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Learning Analytics Research: Using Meta-Review to Inform Meta-Synthesis

  • Xu Du
  • Juan Yang
  • Mingyan Zhang
  • Jui-Long Hung
  • Brett E. Shelton
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 880)

Abstract

Research in learning analytics is proliferating as scholars continue to find better and more engaging ways to consider how data can help inform evidence-based decisions for learning and learning environments. With well over a thousand articles published in journals and conferences with respect to learning analytics, only a handful or articles exist that attempt to synthesize the research. Further, a meta-review of those articles reveals a lack of consistency in the scope of included studies, the confluence of educational data mining activities and “big data” as a parameter for inclusion, and the reporting of actual strategies and analytic methods used by the included studies. To fill these gaps within existing reviews of learning analytics research, this metasynthesis follows procedures outlined by Cooper to reveal developments of learning analytics research. The results include a number of metrics showing trends and types of learning analytic studies through 2017 that include which fields are publishing and to what extent, what methods and strategies are employed by these studies, and what domains remain largely yet unexplored.

Keywords

Learning analytics Metasynthesis Educational data mining 

References

  1. 1.
    Picciano, A.G.: The evolution of big data and learning analytics in american higher education. J. Asynchronous Learn. Netw. 16(4), 9–20 (2012)Google Scholar
  2. 2.
    Yiu, C.: The big data opportunity: making government faster, smarter and more personal. In: Policy Exchange, pp. 1–36 (2012)Google Scholar
  3. 3.
    Wang, G., Gunasekaran, A., Ngai, E.W.T., Papadopoulos, T.: Big data analytics in logistics and supply chain management: certain investigations for research and applications. Int. J. Prod. Econ. 176, 98–110 (2016)CrossRefGoogle Scholar
  4. 4.
    Raghupathi, W., Raghupathi, V.: Big data analytics in healthcare: promise and potential. Health Inf. Sci. Syst. 2(1), 3 (2014)CrossRefGoogle Scholar
  5. 5.
    Daniel, B.: Big data and analytics in higher education: opportunities and challenges. Br. J. Edu. Technol. 46(5), 904–920 (2015)CrossRefGoogle Scholar
  6. 6.
    1st International Conference on Learning Analytics and Knowledge. https://tekri.athabascau.ca/analytics/. Accessed 18 Apr 2018
  7. 7.
    Learning Analytics: The Future is Now. https://edtechdigest.com/2012/05/10/learning-analytics-the-future-is-now/. Accessed 18 Apr 2018
  8. 8.
    Bienkowski, M., Feng, M., Means, B.: Enhancing teaching and learning through educational data mining and learning analytics: an issue brief. https://tech.ed.gov/learning-analytics/. Accessed 18 Apr 2018
  9. 9.
    Elias, T.: Learning analytics: definitions, processes and potential (2011). http://learninganalytics.net/LearningAnalyticsDefinitionsProcessesPotential.pdf. Accessed 18 Apr 2018
  10. 10.
    Chatti, M.A., Dyckhoff, A.L., Schroeder, U., Thüs, H.: A reference model for learning analytics. Int. J. Technol. Enhanc. Learn. 4(5/6), 318–331 (2012)CrossRefGoogle Scholar
  11. 11.
    Romero, C., Ventura, S.: Data mining in education. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 3(1), 12–27 (2013)CrossRefGoogle Scholar
  12. 12.
    Siemens, G., Baker, R.S.J.D.: Learning analytics and educational data mining: towards communication and collaboration. In: International Conference on Learning Analytics and Knowledge, pp. 252–254. ACM (2012)Google Scholar
  13. 13.
    Kumar, R., Sharma, A.: Data mining in education: a review. Int. J. Mach. Eng. Inf. Technol. 5(1), 1843–1845 (2017)Google Scholar
  14. 14.
    Ferguson, R.: The state of learning analytics in 2012: a review and future challenges. Technical Report KMI-12-01, Knowledge Media Institute the Open University UK (2012). http://kmi.open.ac.uk/publications/techreport/kmi-12-01. Accessed 18 Apr 2018
  15. 15.
    Papamitsiou, Z., Economides, A.A.: Learning analytics and educational data mining in practice: a systematic literature review of empirical evidence. J. Educ. Technol. Soc. 17(4), 49–64 (2014)Google Scholar
  16. 16.
    Sin, K., Muthu, L.: Application of big data in education data mining and learning analytics – a literature review. ICTACT J. Soft Comput. 5(4), 1035–1049 (2015)CrossRefGoogle Scholar
  17. 17.
    Vihavainen, A., Ahadi, A., Butler, M., Börstler, J., Edwards, S.H., Isohanni, E., Korhonen, A., Petersen, A., Rivers, K., Rubio, M.A., Sheard, J., Skupas, B., Spacco, J., Szabo, C., Toll, D.: Educational data mining and learning analytics in programming: literature review and case studies. In: ITiCSE on Working Group Reports, pp. 41–63. ACM (2015)Google Scholar
  18. 18.
    Avella, J.T., Kebritchi, M., Nunn, S.G., Kanai, T.: Learning analytics methods, benefits, and challenges in higher education: a systematic literature review. J. Interact. Online Learn. 20(2), 1–17 (2016)Google Scholar
  19. 19.
    Schwendimann, B.A., Rodrigueztriana, M.J., Vozniuk, A., Prieto, L.P., Boroujeni, M.S., Holzer, A., Gillet, D., Dillenbourg, P.: Perceiving learning at a glance: a systematic literature review of learning dashboard research. IEEE Trans. Learn. Technol. 99, 30–41 (2017)CrossRefGoogle Scholar
  20. 20.
    Rodríguez-Triana, M.J., Prieto, L.P., Vozniuk, A., Boroujeni, M.S., Schwendimann, B.A., Holzer, A., Gillet, D.: Monitoring, awareness and reflection in blended technology enhanced learning: a systematic review. Int. J. Technol. Enhanc. Learn 9(2/3), 1–26 (2017)Google Scholar
  21. 21.
    Leitner, P., Khalil, M., Ebner, M.: Learning analytics in higher education—a literature review. In: Learning Analytics: Fundaments, Applications, and Trends, pp. 1–23. Springer (2017)Google Scholar
  22. 22.
    Cooper, H.M.: Organizing knowledge syntheses: a taxonomy of literature reviews. Knowl. Soc. 1(1), 104 (1988)MathSciNetGoogle Scholar
  23. 23.
    Chang, C.Y., Lai, C.L., Hwang, G.J.: Trends and research issues of mobile learning studies in nursing education: a review of academic publications from 1971 to 2016. Comput. Educ. 116, 28–48 (2018)CrossRefGoogle Scholar
  24. 24.
    Johnson, L., Adams, S., Cummins, M.: NMC Horizon Report: 2012K-12 Edition, The New Media Consortium (2012)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Xu Du
    • 1
  • Juan Yang
    • 1
  • Mingyan Zhang
    • 1
  • Jui-Long Hung
    • 2
  • Brett E. Shelton
    • 2
  1. 1.National Engineering Research Center for E-LearningCentral China Normal UniversityWuhanChina
  2. 2.Boise State UniversityBoiseUSA

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