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The Learning Analytics System that Improves the Teaching-Learning Experience of MOOC Instructors and Students

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Learning Technologies and Systems (ICWL 2022, SETE 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13869))

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Abstract

Great learning opportunities are provided through MOOCs. However, MOOCs provide a number of challenges for students. Many students find it difficult to successfully finish MOOCs due to a variety of factors, including feelings of loneliness, a lack of support, and a lack of feedback. Additionally, the instructors of these courses are highly concerned about this situation and want to reduce these difficulties for their students. Due to the large number of students registered in these courses, this is not a simple task. To help both instructors and students, we created edX-LIMS, a learning analytics (LA) system that allows MOOC instructors to monitor the progress of their students and carry out an intervention strategy in their students’ learning thanks to a Web-based Instructor Dashboard. Furthermore, this LA system provides MOOC students with detailed feedback on their course performance as well as advice on how to improve it thanks to Web-based Learner Dashboards. This LA system have been used for more than two year in a MOOC at edX. During this period the Dashboards supported by the system have been improved, and as a result, MOOC students now appreciate the fact that they feel guided, engagement and motivated to complete the course, among other feelings. MOOC instructor have improved their student monitoring tasks and are better able to identify students who need assistance. Moreover thanks to the services that the intervention strategy supported by the LA system offer to them, now students and instructors feel that are connected.

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References

  1. Ma, L., Lee, C.S.: Investigating the adoption of MOOCs: a technology-user-environment perspective. J. Comput. Assist. Learn. 35(1), 89–98 (2019). https://doi.org/10.1111/jcal.12314

    Article  Google Scholar 

  2. Pardo, A., Jovanovic, J., Dawson, S., Gašević, D., Mirriahi, N.: Using learning analytics to scale the provision of personalised feedback. Br. J. Educ. Technol. 50(1), 128–138 (2019). https://doi.org/10.1111/bjet.12592

    Article  Google Scholar 

  3. Iraj, H., Fudge, A., Faulkner, M., Pardo, A., Kovanović, V.: Understanding students’ engagement with personalised feedback messages. In: LAK 2020 Proceedings, pp. 438–447. https://doi.org/10.1145/3375462.3375527

  4. Hone, K.S., El Said, G.R.: Exploring the factors affecting MOOC retention: a survey study. Comput. Educ. 98, 157–168 (2016). https://doi.org/10.1016/j.compedu.2016.03.016

    Article  Google Scholar 

  5. Topali, P., Ortega-Arranz, A., Er, E., Martínez-Monés, A., Villagrá-Sobrino, S.L., Dimitriadis, Y.: Exploring the problems experienced by learners in a MOOC implementing active learning pedagogies. In: Calise, M., Delgado Kloos, C., Reich, J., Ruiperez-Valiente, J., Wirsing, M. (eds.) Digital Education: At the MOOC Crossroads Where the Interests of Academia and Business Converge, vol. 11475, pp. 81–90. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-19875-6_10

  6. Cobos, R., Soberón, J.: A proposal for monitoring the intervention strategy on the learning of MOOC learners. In: CEUR Conference Proceedings. LASI-Spain 2020. Learning Analytics Summer Institute Spain 2020: Learning Analytics. Time for Adoption? Valladolid, Spain. http://ceur-ws.org/Vol-2671/paper07.pdf

  7. Lang, C., Siemens, G., Wise, A., Gasevic, D.: Handbook of Learning Analytics. Society for Learning Analytics Research (SoLAR) (2017). https://doi.org/10.18608/hla17

  8. Romero, C., Ventura, S.: Educational data mining and learning analytics: an updated survey. WIREs Data Mining Knowl. Discov. 10(3) (2020). https://doi.org/10.1002/widm.1355

  9. Sa’don, N.F., Alias, R.A., Ohshima, N.: Nascent research trends in MOOCs in higher educational institutions: a systematic literature review. In: The 2014 International Conference on Web and Open Access to Learning Proceedings (ICWOAL 2014), pp. 1–4 (2014). https://doi.org/10.1109/ICWOAL.2014.7009215

  10. Fauvel, S., et al.: Artificial intelligence powered MOOCs: a brief survey. In: Proceedings of the 2018 IEEE International Conference on Agents (ICA 2018), pp. 56–61 (2018). https://doi.org/10.1109/AGENTS.2018.8460059

  11. Babori, A., Fassi, H.F., Zaid, A.: Research on MOOCs: current trends and taking into account of content. In: Proceedings of the 2nd ACM International Conference on Networking, Information Systems & Security (NISS 2019), art. nr. 17, pp. 1–9 (2019). https://doi.org/10.1145/3320326.3320349

