Skip to main content
Log in

Learner characteristics of m-learning preferences

  • Original Research
  • Published:
International Journal of Information Technology Aims and scope Submit manuscript

Abstract

Now, mobile devices extend learning to any location and time, where students adopt different preferences to learn effectively and efficiently through mobile devices. However, podcasting learning materials to mobile learners involves considerable challenge because of ongoing changes in the behaviour of learners in different contexts. This paper explores mobile learning (m-learning) preferences in tertiary education in order to suggest the best approaches to deliver digital learning materials (podcasts) in different contexts which are physical spaces (e.g. quiet, busy, or walking), and social spaces (e.g. alone, family, or with classmates). A total of 345 students completed a survey study to identify the role of mobile learners’ characteristics (gender, age, material status, nationality: Australians and Saudis, and prior m-learning experience) and their impact on podcast preferences in different physical and social spaces. Based on the survey results, in this paper, we shall present the impact characteristics on m-learning preferences for podcast length and types. We shall also summarise the affected contexts and their causes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Karimi S (2016) Do learners’ characteristics matter? An exploration of mobile-learning adoption in self-directed learning. Comput Human Behav 63((Supplement C)):769–776

    Article  Google Scholar 

  2. Kobayashi M (2017) Students’ Media Preferences In Online Learning. Turk Online J Distance Educ 18(3):4–15

    Article  Google Scholar 

  3. Phillips BJ, Grosch M, Laosinchai P (2014) Mobile media usage by undergraduates and implications for m-learning instructional design. Int J Mob Learn Organ 8(1):1–15

    Article  Google Scholar 

  4. Cassidy ED, Colmenares A, Jones G, Manolovitz T, Shen L, Vieira S (2014) Higher education and emerging technologies: shifting trends in student usage. J Acad Librariansh 40(2):124–133

    Article  Google Scholar 

  5. Matava CT, Rosen D, Siu E, Bould DM (2013) eLearning among Canadian anesthesia residents: a survey of podcast use and content needs. BMC Med Educ 13(1):59

    Article  Google Scholar 

  6. Parson V, Reddy P, Wood J, Senior C (2009) Educating an iPod generation: undergraduate attitudes, experiences and understanding of vodcast and podcast use. Learn Media Technol 34(3):215–228

    Article  Google Scholar 

  7. Rodgers TL, Mabley S, Garforth AA (2017) Understanding student use of resources in “rich-media” courses. Educ Chem Eng 20((Supplement C)):22–31

    Article  Google Scholar 

  8. Copley J (2007) Audio and video podcasts of lectures for campus-based students: production and evaluation of student use. Innov Educ Teach Int 44(4):387–399

    Article  Google Scholar 

  9. Kukulska-Hulme A, Sharples M, Milrad M, Arnedillo-Sanchez I, Vavoula G (2009) Innovation in mobile learning: a european perspective. IGI Global 1(1):13–35

    Google Scholar 

  10. Al-Ismail M, Gedeon T, Sankaranarayana R, Yamin M (2016) Big 5 personality traits affect m-learning preferences in different contexts and cultures. In: 2016 3rd international conference on computing for sustainable global development (INDIACom)

  11. Al-Ismail M, Gedeon T, Yamin M (2017) Effects of personality traits and preferences on m-learning. Int J Inf Technol 9(1):77–86

    Google Scholar 

  12. Bouhnik D, Alona Y-T (2016) Students’ positions regarding academic use of smart devices. Int J Innov Res Sci Technol 2:71–77

    Google Scholar 

  13. Bao Y, Xiong T, Hu Z, Kibelloh M (2013) Exploring gender differences on general and specific computer self-efficacy in mobile learning adoption. J Educ Comput Res 49(1):111–132

    Article  Google Scholar 

  14. Kang H, Lundeberg M, Wolter B, delMas R, Herreid CF (2012) Gender differences in student performance in large lecture classrooms using personal response systems (‘clickers’) with narrative case studies. Learn Media Technol 37(1):53–76

    Article  Google Scholar 

  15. Padilla-Meléndez A, del Aguila-Obra AR, Garrido-Moreno A (2013) Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario. Comput Educ 63:306–317

    Article  Google Scholar 

  16. Yoo SJ, Huang W-HD, Kwon S (2015) Gender still matters: employees’ acceptance levels towards e-learning in the workplaces of South Korea. Knowl Manag E-Learn 7(2):334

    Google Scholar 

  17. Smeda AM, Shiratuddin MF, Wong KW (2017) Measuring the moderating influence of gender on the acceptance of e-book amongst mathematics and statistics students at universities in Libya. Knowl Manag E-Learn 9(2):177

    Google Scholar 

  18. Chen KT-C (2015) Exploring college students’ usage experiences, perceptions and acceptance of mobile English learning in Taiwan. Int Technol Manag Rev 5:162–171

    Article  Google Scholar 

  19. Wang Y-S, Wu M-C, Wang H-Y (2009) Investigating the determinants and age and gender differences in the acceptance of mobile learning. Br J Educ Technol 40(1):92–118

    Article  MathSciNet  Google Scholar 

  20. Viberg O, Grönlund Å (2013) Cross-cultural analysis of users’ attitudes toward the use of mobile devices in second and foreign language learning in higher education: a case from Sweden and China. Comput Educ 69:169–180

    Article  Google Scholar 

  21. Dinev T, Goo J, Hu Q, Nam K (2009) User behaviour towards protective information technologies: the role of national cultural differences. Inf Syst J 19(4):391–412

