Abstract
The purpose of this paper is to investigate how the factors that influence a learner’s ability to be self-directed (Andragogy) and self-determined (Heutagogy) may influence the understanding and modelling of mobile learning adoption. Heutagogy is seen as a progression along a continuum of pedagogical approaches from pedagogy to andragogy to heutagogy, where learners need to progress from each with the aim of becoming highly autonomous and mature learners. Due to the nature of mobile technology, learning can be orientated towards the learner to support their needs. Learners are now better equipped to manage and control their own learning as learning can take place anywhere and anytime. However not all students possess the required traits, such as self-management, self-control and desire for learning, that signal that are ready for learning that is no longer teacher-lead and directed.
The study examines the results of a survey (n = 446 students) assessing how the traits that indicate a readiness for learning that is self-directed and self-determined, can impact on students’ perceptions and adoption of mobile learning. This model was tested using structural equation modelling. The findings showed that there was a strong association with the factors of self-management, self-control and desire for learning on the positive perception of mobile learning and adoption. The study reinforces the need for scaffolding and developing learners so that they are comfortable to succeed in an environment that is self- directed and determined.
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References
Akour, H.: Determinants of mobile learning acceptance: an empirical investigation in higher education Doctoral dissertation. Retrieved from ProQuest Dissertations & Theses database (2009). (UMI No. AAT 3408682)
Blaschke, L.M.: Heutagogy and lifelong learning: a review of heutagogical practice and self-determined learning. Int. Rev. Res. Open Distrib. Learn. 13(1), 56–71 (2012)
Bridges, P., Bierema, L., Valentine, T.: The propensity to adopt evidence-based practice among physical therapists. BMC Health Serv. Res. 7(1), 103 (2007). doi:10.1186/1472-6963-7-103
Canning, N., Callan, S.: Heutagogy: Spirals of reflection to empower learners in higher education. Reflect. Pract. 11(1), 71–82 (2010)
Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–339 (1989)
Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: Extrinsic and intrinsic motivation to use computers in the workplace. J. Appl. Soc. Psychol. 22(14), 1111–1132 (1992). doi:10.1111/j.1559-1816.1992.tb00945.x
Deepwella, F., Malikb, S.: On campus, but out of class: an investigation into students’ experiences of learning technologies in their self-directed study. ALTJ, Res. Learn. Technol. 16(1), 5–14 (2008). http://repository.alt.ac.uk/749/
Dillon, A.: User acceptance of information technology. In: Karwowski, W. (ed.) Encyclopedia of Human Factors and Ergonomics. Taylor and Francis, London (2001)
Donaldson, R.L.: Student acceptance of mobile learning. Unpublished doctoral dissertation. Florida State University, USA (2011). http://www.rdonaldson.com/wpcontent/uploads/2011/05/Donaldson_R_Dissertation_2011.pdf
Ebner, M., Lienhardt, C., Rohs, M., Meyer, I.: Microblogs in higher education: a chance to facilitate informal and process-oriented learning? Comput. Educ. 55(1), 92–100 (2010). doi:10.1016/j.compedu.2009.12.006
Fisher, M.J., King, J.: The self-directed learning readiness scale for nursing education revisited: A confirmatory factor analysis. Nurs. Educ. Today 30(1), 44–48 (2010). doi:10.1016/j.nedt.2009.05.020
Fisher, M., King, J., Tague, G.: Development of a self-directed learning readiness scale for nursing education. Nurs. Educ. Today 21(7), 516–525 (2001). doi:10.1054/nedt.2001.0589
Fischer, G., Scharff, E.: Learning technologies in support of self-directed learning. J. Interact. Media Educ. vol. 1998(2), Article 4 (2010)
Hackbarth, G., Grover, V., Yi, M.Y.: Computer playfulness and anxiety: positive and negative mediators of the system experience effect on perceived ease of use. Inf. Manage. 40(3), 221–232 (2003). doi:10.1016/S0378-7206(02)00006-X
Hedman, J., Gimpel, G.: The adoption of hyped technologies: a qualitative study. Inf. Technol. Manage. 11(4), 161–175 (2010). doi:10.1007/s10799-010-0075-0
Hooper, D., Couglan, J., Mullen, M.R.: Structural equation modelling: guidelines for determining model fit. Electron. J. Bus. Res. Methods 6(1), 53–60 (2008). http://arrow.dit.ie/libart/4
Kenyon, C., Hase, S.: Moving from andragogy to heutagogy in vocational education (2001). http://www.avetra.org.au/abstracts_and_papers_2001/Hase-Kenyon_full.pdf
Lan, Y.-F., Sie, Y.-S.: Using RSS to support mobile learning based on media richness theory. Comput. Educ. 55(2), 723–732 (2010). doi:10.1016/j.compedu.2010.03.005
Lawlor, B., Donnelly, R.: Using podcasts to support communication skills development: a case study for content format preferences among postgraduate research students. Comput. Educ. 54(4), 962–971 (2010). doi:10.1016/j.compedu.2009.09.031
