Chrome Plug-in to Support SRL in MOOCs

  • María Elena Alonso-Mencía
  • Carlos Alario-HoyosEmail author
  • Carlos Delgado Kloos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11475)


Massive Open Online Courses (MOOCs) have gained popularity over the last years, offering a learning environment with new opportunities and challenges. These courses attract a heterogeneous set of participants who, due to the impossibility of personal tutorship in MOOCs, are required to create their own learning path and manage one’s own learning to achieve their goals. In other words, they should be able to self-regulate their learning. Self-regulated learning (SRL) has been widely explored in settings such as face-to-face or blended learning environments. Nevertheless, research on SRL in MOOCs is still scarce, especially on supporting interventions. In this sense, this document presents MOOCnager, a Chrome plug-in to help learners improve their SRL skills. Specifically, this work focuses on 3 areas: goal setting, time management and selfevaluation. Each area is included in one of the 3 phases composing Zimmerman’s SRL Cyclical Model. In this way, the plug-in aims to support enrolees’ self-regulation throughout their complete learning process. Finally, MOOCnager was uploaded to the Chrome Web Store, in order to get a preliminary evaluation with real participants from 6 edX Java MOOCs designed by the Universidad Carlos III de Madrid (UC3M). Results were not conclusive as the use of the plug-in by the participants was very low. However, learners seem to prefer a seamless tool, integrated in the MOOC platform, which is able to assist them without any learner-tool interaction.


Self-regulated learning Massive Open Online Course Plug-in MOOCnager Tool 



The authors acknowledge the eMadrid Network, funded by the Madrid Regional Government (Comunidad de Madrid) with grant No. P2018/TCS-4307. This work also received partial support from the Spanish Ministry of Economy and Competitiveness/Ministry of Science, Innovation, and Universities, Projects RESET (TIN2014-53199-C3-1-R) and Smartlet (TIN2017-85179-C3- 1-R), and from the European Commission through Erasmus+ projects COMPETEN-SEA (574212-EPP-1-2016-1-NL-EPPKA2-CBHE-JP), LALA (586120-EPP-1-2017-1-ES-EPPKA2- CBHE-JP), and InnovaT (598758-EPP-1-2018-1-AT-EPPKA2-CBHE-JP).


