 (2010)CrossRefGoogle Scholar
  34. 34.
    Muller-Kalthoff, T., Moller, J.: Browsing while reading: effects of instructional design and learners’ prior knowledge. Res. Learn. Technol. 14(2), 183198 (2006)Google Scholar
  35. 35.
    Gurlitt, J., Renkl, A.: Prior knowledge activation: how different concept mapping tasks lead to substantial differences in cognitive processes, learning outcomes, and perceived self-efficacy. Instr. Sci. 38(4), 417–433 (2010)CrossRefGoogle Scholar
  36. 36.
    Gurlitt, J., Renkl, A.: Are high-coherent concept maps better for prior knowledge activation? Differential effects of concept mapping tasks on high school vs. university students. J. Comput. Assist. Learn. 24(5), 407–419 (2008)CrossRefGoogle Scholar
  37. 37.
    Shapiro, A.M.: How including prior knowledge as a subject variable may change outcomes of learning research. Am. Educ. Res. J. 41(1), 159–189 (2004)CrossRefGoogle Scholar
  38. 38.
    Kumi, R., Conway, C.M., Limayem, M., Goyal, S.: Research article learning in color: how color and affect influence learning outcomes. IEEE Trans. Prof. Commun. 56(1), 2–15 (2013)CrossRefGoogle Scholar
  39. 39.
    Vinu, P.V., Sherimon, P.C., Krishnan, R.: Towards pervasive mobile learningthe vision of 21st century. Procedia Soc. Behav. Sci. 15, 3067–3073 (2011)CrossRefGoogle Scholar
  40. 40.
    Hutter, R.I., Oldenhof-Veldman, T., Pijpers, J.R., Oudejans, R.R.: Professional development in sport psychology: relating learning experiences to learning outcomes. J. Appl. Sport Psychol. 29(1), 1–16 (2017)CrossRefGoogle Scholar
  41. 41.
    Aboukhatwa, E.A.: Blended learning as a pedagogical approach to improve the traditional learning and e-learning environments. In: The Second International Arab Conference on Quality Assurance in Higher Education (IACQA), pp. 1061–1067 (2012)Google Scholar
  42. 42.
    Yang, J.C., Lin, Y.L.: Development and evaluation of an interactive mobile learning environment with shared display groupware. Educ. Technol. Soc. 13(1), 195–207 (2010)MathSciNetGoogle Scholar
  43. 43.
    Yang, J.C., Chen, C.H., Jeng, M.C.: Integrating video-capture virtual reality technology into a physically interactive learning environment for English learning. Comput. Educ. 55(3), 1346–1356 (2010)CrossRefGoogle Scholar
  44. 44.
    Bagheri, Z., Mahmoudi, A.: The effects of method, time and their interaction on learning grammatical cohesive devices. Theory Pract. Lang. Stud. 6(2), 423 (2016)CrossRefGoogle Scholar
  45. 45.
    Huang, R.: A study on large-class teaching strategies in listening for English major on web-based autonomous learning. In: 2nd International Conference on Education, Language, Art and Intercultural Communication (ICELAIC 15), pp. 265–269. Atlantis-press (2016)Google Scholar
  46. 46.
    Benitti, F.B.V., Sommariva, L.: Evaluation of a game used to teach usability to undergraduate students in computer science. J. Usability Stud. 11(1), 21–39 (2015)Google Scholar
  47. 47.
    Mackey, T.P., Ho, J.: Exploring the relationships between Web usability and students’ perceived learning in Web-based multimedia (WBMM) tutorials. Comput. Educ. 50(1), 386–409 (2008)CrossRefGoogle Scholar
  48. 48.
    Lim, D.H., Morris, M.L.: Learner and instructional factors influencing learning outcomes within a blended learning environment. Educ. Technol. Soc. 12(4), 282–293 (2009)Google Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Aijaz Ahmed Arain
    • 1
  • Zahid Hussain
    • 1
  • Wajid H. Rizvi
    • 2
  • Muhammad Saleem Vighio
    • 1
  1. 1.Quaid-e-Awam University of Engineering, Science and TechnologyNawabshahPakistan
  2. 2.Institute of Business AdministrationKarachiPakistan

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