Lazzari, M.: Creative use of podcasting in higher education and its effect on competitive agency. Comput. Educ. 52(1), 27–34 (2009). doi:10.1016/j.compedu.2008.06.002
Liu, Y., Li, H.: What drives m-learning success? drawing insights from selfdirected learning theory. In: Pacific Asia Conference on Information Systems (PACIS 2009), India July 2009
Lowenthal, J.N.: Using mobile learning: determinates impacting behavioural intention. Am. J. Distance Educ. 24(4), 195–206 (2010). doi:10.1080/08923647.2010.519947
Luckin, R., Clark, W., Garnett, F., Whitworth, A., Akass, J., Cook, J., Robertson, J.: Learner-Generated Contexts: A Framework to Support the Effective Use of Technology for Learning. In: Lee, M., McLoughlin, C. (eds.) Web 2.0-Based E-Learning: Applying Social Informatics for Tertiary Teaching, pp. 70–84. IGI Global, Hershey (2010)
Merriam, S.B.: Andragogy and self-directed learning: Pillars of adult learning theory. New Dir. Adult Contin. Educ. 2001(89), 3–14 (2001)
Newman, M.: Problem based learning: An exploration of the method and evaluation of its effectiveness in a continuing nursing education programme Project on the Effectiveness of Problem Based Learning (PEPBL) Research Report. Middlesex University, Middlesex, UK (2004)
Nunnally, J.C., Bernstein, I.H.: Psychometric Theory, 3rd edn. McGraw-Hill, New York (1994)
Pallant, J.: SPSS survival manual: a step by step guide to data analysis using SPSS for Windows, 3rd edn. Allen & Unwin, Crows Nest, Australia (2007)
Penman, M.: Do we have what it takes? An investigation into New Zealand occupational therapists’ readiness to be self-directed learners Doctoral dissertation, University of Otago (2014)
Ponton, M.K., Carr, P.B.: Understanding and promoting autonomy in selfdirected learning. Current Research Social Psychology 5(19), 271–284 (2000). http://www.uiowa.edu/~grpproc/crisp/crisp.5.19.htm
Regan, J.-A.: Facilitating students towards self-directed learning. In: Hartley, P., Woods, A., Pill, M. (eds.) Enhancing teaching in higher education: new approaches for improving student learning, pp. 93–108. Routledge, Abingdon (2005)
Ryu, H., Cui, J., Parsons, D.: Raising the bar of challenge with collaboration: social flow in mobile learning. In: 9th World Conference on Mobile and Contextual Learning (m-Learn 2010), Valetta, Malta, October 2010
Saadé, R., Kira, D.: Mediating the impact of technology usage on perceived ease of use by anxiety. Comput. Educ. 49(4), 1189–1204 (2007)
Sha, L., Looi, C.-K., Chen, W., Zhang, B.H.: Understanding mobile learning from the perspective of self-regulated learning. J. Comput. Assist. Learn. 28(4), 366–378 (2012). doi:10.1111/j.1365-2729.2011.00461.x
Smedley, A.: The self-directed learning readiness of first year bachelor of nursing students. J. Res. Nurs. 12, 373–385 (2007). doi:10.1177/1744987107077532
Stone, A. (Ed.): Designing scalable, effective mobile learning for multiple technologies: Learning and Skills Development Agency (2004)
Straub, E.T.: Understanding technology adoption: theory and future directions for informal learning. Rev. Educ. Res. 79(2), 625–649 (2009). doi:10.3102/0034654308325896
Theng, Y.-L.: Mobile learning for tertiary students: an exploratory study of acceptance of use. In: World Conference on Educational Multimedia, Hypermedia and Telecommunications 2009, Honolulu, HI, USA, June 2009. http://www.editlib.org/p/31606
Torabi, N., Abdollahi, B., Aslani, G., Bahrami, A.: A validation of a self-directed learning readiness scale among preliminary schoolteachers in Esfahan. Procedia-Soc. Behav. Sci. 83, 995–999 (2013)
Venkatesh, V.: Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Inf. Syst. Res. 11, 342–365 (2000). doi:10.1287/isre.11.4.342.11872
Venkatesh, V., Davis, F.D.: A model of the antecedents of perceived ease of use: development and test. Decis. Sci. 27(3), 451–481 (1996). doi:10.1111/j.1540-5915.1996.tb00860.x
Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: Toward a unified view. MIS Q. 27(3), 425–478 (2003). doi:10.2190/EC.40.1.d
Zeng, R., Luyegu, E.: Mobile learning in higher education. In: Olofsson, A.D., Lindberg, J.O. (Eds.) Informed Design of Educational Technologies in Higher Education: Enhanced Learning and Teaching, pp. 292–306. IGI Global (2011)
Wang, Y.S., Wu, M.C., Wang, H.Y.: Investigating the determinants and age and gender differences in the acceptance of mobile learning. Br. J. Educ. Technol. 40(1), 92–118 (2009)
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Mac Callum, K., Jeffery, L., Kinshuk (2015). Heutagogial Approaches in the Understanding and Modelling the Adoption of Mobile Learning. In: Brown, T., van der Merwe, H. (eds) The Mobile Learning Voyage - From Small Ripples to Massive Open Waters. mLearn 2015. Communications in Computer and Information Science, vol 560. Springer, Cham. https://doi.org/10.1007/978-3-319-25684-9_24
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