  1. 1.
    McAuley, A., Stewart, B., Siemens, G., Cormier, D.: The MOOC Model for Digital Practice. University of Prince Edwards Island, Canada (2010)Google Scholar
  2. 2.
    Gašević, D., Kovanovic, V., Joksimovic, S., Siemens, G.: Where is research on massive open online courses headed? A data analysis of the MOOC research initiative. Int. Rev. Res. Open Distrib. Learn. 15(5), 134–176 (2014)Google Scholar
  3. 3.
    Shah D.: By the numbers: MOOC in 2017. Accessed 24 Dec 2018
  4. 4.
    Clow, D.: MOOCs and the funnel of participation. In: Proceedings of the 3rd International Conference on Learning Analytics and Knowledge, pp. 185–189. ACM, Leuven (2013)Google Scholar
  5. 5.
    Khalil, H., Ebner, M.: MOOCs completion rates and possible methods to improve retention- a literature review. In: Proceedings of the 22nd World Conference on Educational Multimedia, Hypermedia and Telecommunications, pp. 1236–1244. AACE, Tampere (2014)Google Scholar
  6. 6.
    Min, L., Jingyan, L.: Assessing the effectiveness of self-regulated rearning in MOOCs using macro-level behavioural sequence data. In: Proceedings of the 5th European MOOCs Stake- Holders Summit - Work in Progress Papers, pp. 1–9. CEUR, Madrid (2017)Google Scholar
  7. 7.
    Pérez-Sanagustín, R., Maldonado-Mahauad, J.J.: How to design tools for supporting self-regulated learning in MOOCs? Lessons learned from a literature review from 2008 to 2016. In: Proceedings of the 42nd Latin American Computing Conference, pp. 1–12. IEEE, Valparaíso (2016)Google Scholar
  8. 8.
    Alonso-Mencía, M.E., Alario-Hoyos, C., Maldonado-Mahauad, J., Estévez-Ayres, I., Pérez-Sanagustín, M., Delgado, C.: Self-regulated learning in MOOCs: lessons learned from a literature review. Edu. Rev. (2019, forthcoming)Google Scholar
  9. 9.
    Jansen, R.S., Van Leeuwen, A., Janssen, J., Kester, L., Kalz, M.: Validation of the self-regulated online learning questionnaire. J. Comp. High. Educ. 29(1), 6–27 (2017)CrossRefGoogle Scholar
  10. 10.
    Panadero, E.: A review of self-regulated learning: six models and four directions for research. Front. Psychol. 8, 1–28 (2017)CrossRefGoogle Scholar
  11. 11.
    Zimmerman, B.J.: Attaining self-regulation: a social cognitive perspective. In: Boekaerts, M., Pintrich, P., Zeidner, M. (eds.) Handbook of Self-regulation, pp. 13–39. Academic Press (2000)Google Scholar
  12. 12.
    Onah, D.F., Sinclair, J.E.: Measuring self-regulated learning in a novel e-learning platform: eLDa. In: Proceedings of the 15th Koli Calling Conference on Computing Education Research, pp. 167–168. ACM, Koli (2015)Google Scholar
  13. 13.
    Onah, D.F.O., Sinclair, J.E.: A multi-dimensional investigation of self-regulated learning in a blended classroom context: a case study on eLDa MOOC. In: Auer, M., Guralnick, D., Uhomoibhi, J. (eds.) ICL 2016. AISC, vol. 545, pp. 63–85. Springer, Cham (2017)Google Scholar
  14. 14.
    Onah, D.F., Sinclair, J.E.: Design science MOOC: a framework of good practice pedagogy in a novel e-learning platform eLDa. In: Proceedings of 28th Annual World Conference on Educational Media and Technology, pp. 1–7. AACE, Vancouver (2016)Google Scholar
  15. 15.
    Yousef, A.M., Chatti, M.A., Danoyan, N., Thüs, H., Schroeder, U.: Video-mapper: a video annotation tool to support collaborative learning in MOOCs. In: Proceedings of the 3rd European MOOCs Stakeholders Summit EMOOCs, Mons, pp. 131–140 (2015)Google Scholar
  16. 16.
    Pérez-Álvarez, R., Maldonado-Mahauad, J.J., Sapunar-Opazo, D., Pérez-Sanagustín, M.: NoteMyProgress: a tool to support learners’ self-regulated learning strategies in MOOC environments. In: Lavoué, É., Drachsler, H., Verbert, K., Verbert, J., Pérez-Sanagustín, M. (eds.) EC-TEL 2017. LNCS, vol. 10474, pp. 460–466. Springer, Cham (2017). Scholar
  17. 17.
    Jo, Y., Tomar, G., Ferschke, O., Rosé, C.P., Gašević, D.: Expediting support for social learning with behavior modeling. In: Proceedings of the 9th International Conference on Educational Data Mining, Raleigh, pp. 400–405 (2016)Google Scholar
  18. 18.
    Kizilcec, R.F., Pérez-Sanagustín, M., Maldonado, J.J.: Self-regulated learning strategies predict learner behavior and goal attainment in massive open online courses. Comput. Educ. 104, 18–33 (2017)CrossRefGoogle Scholar
  19. 19.
    Chen, P.J., Chen, Y.H.: Facilitating MOOCs learning through weekly meet-up: a case study in Taiwan. In: Proceedings of the 1st ACM Conference on Learning@ Scale Conference, pp. 183–184. ACM, Atlanta (2014)Google Scholar
  20. 20.
    de Waard, I., Kukulska-Hulme, A., Sharples, M.: Self-directed learning in trial FutureLearn courses. In: Proceedings of the 3rd European Stakeholder Summit EMOOCs, Mons, pp. 234–243 (2015)Google Scholar
  21. 21.
    Milligan, C., Littlejohn, A.: How health professionals regulate their learning in massive open online courses. Internet High. Edu. 31, 113–121 (2016)CrossRefGoogle Scholar
  22. 22.
    Davis, D., Chen, G., Jivet, I., Hauff, C., Houben, G.J.: Encouraging metacognition and self-regulation in MOOCs through increased learner feedback. In: Proceedings of the Learning Analytics and Knowledge Workshop on Learning Analytics for Learners, pp. 17–22. CEUR, Edinburgh (2016)Google Scholar
  23. 23.
    Ruiz, S., Charleer, S., Urretavizcaya, M., Klerkx, J., Fernández-Castro, I., Duval, E.: Supporting learning by considering emotions: tracking and visualization a case study. In: Proceedings of the 6th International Conference on Learning Analytics and Knowledge, pp. 254–263. ACM, Edinburgh (2016)Google Scholar
  24. 24.
    Guo, P.J., Reinecke, K.: Demographic differences in how students navigate through MOOCs. In: Proceedings of the 1st ACM conference on Learning@ scale Conference, pp. 21–30. ACM, Atlanta (2014)Google Scholar
  25. 25.
    Leris, D., Sein-Echaluce, M.L., Hernández, M., Bueno, C.: Validation of indicators for implementing an adaptive platform for MOOCs. Comput. Hum. Behav. 72, 783–795 (2017)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • María Elena Alonso-Mencía
    • 1
  • Carlos Alario-Hoyos
    • 1
    Email author
  • Carlos Delgado Kloos
    • 1
  1. 1.Department of Telematics EngineeringUniversidad Carlos III de MadridMadridSpain

Personalised recommendations