Abstract
This study argues that in developing a robust framework for students in a blended learning environment, Structural Alignment (SA) becomes the third principle of specialisation in addition to Epistemic Relation (ER) and Social Relation (SR). We provide an extended code: (ER+/−, SR+/−, SA+/−) that present strong classification and framing to the architecture of blended learning while defining the impact of structural alignment in the trajectory. The subjects in this study were 500 undergraduate students drawn from three faculties in a university. Using a Structural Equation Model (SEM), we show that SR, ER and SA redefine the principle of specialisation in Legitimation Code Theory (LCT) which is necessary in enhancing blended learning. We conclude that whereas epistemic and social relations define the knower and knowledge code, structural alignment explains the infrastructure and policy framework that supports knowledge acquisition in a blended learning environment.
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Akyol, Z. (2014). The development of a community of inquiry over time in an online course: understanding the progression and integration of social, cognitive, and teaching presence. Journal of Asynchronous Learning Networks, 12(3–4), 3–22.
Allen, I. E., & Seaman, J. (2014). Grade change: tracking online education in the United States. Babson Survey Research Group. Available at: http://www.onlinelearningsurvey.com/reports/gradechange.pdf. Accessed 23 January 2016
Ally, M. (2011). Foundations of educational theory for online learning. In T. Anderson (Ed.), (2011) The theory and practice of online learning. Edmonton: AU Press.
Alonso, F., López, G., Manrique, D., & Viñes, J. M. (2005). An instructional model for web-based e-learning education with a blended learning process approach. British Journal of Educational Technology, 36(2), 217–235.
Bailey, K. D. (1994). Methods of social research. New York: The Free Press.
Barnett, M. (2006). Vocational knowledge and vocational pedagogy. In M. Young & J. Gamble (Eds.), Knowledge, curriculum and qualifications for south African further education (pp. 104–124). Cape Town: Human Sciences Research Council Press.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.
Bernstein, B. (1999). Vertical and horizontal discourse: an essay. British Journal of Sociology of Education, 20(2), 157–173.
Bolliger, D. U., & Wasilik, O. (2009). Factors influencing faculty satisfaction with online teaching and learning in higher education. Distance Education, 30(1), 103–116.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research. NJ: Lawrence Erlbaum Associates.
Chmiliar, L. (2010). Case study surveys. In A. J. Mills, G. Durepos, & E. Wiebe (Eds.), Encyclopedia of case study research (pp. 761–765). Thousand Oaks: SAGE.
Christie, F., & Maton, F. (2010). Disciplinarity: functional linguistic and sociological perspectives. New York: Continuum.
Clark, J. (2001). Stimulating collaboration and discussion in online learning environments. The Internet and Higher Education, 4(2), 119–124.
Cohen, L., Manion, L., & Morrison, K. (2011). Research methods in education. New York: Routledge.
Collins, R., & Makowsky, M. (1993). Dreyfus’s empire: Emile Durkheim and George Sorel. In R. Collins & M. Makowsky (Eds.), The discovery of society (pp. 101–116). New York: McGraw-Hill Inc..
Creswell, J. (2008). Educational research: planning, conducting and evaluating quantitative and qualitative research (3rd ed.). Upper Saddle River: Pearson Prentice Hall.
Czerniewicz, L. (2010). Educational technology – mapping the terrain with Bernstein as cartographer. Journal of Computer Assisted Learning, 26(6), 523–534.
De George-Walker, L., & Keeffe, M. (2010). Self-determined blended learning: a case study of blended learning design. Higher Education Research and Development, 29(1), 1–13.
Eom, S. B., Wen, H. J., & Ashill, N. (2006). The determinants of Students' perceived learning outcomes and satisfaction in university online education: an empirical investigation. Decision Sciences Journal of Innovative Education, 4(2), 215–235.
Fenwick, T., & Edwards, R. (2013). Performative ontologies: Sociomaterial approaches to researching adult education and lifelong learning. European journal for Research on the Education and Learning of Adults, 4(1), 49–63.
Ferguson, R. (2012). Learning analytics: drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5&6), 304–317.
Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(3), 39–50.
Gamble, J. (2006). Theory and practice in the vocational curriculum. In M. Young & J. Gamble (Eds.), Knowledge, curriculum and qualifications for south African further education. Cape Town: Human Sciences Research Council Press.
Garrison, D. R., & Kanuka, H. (2004). Blended learning: uncovering its transformative potential in higher education. The Internet and Higher Education, 7(2), 95–105.
Garrison, D. R., & Vaughan, N. D. (2013). Institutional change and leadership associated with blended learning innovation: two case studies. The Internet and Higher Education, 18, 24–28.
Gefen, D., Straub, D., & Boudreau, M. C. (2000). Structural equation modelling and regression: guidelines for research practice. Communications of the Association for Information Systems, 4(7), 1–79.
Graham, C. R. (2006). Blended learning systems: definition, current trends and future directions. In C. J. Bonk & C. R. Graham (Eds.), Handbook of blended learning: global perspectives, local designs. San Francisco: Pfeiffer.
Graham, C. R. (2013). Emerging practice and research in blended learning. In M. J. Moore (Ed.), Handbook of distance education (3rd ed., pp. 333–350). New York: Routledge.
Grix, J. (2002). Introducing students to the generic terminology of social research. Politics, 22(3), 175–186.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2013). A primer on partial least squares structural equation modeling (PLS-SEM) (1st ed.). London: Sage Publications.
Henseler, J., Ringle, C. M., & Sinkovics, R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–319.
Ho, C. H., & Swan, K. (2007). Evaluating online conversation in an asynchronous learning environment: an application of Grice's cooperative principle. The Internet and Higher Education, 10(1), 3–14.
Howard, S., & Maton, K. (2011). Theorising knowledge practices: a missing piece of the educational technology puzzle. Research in Learning Technology, 19(3), 191–206.
Hrastinski, S. (2008). Asynchronous and synchronous e-learning. Educause Quarterly, 31(4), 51–55.
Hrastinski, S. (2009). A theory of online learning as online participation. Computers & Education, 52(1), 78–82.
Jones, N. (2006). E-college wales, a case study of blended learning. In C. J. Bonk & C. R. Graham (Eds.), The handbook of blended learning. Global perspectives, local designs (pp. 182–193). San Francisco: Pfeiffer.
Kock, N. (2013). WarpPLS 4.0 user manual. Texas: ScriptWarp Systems.
Lakhal, S., Khechine, H., & Pascot, D. (2013). Student behavioural intentions to use desktop video conferencing in a distance course: integration of autonomy to the UTAUT model. Journal of Computing in Higher Education, 25(2), 93–121.
Lee, S. M., & Hong, S. (2002). An enterprise-wide knowledge management system infrastructure. Industrial Management & Data Systems, 102(1), 17–25.
Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: a case study of the blackboard system. Computers & Education, 51(2), 864–873.
Lin, W. S., & Wang, C. H. (2012). Antecedences to continued intentions of adopting e-learning system in blended learning instruction: a contingency framework based on models of information system success and task-technology fit. Computers & Education, 58(1), 88–99.
Lindlof, T. R. (1995). Qualitative communication research methods. Thousand Oaks: Sage.
Macdonald, J. (2008). Blended learning and online tutoring (2nd ed.). Hampshire: Gower.
Maton, K. (2004). The wrong kind of knower: education, expansion and the epistemic device. In J. Muller, B. Davies, & A. Morais (Eds.), Reading Bernstein, Researching Bernstein. London: Routlegde.
Maton, K. (2014). Knowledge and knowers. Towards a realist sociology of education. London: Routlegde.
Maton, K., & Moore, R. (2010a). Social realism, knowledge and the sociology of education: coalitions of the mind. London: Continuum.
Maton, K., & Moore, R. (2010b). Analysing knowledge claims and practices: languages of legitimation. In K. Maton & R. Moore (Eds.), Social realism, knowledge and the sociology of education: coalitions of the mind. London: Continuum.
