Situating learning analytics pedagogically: towards an ecological lens

References

• Agudo-Peregrina, Á. F. , Iglesias-Pradas, S. , Conde-González, M. Á. , & Hernández-García, Á. (2014). Can we predict success from log data in VLEs? Classification of interactions for learning analytics and their relation with performance in VLE-supported F2F and online learning. Computers in Human Behavior , 31, 542–550. doi:10.1016/j.chb.2013.05.031
   Web of Science ®Google Scholar
• Alexander, R. (2008). Essays on pedagogy . New York: Routledge.
   Google Scholar
• Box, G. E. , & Draper, N. R. (1987). Empirical model-building and response surfaces (Vol. 424). New York, NY: Wiley.
   Google Scholar
• Bronfenbrenner, U. (1994). Ecological models of human development. Readings on the Development of Children , 2(1), 37–43.
   Google Scholar
• Buckingham Shum, S. , & Deakin Crick, R. (2016). Learning analytics for 21st century competencies. Journal of Learning Analytics , 3(2), 6–21. doi:10.18608/jla.2016.32.2
   Google Scholar
• City, E.A., Elmore, R. F. , Fiarman, S. E. , & Teitel, L. (2009). Instructional rounds in education: A network approach to improving teaching and learning . Cambridge, MA: Harvard Education Press.
   Google Scholar
• Elmore, R. (1996). Getting to scale with good educational practice. Harvard Educational Review , 66(1), 1–27. doi:10.17763/haer.66.1.g73266758j348t33
   Web of Science ®Google Scholar
• Ferguson, R. (2012). Learning analytics: Drivers, developments and challenges. International Journal of Technology Enhanced Learning , 4(5/6), 304–317. doi:10.1504/IJTEL.2012.051816
   Google Scholar
• Inayatullah, S. (1998). Causal layered analysis: Poststructuralism as method. Futures , 30(8), 815–829. doi:10.1016/S0016-3287(98)00086-X
   Web of Science ®Google Scholar
• Johnson, L. , Adams Becker, S. , Cummins, M. , Estrada, V. , Freeman, A. , & Hall, C. (2016). NMC horizon report: 2016 higher education edition . Austin, TX: The New Media Consortium.
   Google Scholar
• 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. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, Edinburgh, United Kingdom (pp. 74–83). New York: ACM. doi:10.1145/2883851.2883914
   Google Scholar
• Lockyer, L. , Heathcote, E. , & Dawson, S. (2013). Informing pedagogical action: Aligning learning analytics with learning design. American Behavioral Scientist , 57(10), 1439–1459. doi:10.1177/0002764213479367
   Web of Science ®Google Scholar
• Office of Education Research . (2016). 17th request for proposals: School improvement and core research program . Singapore: National Institute of Education. Unpublished document.
   Google Scholar
• Rosé, C. P. , Gašević, D. , Dillenbourg., P. , Jo, Y. , Tomar, G. , Ferschke, O. , … Yang, S. (2016). Analytics of social processes in learning contexts: A multi-level perspective. In Proceedings of the 12th International Conference of the Learning Sciences (ICLS) 2016, (Vol. 1, pp. 24–31). Invited Symposium. Singapore: International Society of the Learning Sciences.
   Google Scholar
• Schoenfeld, A. H. , & the Teaching for Robust Understanding Project . (2016). An introduction to the Teaching for Robust Understanding (TRU) framework . Berkeley, CA: Graduate School of Education. Retrieved from http://tru.berkeley.edu
   Google Scholar
• Siemens, G. , & Gašević, D. (2012). Guest editorial: Learning and knowledge analytics. Educational Technology & Society , 15(3), 1–2.
   Web of Science ®Google Scholar
• Tan, J. P-L. (2009). Digital kids, analogue students: A mixed methods study of students’ engagement with a school-based Web 2.0 learning innovation (Doctoral dissertation). Queensland University of Technology.
   Google Scholar
• Wise, A. F. (2014). Designing pedagogical interventions to support student use of learning analytics. In Proceedings of the Fourth International Conference on Learning Analytics and Knowledge,Indianapolis, IN, USA (pp. 203–211). New York: ACM. doi:10.1145/2567574.2567588
   Google Scholar