Pedagogical Design: Bridging Learning Theory and Learning Analytics
DOI:
https://doi.org/10.21432/cjlt27959Keywords:
Epistemology, learning analytics, learning theory, pedagogical design, learning design, instructional design, learning ecosystem designAbstract
Which learning analytics (LA) approach might be the best choice for your teaching and learning context? Learning analytics as a field of research and application seeks to collect, analyze, report, and interpret educational data with the goal of improving teaching and learning. But hasty adoption of learning analytics tools and methods that are simply convenient, promoted or available risks allowing learning analytics to ‘drive the pedagogical bus’. In this paper, we propose that careful reflection on pedagogical design choices and the learning theory that underpins them can and should inform selection of relevant learning analytics tools and approaches. We broadly review established learning theories and the implications of each for pedagogical design; for each design approach we offer examples of learning analytics most clearly aligned with the theoretical perspectives on learning and knowledge that have shaped it. Moreover, we argue that careful consideration of the learning theory underpinning the pragmatics of pedagogical design choices should guide LA implementation, and help educators and designers avoid the risk of gathering data on, and measuring outcomes for, activities that are not relevant to their pedagogical design or goals.
References
Akdeniz, C. (Ed.) (2016). Instructional process and concepts in theory and practice. Improving the teaching process. Springer Science.
Altun, S., & Büyükduman, F. I. (2007). Teacher and student beliefs on constructivist instructional design: A case study. Kuram ve Uygulamada Egitim Bilimleri, 7(1), 30-39.
Banihashem, S. K., & Aliabadi, K. (2017). Connectivism: Implications for distance education. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 8(3). http://dx.doi.org/10.5812/IJVLMS.10030
Banihashem S. K., Aliabadi K., Pourroostaei Ardakani S., Delavar, A., & Nili Ahmadabadi, M. R. (2018). Learning analytics: A systematic literature review. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 9(2). https://dx.doi.org/10.5812/ijvlms.63024
Banihashem, S. K., Aliabadi, K., Pourroostaei Ardakani, S., Nili AhmadAbadi, M. R., & Delavar, A. (2019). Investigation on the role of learning theory in learning analytics. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 10(4), 14-27. http://dx.doi.org/10.30476/IJVLMS.2019.84294.1001
Barron, A. B., Hebets, E. A., Cleland, T. A., Fitzpatrick, C. L., Hauber, M. E., & Stevens, J. R. (2015). Embracing multiple definitions of learning. Trends in Neurosciences, 38(7), 405-407. https://dx.doi.org/10.1016/j.tins.2015.04.008
Bell, F. (2009). Connectivism: A network theory for teaching and learning in a connected world. Educational Developments, The Magazine of the Staff and Educational Development Association, 10(3). http://usir.salford.ac.uk/id/eprint/2569/
Bell, F. (2011). Connectivism: Its place in theory-informed research and innovation in technology-enabled learning. The International Review of Research in Open and Distributed Learning, 12(3), 98. https://dx.doi.org/10.19173/irrodl.v12i3.902
Berland, M., Baker, R. S., & Blikstein, P. (2014). Educational data mining and learning analytics: Applications to constructionist research. Technology, Knowledge and Learning, 19(1-2), 205-220. https://doi.org/10.1007/s10758-014-9223-7
Boghossian, P. (2013). Behaviorism, constructivism, and Socratic pedagogy. Educational Philosophy and Theory, 38(6), 713-722. https://doi.org/10.1111/j.1469-5812.2006.00226.x
Branch, R. M. (2009). Instructional design: The ADDIE approach. Springer Science & Business Media.
Brown, A. H., & Green, T. D. (2019). The essentials of instructional design: Connecting fundamental principles with process and practice. Routledge.