  12. Ferguson, R., et al.: Research evidence on the use of learning analytics - implications for education policy. In: Vuorikari, R., Castaño Muñoz, J. (eds.) European Commission’s Joint Research Centre Science for Policy Report (JRC), EUR 28294 EN (2016). https://doi.org/10.2791/955210. ISBN 978-92-79-64441-2

  13. Martínez Monés, A., et al.: Achievements and challenges in learning analytics in Spain: the view of SNOLA. Revista Iberoamericana de Educación a Distancia 23(2), 187–212 (2020). https://doi.org/10.5944/RIED.23.2.26541

    Article  Google Scholar 

  14. Onah, D.F.O., Pang, E.E.L., Sinclair, J.E., Uhomoibhi, J.: Learning analytics for motivating self-regulated learning and fostering the improvement of digital MOOC resources. In: Auer, M.E., Tsiatsos, T. (eds.) IMCL 2018. AISC, vol. 909, pp. 14–21. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-11434-3_3

    Chapter  Google Scholar 

  15. Verbert, K., et al.: Learning dashboards: an overview and future research opportunities. Pers. Ubiquit. Comput. 18(6), 1499–1514 (2013). https://doi.org/10.1007/s00779-013-0751-2

    Article  Google Scholar 

  16. Cobos, R., Olmos, L.: A learning analytics tool for predictive modeling of dropout and certificate acquisition on MOOCs for professional learning. In: IEEE International Conference on Industrial Engineering and Engineering Management Proceedings, vol. 2019, pp. 1533–1537 (2019). https://doi.org/10.1109/IEEM.2018.8607541

  17. Moreno-Marcos, P.M., Alario-Hoyos, C., Munoz-Merino, P.J., Kloos, C.D.: Prediction in MOOCs: a review and future research directions. IEEE Trans. Learn. Technol. 12(3), 384–401 (2019). https://doi.org/10.1109/TLT.2018.2856808

    Article  Google Scholar 

  18. Cobos, R., Ruiz-Garcia, J.C.: Improving learner engagement in MOOCs using a learning intervention system: a research study in engineering education. Comput. Appl. Eng. Educ. 29(4), 733–749 (2021). https://doi.org/10.1002/cae.22316

    Article  Google Scholar 

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Acknowledgments

This work has been co-funded by the Madrid Regional Government through the e-Madrid-CM Project under Grant S2018/TCS-4307, a project which is co-funded by the European Structural Funds (FSE and FEDER). This research has been co-funded by the National Research Agency of the Spanish Ministry of Science, Innovation and Universities under project grant RED2018–102725-T (SNOLA). And, this research has been co-funded by the National Research Agency of the Spanish Ministry of Science and Innovation under project grants PID2019-105951RB-I00 (IndiGo!) and PID2021-127641OB-I00/AEI/FEDER https://doi.org/10.13039/501100011033 (BBforTAI).

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Authors and Affiliations

  1. Computer Science Department, Universidad Autónoma de Madrid, Madrid, Spain

    Ruth Cobos

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  1. Ruth Cobos
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Correspondence to Ruth Cobos .

Editor information

Editors and Affiliations

  1. Universidad de La Laguna, Tenerife, Spain

    Carina S. González-González

  2. Universidad Complutense de Madrid, Madrid, Madrid, Spain

    Baltasar Fernández-Manjón

  3. Durham University, Durham, UK

    Frederick Li

  4. Universidad de Salamanca, Salamanca, Spain

    Francisco José García-Peñalvo

  5. Mercatorum University, Rome, Italy

    Filippo Sciarrone

  6. Université de Caen Normandie, Caen, France

    Marc Spaniol

  7. University of Salamanca, Salamanca, Spain

    Alicia García-Holgado

  8. Universidad de La Laguna, Tenerife, Spain

    Manuel Area-Moreira

  9. University of Hagen, Hagen, Germany

    Matthias Hemmje

  10. South China Normal University, Guangzhou, China

    Tianyong Hao

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Cobos, R. (2023). The Learning Analytics System that Improves the Teaching-Learning Experience of MOOC Instructors and Students. In: González-González, C.S., et al. Learning Technologies and Systems. ICWL SETE 2022 2022. Lecture Notes in Computer Science, vol 13869. Springer, Cham. https://doi.org/10.1007/978-3-031-33023-0_3

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  • DOI: https://doi.org/10.1007/978-3-031-33023-0_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-33022-3

  • Online ISBN: 978-3-031-33023-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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