Research Article

How Can Learner Analytics Data Inform Language MOOC Design?

Volume: 35 Number: 1 November 12, 2018
  • Suzi Lee *
  • Robert S. Kadel
  • Amanda Madden
  • Yakut Gazi
TR

How Can Learner Analytics Data Inform Language MOOC Design?

Abstract

This study explores student engagement in a Massive Open Online Course (MOOC) designed to teach advanced-level speaking in English. The course, with over 200,000 students enrolled, was offered on the Coursera platform. Learners’ engagement with course elements in relation to their performance in the course was analyzed with a view to improving course design and activities. The results point to positive effects of quiz completion, peer assessment as well as video watching on course performance.

Keywords

References

  1. Bárcena, E., Read, T., Martín-Monje, E., & Castrillo, M. (2014). Analysing student participation in foreign language MOOCs: A case study. In U. Cress & C. Delgado Kloos (Eds.), Proceedings of the European MOOC Stakeholder Summit 2014 (pp. 11-17). First International Conference on Learning Analytics and Knowledge (22 July 2010). Retrieved from https://tekri.athabascau.ca/analytics/ Gelan, A., Fastré, G., Verjans, M., Martin, N., Janssenswillen, G., Creemers, M., Lieben, J, Depaire, B., & Thomas, M. (2018). Affordances and limitations of learning analytics for computer-assisted language learning: A case study of the VITAL project. Computer Assisted Language Learning, 31(3), 1-26. Gimeno-Sanz, A., Navarro-Laboulais, C., & Despujol-Zabala, I. (2017). Additional functionalities to convert an xMOOC into an xLMOOC. In European Conference on Massive Open Online Courses (pp. 48-57). Springer, Cham. Godwin-Jones, R. (2014). Global reach and local practice: The promise of MOOCs. Language Learning & Technology, 18, 5–15. Guo P. J., Kim J., & Robin R. (2014). How video production affects student engagement: An empirical study of MOOC videos. ACM Conference on Learning at Scale (L@S 2014). Martín-Monje, E., Castrillo, M. D., & Mañana-Rodríguez, J. (2017). Understanding online interaction in language MOOCs through learning analytics. Computer Assisted Language Learning, 31(3), 251-272. Montero P. M., Van Den Noortgate, W., & Desmet, P. (2013). Captioned video for L2 listening and vocabulary learning: A meta-analysis. System, 41, 720-739. Rienties, B., Nguyen, Q., Holmes, W., & Reedy, K. (2017). A review of ten years of implementation and research in aligning learning design with learning analytics at the Open University UK. Interaction Design and Architecture(s), 33, 134-154. Shah, K., Bach, M., Qin, N., Liu, A., Hussen, H., Lee, J.Y., & Kadel, R. (2017). Inferring student success predictors for CS1301x online course at Georgia Tech. Poster session presented at the American Society of Engineering Education STEM Education Expo, Atlanta, GA. Sokolik, M. (2014). What constitutes an effective language MOOC? In E. Martin Monje & E. Bárcena (Eds.), Language MOOCs: Providing learning, transcending boundaries (pp. 17-32). Berlin: De Gruyter Open. Türkay, S., Eidelman, H., Rosen, Y., Seaton, D., Lopez, G., & Whitehill, J. (2017). Getting to know English language learners in MOOCs: Their motivations, behaviors, and outcomes. In Proceedings of the Fourth (2017) ACM Conference on Learning@ Scale (pp. 209-212). Cambridge, Massachusetts.   Uchidiuno, J., Koedinger, K., Hammer, J., Yarzebinski, E., & Ogan, A. (2017). How do English language learners interact with different content types in MOOC videos? International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-017-0156-x Wiggins, G., & McTighe, J. (2005). Understanding by design (2nd ed.). Alexandria, VA: ASCD.

Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Suzi Lee * This is me

Robert S. Kadel This is me

Amanda Madden This is me

Publication Date

November 12, 2018

Submission Date

June 29, 2018

Acceptance Date

September 15, 2018

Published in Issue

Year 2018 Volume: 35 Number: 1

APA
Lee, S., Kadel, R. S., Madden, A., & Gazi, Y. (2018). How Can Learner Analytics Data Inform Language MOOC Design? Bogazici University Journal of Education, 35(1), 19-29. https://izlik.org/JA29ZE64HA
AMA
1.Lee S, Kadel RS, Madden A, Gazi Y. How Can Learner Analytics Data Inform Language MOOC Design? BUJE. 2018;35(1):19-29. https://izlik.org/JA29ZE64HA
Chicago
Lee, Suzi, Robert S. Kadel, Amanda Madden, and Yakut Gazi. 2018. “How Can Learner Analytics Data Inform Language MOOC Design?”. Bogazici University Journal of Education 35 (1): 19-29. https://izlik.org/JA29ZE64HA.
EndNote
Lee S, Kadel RS, Madden A, Gazi Y (November 1, 2018) How Can Learner Analytics Data Inform Language MOOC Design? Bogazici University Journal of Education 35 1 19–29.
IEEE
[1]S. Lee, R. S. Kadel, A. Madden, and Y. Gazi, “How Can Learner Analytics Data Inform Language MOOC Design?”, BUJE, vol. 35, no. 1, pp. 19–29, Nov. 2018, [Online]. Available: https://izlik.org/JA29ZE64HA
ISNAD
Lee, Suzi - Kadel, Robert S. - Madden, Amanda - Gazi, Yakut. “How Can Learner Analytics Data Inform Language MOOC Design?”. Bogazici University Journal of Education 35/1 (November 1, 2018): 19-29. https://izlik.org/JA29ZE64HA.
JAMA
1.Lee S, Kadel RS, Madden A, Gazi Y. How Can Learner Analytics Data Inform Language MOOC Design? BUJE. 2018;35:19–29.
MLA
Lee, Suzi, et al. “How Can Learner Analytics Data Inform Language MOOC Design?”. Bogazici University Journal of Education, vol. 35, no. 1, Nov. 2018, pp. 19-29, https://izlik.org/JA29ZE64HA.
Vancouver
1.Suzi Lee, Robert S. Kadel, Amanda Madden, Yakut Gazi. How Can Learner Analytics Data Inform Language MOOC Design? BUJE [Internet]. 2018 Nov. 1;35(1):19-2. Available from: https://izlik.org/JA29ZE64HA

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