Brown, J. S. (2000). Growing up digital: How the web changes work, education, and the ways people learn. USDLA journal, 16(2), n2. https://doi.org/10.1080/00091380009601719
Buckingham Shum, S., & Ferguson, R. (2011). Social learning analytics. The Open University, UK: Knowledge Media Institute. http://kmi.open.ac.uk/publications/pdf/kmi-11-01.pdf
Bybee, R. W., Taylor, J. A., Gardner, A., Van Scotter, P., Powell, J. C., Westbrook, A., & Landes, N. (2006). The BSCS 5E instructional model: Origins and effectiveness. BSCS. https://bscs.org/resources/reports/the-bscs-5e-instructional-model-origins-and-effectiveness/
Chatti, M. A. (2010). The LaaN theory. In Personalization in technology enhanced learning: A social software perspective (pp. 19-42). Shaker Verlag. http://mohamedaminechatti.blogspot.com/2013/01/the-laan-theory.html
Chen, P.-S. D., Lambert, A. D., & Guidry, K. R. (2010). Engaging online learners: The impact of web-based learning technology on college student engagement. Computers & Education, 54(4), 1222-1232. https://doi.org/10.1080/13562517.2013.827653
Clow, D. (2013). An overview of learning analytics. Teaching in Higher Education, 18(6), 683-695. https://doi.org/10.1080/13562517.2013.827653
Conole, G. (2012). Designing for learning in an open world. New York, USA: Springer Science & Business Media.
Cooper, P. A. (1993). Paradigm shifts in designed instruction: From behaviorism to cognitivism to constructivism. Educational Technology, 33(5), 12-19. https://www.jstor.org/stable/44428049
Crosslin, M., Dellinger, J. T., Joksimovic, S., Kovanovic, V., & Gaševic, D. (2018). Customizable modalities for individualized learning: Examining patterns of engagement in dual-layer MOOCs. Online Learning, 22(1), 19-38. http://dx.doi.org/10.24059/olj.v22i1.1080
Currie, G. (2004). Cognitivism. In T. Miller & R. Stam (Eds.), A companion to film theory (pp. 105-122). John Wiley & Sons.
Dawson, S. (2009). ‘Seeing’ the learning community: An exploration of the development of a resource for monitoring online student networking. British Journal of Educational Technology, 41(5), 736-752. http://dx.doi.org/10.1111/j.1467-8535.2009.00970.x
Dick, W., Carey, L., & Carey, J. O. (2005). The systematic design of instruction. Pearson/Allyn and Bacon.
Downes, S. (2008). An introduction to connective knowledge. Media, Knowledge & Education: Exploring new Spaces, Relations and Dynamics in Digital Media Ecologies (pp. 77-102). Innsbruck University Press. https://www.oapen.org/search?identifier=449459
Duke, B., Harper, G., & Johnston, M. (2013). Connectivism as a digital age learning theory? The International HETL Review, 2013(Special Issue), 4-13. https://www.hetl.org/wp-content/uploads/2013/09/HETLReview2013SpecialIssueArticle1.pdf
Dunaway, M. K. (2011). Connectivism: Learning theory and pedagogical practice for networked information landscapes. Reference Services Review, 39(4), 675-685. https://doi.org/10.1108/00907321111186686
Ertmer, P. A., & Newby, T. J. (2013). Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance Improvement Quarterly, 26(2), 43-71. https://dx.doi.org/10.1002/piq.21143
Ferguson, R., & Clow, D. (2017). Where is the evidence? A call to action for learning analytics. Seventh International Conference on Learning Analytics & Knowledge (pp. 56-65). ACM. https://doi.org/10.1145/3027385.3027396
Gagné, R. M. (1965). Conditions of learning. Holt McDougal.
Gagnon, G. W., & Collay, M. (2005). Constructivist learning design: Key questions for teaching to standards. Corwin Press.
Gašević, D., Dawson, S., Rogers, T., & Gasevic, D. (2016). Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success. The Internet and Higher Education, 28, 68-84. https://doi.org/10.1016/j.iheduc.2015.10.002
Gašević, D., Dawson, S., & Siemens, G. (2015). Let’s not forget: Learning analytics are about learning. TechTrends, 59(1), 64-71. https://dx.doi.org/10.1007/s11528-014-0822-x
Gütl, C., & Chang, V. (2008). Ecosystem-based theoretical models for learning in environments of the 21st century. International Journal of Emerging Technologies in Learning (iJET), 3(2008). http://dx.doi.org/10.3991/ijet.v3i1.742
Halttunen, K. (2011). Pedagogical design and evaluation of interactive information retrieval learning environment. In E. Efthimiadis, J. Fernández-Luna, J. Huete, & A. MacFarlane (Eds.), Teaching and learning in information retrieval (pp. 61-73). Springer.