Moore, R. (2010). Knowledge structures and the canon: a preference for judgements. In K. Maton & R. Moore (Eds.), Social realism, knowledge and the sociology of education (pp. 131–153). London: Continuum.
Moskal, P., Dziuban, P., & Hartman, J. (2013). Blended learning: a dangerous idea? The Internet and Higher Education, 18, 15–23.
Muller, J. (2007). On splitting hairs: hierarchy, knowledge and the school curriculum. In F. Christie & J. Martin (Eds.), Language, knowledge and pedagogy (pp. 65–86). London: Continuum.
Muller, J. (2009). Forms of knowledge and curriculum coherence. Journal of Education and Work, 22(3), 205–226.
Niemiec, M., & Otte, G. (2010). An administrator’s guide to the whys and hows of blended learning. Journal of Asynchronous Learning Networks, 14(1), 91–102.
Nunnally, J., & Bernstein, I. H. (1994). Psychometric theory. London: McGraw Hill.
Osguthorpe, R. T., & Graham, C. R. (2003). Blended learning environments: definitions and directions. Quarterly Review of Distance Education, 4(3), 227–233.
Ozkan, S., & Koseler, R. (2009). Multi-dimensional students’ evaluation of e-learning systems in the higher education context: an empirical investigation. Computers & Education, 53(4), 1285–1296.
Patton, M. Q. (2002). Qualitative research and evaluation methods. Thousand Oaks: Sage.
Pituch, K., & Lee, Y. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222–244.
Porter, W. W., Graham, C. R., Spring, K. A., & Welch, K. R. (2014). Blended learning in higher education: institutional adoption and implementation. Computers & Education, 75, 185–195.
Rata, E. (2012). The politics of knowledge in education. British Educational Research Journal, 38(1), 103–124.
Remesal, A., & Colomina, R. (2013). Social presence and online collaborative small group work: a socio constructivist account. Computers & Education, 60(1), 357–367.
Selim, H. M. (2007). E-learning critical success factors: an exploratory investigation of student perceptions. International Journal of Technology Marketing, 2(2), 157–182.
Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. London: John Wiley & Sons.
So, H. J., & Brush, T. A. (2008). Student perceptions of collaborative learning, social presence and satisfaction in a blended learning environment: relationships and critical factors. Computers & Education, 51(1), 318–336.
Somekh, B. (2000). New technology and learning: policy and practice in the UK, 1980-2010. Education and Information Technologies, 5(1), 19–38.
Sun, P., Ray, J. T., Glenn, F., Yueh-Yang, C., & Dowming, Y. (2007). What drives a successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183–1202.
Taylor, J. A., & Newton, D. (2012). Beyond blended learning: a case study of institutional change at an Australian regional university. The Internet and Higher Education, 18, 54–60.
Teddlie, C., & Tashakkori, A. (2009). Foundations of mixed methods research: integrating quantitative and qualitative in the social and Behavioural sciences. Thousand Oaks: Sage.
Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., & Lauro, C. (2005). PLS path modelling. Computational Statistics and Data Analysis, 48(1), 159–205.
Watson, D. M. (2001). Pedagogy before technology: Re-thinking the relationship between ICT and teaching. Education and Information Technologies, 6(4), 251–266.
Wheelahan, L. (2007). How competency-based training locks the working class out of powerful knowledge: a modified Bernteinian analysis. British Journal of Sociology of Education, 28(5), 637–651.
Wu, D., & Hiltz, S. R. (2004). Predicting learning from asynchronous online discussions. Journal of Asynchronous Learning Networks, 8(2), 139–152.
Young, M. (2006). Conceptualising vocational knowledge: some theoretical considerations. In M. Young & J. Gamble (Eds.), Knowledge, curriculum and qualifications for south African further education (pp. 104–124). Cape Town: Human Sciences Research Council Press.
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Owusu-Agyeman, Y., Larbi-Siaw, O. Reframing the principle of specialisation in legitimation code theory: A blended learning perspective. Educ Inf Technol 22, 2583–2603 (2017). https://doi.org/10.1007/s10639-016-9563-0
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DOI: https://doi.org/10.1007/s10639-016-9563-0