    Article  Google Scholar 

  22. Li X, Hess TJ, McNab AL, Yu Y (2009) Culture and acceptance of global web sites: a cross-country study of the effects of national cultural values on acceptance of a personal web portal. SIGMIS Database 40(4):49–74

    Article  Google Scholar 

  23. McCoy S, Galletta DF, King WR (2005) Integrating national culture into IS research: the need for current individual level measures. Commun Assoc Inf Syst 15(1):12

    Google Scholar 

  24. Srite M (2006) Culture as an explanation of technology acceptance differences: an empirical investigation of Chinese and US Users. Australasian J Inf Systems 14(1):5–26. https://doi.org/10.3127/ajis.v14i1.4

    Article  Google Scholar 

  25. Tarhini A, Hone K, Liu X, Tarhini T (2017) Examining the moderating effect of individual-level cultural values on users’ acceptance of E-learning in developing countries: a structural equation modeling of an extended technology acceptance model. Interact Learn Environ 25(3):306–328

    Article  Google Scholar 

  26. Hofstede G, Hofstede GJ, Minkov M (2010) Cultures and organizations: software of the mind. Revised and expanded. McGraw-Hill, New York

    Google Scholar 

  27. Cavus N, Uzunboylu H (2009) Improving critical thinking skills in mobile learning. Procedia Soc Behav Sci 1(1):434–438

    Article  Google Scholar 

  28. Mac Callum K, Jeffrey L (2013) The influence of students’ ICT skills and their adoption of mobile learning. Aust J Educ Technol 29(3):303–314

    Google Scholar 

  29. Bolliger DU, Supanakorn S, Boggs C (2010) Impact of podcasting on student motivation in the online learning environment. Comput Educ 55(2):714–722

    Article  Google Scholar 

  30. Wehrwein EA, Lujan HL, DiCarlo SE (2007) Gender differences in learning style preferences among undergraduate physiology students. Adv Physiol Educ 31(2):153–157

    Article  Google Scholar 

  31. Whitley BE (1997) Gender differences in computer-related attitudes and behavior: a meta-analysis. Comput Hum Behav 13(1):1–22

    Article  Google Scholar 

  32. Durndell A, Thomson K (1997) Gender and computing: a decade of change? Comput Educ 28(1):1–9

    Article  Google Scholar 

  33. Mitra A, Lenzmeier S, Steffensmeier T, Avon R, Qu N, Hazen M (2000) Gender and computer use in an academic institution: report from a Longitudinal Study. J Educ Comput Res 23(1):67–84

    Article  Google Scholar 

  34. Pagani M (2004) Determinants of adoption of third generation mobile multimedia services. J Interact Mark 18(3):46–59

    Article  Google Scholar 

  35. Torres R, Gerhart N (2017) Mobile proximity usage behaviors based on user characteristics. J Comput Inf Syst 57:1–10

    Google Scholar 

  36. Hamidi H, Chavoshi A (2017) Analysis of the essential factors for the adoption of mobile learning in higher education: a case study of students of the University of Technology. Telemat Inform 35(4):1053–1070

    Article  Google Scholar 

  37. Kim H-J, Lee J-M, Rha J-Y (2017) Understanding the role of user resistance on mobile learning usage among university students. Comput Educ 113((Supplement C)):108–118

    Article  Google Scholar 

  38. Woodcock B, Middleton A, Nortcliffe A (2012) Considering the smartphone learner: an investigation into student interest in the use of personal technology to enhance their learning. Stud Engagem Exp J 1(1):1–15

    Google Scholar 

  39. Yamin M (2018) Managing crowds with technology: cases of Hajj and Kumbh mela. Int J Inf Technol. https://doi.org/10.1007/s41870-018-0266-1

    Article  Google Scholar 

  40. Yamen M, Basahel AM, Abi Sen AA (2018) Managing crowds with wireless and mobile technologies. Hindawi. Wirel Commun Mob Comput 2018:15. https://doi.org/10.1155/2018/7361597 (Article ID 7361597)

    Article  Google Scholar 

  41. Yamin M, Abi Sen AA (2018) Improving privacy and security of user data in location based services. Int J Ambient Comput Intell 9(1):19–42. https://doi.org/10.4018/IJACI.2018010102

    Article  Google Scholar 

  42. Yamin M (2018) IT applications in healthcare management: a survey. Int J Inf Technol 10(4):503–509. https://doi.org/10.1007/s41870-018-0203-3 (Springer Publication)

    Article  Google Scholar 

  43. Yamin M, Abi Sen AA (2018) Improving privacy and security of user data in location based services. Int J Ambient Comput Intell 9(1):19–42. https://doi.org/10.4018/IJACI.2018010102

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohammad Yamin.

Appendix

Appendix

1.1 Background and demographics

  1. 1.

    Would you please write down your email:

  2. 2.

    What is your age?

  3. 3.

    Which of the following best describes your current relationship status?

  4. 4.

    Have you ever listened to an educational podcast using your mobile device?

  5. 5.

    Have you ever watched to an educational video using your mobile device?

  6. 6.

    Have you ever read to an educational materials using your mobile device?

Questionnaire for preferences has the same structure scenarios based on podcast type, length, and context (a combination of physical space and social space) as shown below:

figure a
figure b
figure c
figure d

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Al-Ismail, M., Yamin, M., Liu, YH. et al. Learner characteristics of m-learning preferences. Int. j. inf. tecnol. 11, 493–505 (2019). https://doi.org/10.1007/s41870-019-00279-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s41870-019-00279-w

Keywords

Navigation