Heinich, R., Molenda, M., Russell, J., & Smaldino, S. (1999). Instructional media and technologies for learning (6th ed.). Prentice Hall.
Ifenthaler, D., Gibson, D., & Dobozy, E. (2018). Informing learning design through analytics: Applying network graph analysis. Australasian Journal of Educational Technology, 34(2). https://doi.org/10.14742/ajet.3767
Jonassen, D. H. (1991). Objectivism versus constructivism: Do we need a new philosophical paradigm? Educational Technology Research and Development, 39(3), 5-14. https://doi.org/10.1007/BF02296434
Jonassen, D. H. (1999). Designing constructivist learning environments. In C. M. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory (pp. 215-239). Lawrence Erlbaum Associates.
Kizito, R. N. (2016). Connectivism in learning activity design: Implications for pedagogically-based technology adoption in African higher education contexts. International Review of Research in Open and Distributed Learning, 17(2), 19-39. https://doi.org/10.19173/irrodl.v17i2.2217
Knight, S., Buckingham Shum, S., & Littleton, K. (2013). Epistemology, pedagogy, assessment and learning analytics. Proceedings, Third International Conference on Learning Analytics and Knowledge (pp. 75-84). ACM. https://doi.org/10.1145/2460296.2460312
Knight, S., Shum, S. B., & Littleton, K. (2014). Epistemology, assessment, pedagogy: Where learning meets analytics in the middle space. Journal of Learning Analytics, 1(2), 23‐47. https://doi.org/10.18608/jla.2014.12.3
Koh, E., Shibani, A., Tan, J. P.-L., & Hong, H. (2016). A pedagogical framework for learning analytics in collaborative inquiry tasks: An example from a teamwork competency awareness program. Proceedings, Sixth International Conference on Learning Analytics & Knowledge (pp. 74-83). ACM. https://doi.org/10.1145/2883851.2883914
Kop, R., & Hill, A. (2008). Connectivism: Learning theory of the future or vestige of the past? The International Review of Research in Open and Distributed Learning, 9(3). https://doi.org/10.19173/irrodl.v9i3.523
Levers, M.-J. D. (2013). Philosophical paradigms, grounded theory, and perspectives on emergence. SAGE Open, 3(4), 1-6. https://doi.org/10.1177/2158244013517243
Long, P., & Siemens, G. (2011). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 45(6). Retrieved from https://er.educause.edu/articles/2011/9/penetrating-the-fog-analytics-in-learning-and-education
Mazur, J. E. (2016). Learning and behavior (8th ed.). Routledge.
McNamara, D. S., Allen, L., Crossley, S., Dascalu, M., & Perret, C. A. (2017). Natural language processing and learning analytics. In C. Lang, G. Siemens, A. Wise, & D. Gašević (Eds.), Handbook of learning analytics (1st ed., pp. 93-104). Society for Learning Analytics Research (SoLAR). https://doi.org/10.18608/hla17.008
Mergel, B. (1998). Instructional design and learning theory. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.645.7122&rep=rep1&type=pdf
Merrill, M. D. (1991). Constructivism and instructional design. Educational Technology, 31(5), 45-53. https://www.jstor.org/stable/44427520
Merrill, M. D. (2002). First principles of instruction. Educational Technology Research and Development, 50(3), 43-59. https://doi.org/10.1007/BF02505024
Mohammadi, M., Moenikia, M., & Zahed-Babelan, A. (2010). The role of advance organizer on English language learning as a second language. Procedia-Social and Behavioral Sciences, 2(2), 4667-4671. https://doi.org/10.1016/j.sbspro.2010.03.747
Mor, Y., & Craft, B. (2012). Learning design: Reflections upon the current landscape. Research in Learning Technology, 20, 85-94. https://doi.org/10.3402/rlt.v20i0.19196
Mor, Y., Craft, B., & Maina, M. (2015). Introduction: Learning design: Definitions, current issues and grand challenges. In Y. Mor, B. Craft, & M. Maina (Eds.), The art & science of learning design (pp. ix-xxvi). Sense.
Morrison, G. R., Ross, S. J., & Kemp, J. E. (2004). Designing effective instruction (4th ed.). John Wiley & Sons.
Papadakis, S. (2012). Enabling creative blended learning for adults through learning design. In P. S. Anastasiades (Ed.), Blended learning environments for adults: Evaluations and frameworks (pp. 257-273). IGI Global.
Parker, K. H. (2009). Constructivist learning design: A qualitative study of learning theory and at-rsk student academic success. [Doctoral dissertation, Capella University]. Available from ProQuest Dissertations and Theses database (3355349). https://www.proquest.com/openview/acfa703c696a3e9a9148a5f8a0262016/1?pq-origsite=gscholar&cbl=18750
Perelmutter, B., McGregor, K. K., & Gordon, K. R. (2017). Assistive technology interventions for adolescents and adults with learning disabilities: An evidence-based systematic review and meta-analysis. Computers & Education, 114, 139-163. https://doi.org/10.1016/j.compedu.2017.06.005
Pradhan, A. (2016, February 19). 6 steps to creating learning ecosystems (why you should bother). https://learnnovators.com/blog/6-steps-to-creating-learning-ecosystems-and-why-you-should-bother/.
Prasertsilp, P. (2013). Mobile learning: designing a socio-technical model to empower learning in higher education. LUX: A Journal of Transdisciplinary Writing and Research from Claremont Graduate University, 2(1), 23. https://scholarship.claremont.edu/lux/vol2/iss1/23/
Reiser, R. A., & Dempsey, J. V. (2007). Trends and issues in instructional design and technology. Allyn & Bacon.
Richardson, A. (2002). An ecology of learning and the role of elearning in the learning environment. Global Summit of Online Knowledge Networks, (pp. 47-51). Education.au Limited.
Romiszowski, A. J. (2016). Designing instructional systems: Decision making in course planning and curriculum design. Routledge.
Rosé, C. P., Ferschke, O., Tomar, G., Yang, D., Howley, I., Aleven, V., . . . Baker, R. (2015). Challenges and opportunities of dual-layer MOOCs: Reflections from an edX deployment study. 11th International Conference on Computer Supported Collaborative Learning (CSCL 2015) (pp. 848-851). International Society of the Learning Sciences, Inc. https://84.38.64.180/data/publications/2015/RoseCSCL2015.pdf
Saadatmand, M. (2017). A new ecology for learning: An online ethnographic study of learners’ participation and experience in connectivist MOOCs. [Doctoral dissertation, University of Helsinki]. http://urn.fi/URN:ISBN:978-951-51-3191-1
Sawyer, R. (2014). Introduction: The new science of learning. In R. Sawyer (Ed.), The Cambridge handbook of the learning sciences (Cambridge Handbooks in Psychology, pp. 1-18). Cambridge University Press. https://doi.org/10.1017/CBO9781139519526.002
Schott, F., & Seel, N. M. (2015). Instructional design. In International encyclopedia of the social & behavioral sciences (2nd ed., pp. 196-200). Elsevier. https://doi.org/10.1016/B978-0-08-097086-8.92032-4
Seel, N. M., Lehmann, T., Blumschein, P., & Podolskiy, O. A. (2017). Instructional design for learning: Theoretical foundations. Sense.
Shaffer, D. W., Collier, W., & Ruis, A. R. (2016). A tutorial on epistemic network analysis: Analyzing the structure of connections in cognitive, social, and interaction data. Journal of Learning Analytics, 3(3), 9-45. https://doi.org/10.18608/jla.2016.33.3
Shaffer, D. W., & Ruis, A. (2017). Epistemic network analysis: A worked example of theory-based learning analytics. In C. Lang, G. Siemens, A. F. Wise, & D. Gaševic (Eds.), The Handbook of Learning Analytics (1st ed., pp. 175-187). Society for Learning Analytics Research (SoLAR). https://doi.org/10.18608/jla.2016.33.3
Shibani, A., Knight, S., & Shum, S. B. (2019). Contextualizable learning analytics design: A generic model and writing analytics evaluations. Proceedings of the Ninth International Conference on Learning Analytics & Knowledge (pp. 210-219). ACM. https://doi.org/10.1145/3303772.3303785
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3-10. https://www.itdl.org/Journal/Jan_05/Jan_05.pdf
Siemens, G. (2008). Learning and knowing in networks: Changing roles for educators and designers. ITFORUM for Discussion, 27, 1-26.
Siemens, G., Dawson, S., & Lynch, G. (2013). Improving the quality and productivity of the higher education sector. Policy and strategy for systems-level deployment of learning analytics. Society for Learning Analytics Research & Australian Government Office for Learning and Teaching. https://solaresearch.org/wp-content/uploads/2017/06/SoLAR_Report_2014.pdf
Siemens, G., & Tittenberger, P. (2009). Handbook of emerging technologies for learning. University of Manitoba.
Smith, M. (1999-2020). Learning theory. In M. Smith (Ed.), The encyclopedia of pedagogy and informal education. https://infed.org/mobi/learning-theory-models-product-and-process/
Smith, P. L., & Ragan, T. J. (2004). Instructional design. John Wiley & Sons.
Stauter, D. W., Prehn, J., Peters, M., Jeffries, L. M., Sylvester, L., Wang, H., & Dionne, C. (2019). Assistive technology for literacy in students with physical disabilities: A systematic review. Journal of Special Education Technology, 34(4), 284-292. https://doi.org/10.1177/0162643419868259
Stewart, C. (2017). Learning analytics: Shifting from theory to practice. Journal on Empowering Teaching Excellence, 1(1), 10. https://doi.org/10.15142/T3G63W
Viberg, O., Hatakka, M., Bälter, O., & Mavroudi, A. (2018). The current landscape of learning analytics in higher education. Computers in Human Behavior, 89, 98-110. https://doi.org/10.1016/j.chb.2018.07.027
Watson, J. B. (1913). Psychology as the behaviorist views it. Psychological Review, 20(2), 158. https://doi.org/10.1037/h0074428
Weegar, M. A., & Pacis, D. (2012). A comparison of two theories of learning-behaviorism and constructivism as applied to face-to-face and online learning. Paper presented at the CASA e-leader conference, Manila, 2012. https://g-casa.com/conferences/manila/papers/Weegar.pdf
Wise, A. (2014). Designing pedagogical interventions to support student use of learning analytics. Proceedings, Fourth International Conference on Learning Analytics & Knowledge (pp. 203-211). ACM. https://doi.org/10.1145/2567574.2567588
Wong, J., Baars, M., de Koning, B. B., van der Zee, T., Davis, D., Khalil, M., . . . Paas, F. (2019). Educational theories and learning analytics: From data to knowledge. The whole is greater than the sum of its parts. In D. Ifenthaler, D. K. Mah, & J. K. Yau (Eds.), Utilizing learning analytics to support study success (pp. 3-25). Springer. http://dx.doi.org/10.1007/978-3-319-64792-0_1
Yilmaz, K. (2011). The cognitive perspective on learning: Its theoretical underpinnings and implications for classroom practices. The Clearing House: A Journal of Educational Strategies, Issues and Ideas, 84(5), 204-212. https://doi.org/10.1080/00098655.2011.568989
Published
Issue
Section
License
Copyright (c) 2021 Seyyed Kazem Banihashem, Leah P. Macfadyen
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright Notice
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under an International Creative Commons Attribution-NonCommercial License (CC-BY-NC 4.0) that allows others to share the work for non-commercial purposes, with an acknowledgement of the work's authorship and initial publication in this journal.