Abstract
Massive open online course (MOOC) platforms within the so-called xMOOC framework typically host quizzes, sometimes as part of the course assessment. Within our contribution we look at and describe quizzes and their results as a feedback for learners. Additionally, we describe current research on quizzes in MOOCs, especially from a learning analytics perspective. Building upon this, we explore data from a single MOOC (N = 1,484) from the Austrian MOOC platform iMooX.at where quizzes are used for final assessment but can be repeated up to five times within the course. The analysis of quiz activities shows a moderate correlation (r = 0,2765, N = 957) of the very first attempt with the final MOOC success.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Admiraal, W., Huisman, B., Pilli, O.: Assessment in massive open online courses. Electron. J. e-Learn. 13(4), 207–216 (2015)
Anggraini, A., Tanuwijaya, C.N., Oktavia, T., Meyliana, M., Prabowo, H., Supangkat, S.H.: Analyzing MOOC features for enhancing students learning satisfaction. J. Telecommun. Electron. Comput. Eng. 10(1–4), 67–71 (2018). https://journal.utem.edu.my/index.php/jtec/article/view/3578/0
Chauhan, J., Goel, A.: An analysis of quiz in MOOC. In: Ninth International Conference on Contemporary Computing (IC3) (2016)
Daneji, A.A., Ayub, A.F.M., Khambari, M.N.M.: The effects of perceived usefulness, confirmation and satisfaction on continuance intention in using massive open online course (MOOC). Knowl. Manag. E-Learn. 11(2), 201–214 (2019)
DeSouza, E., Fleming, M.: A comparison of in-class and online quizzes on student exam performance. J. Comput. High. Educ. 14(2), 121–134 (2003)
Ebner, M., Adams, S., Bollin, A., Kopp, M., Teufel, M.: Digital gestütztes Lehren mittels innovativem MOOC-Konzept. journal für lehrerInnenbildung 20(1), 68–77 (2020). https://doi.org/10.35468/jlb-01-2020_05
Ebner, M., et al.: How OER enhances MOOCs—a perspective from German-speaking Europe. In: Jemni, M., Kinshuk, Khribi, M. (eds.) Open Education: From OERs to MOOCs. LNET, pp. 205–220. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-52925-6_11
Ebner, M., Schön, S., Braun, C.: More than a MOOC—seven learning and teaching scenarios to use MOOCs in higher education and beyond. In: Yu, S., Ally, M., Tsinakos, A. (eds.) Emerging Technologies and Pedagogies in the Curriculum. BHMFEI, pp. 75–87. Springer, Singapore (2020). https://doi.org/10.1007/978-981-15-0618-5_5
Ebner, M., Schön, S.: Inverse blended learning – a didactical concept for MOOCs and its positive effects on dropout-rates. In: Ally, M., Amin Embi, M., Norman, H. (eds.) The Impact of MOOCs on Distance Education in Malaysia and Beyond. Routledge (2019)
Ebner, M., Schön, S.: Future teacher training of several universities with MOOCs as OER. In: Ferdig, R.E., Baumgartner, E., Hartshorne, R., Kaplan-Rakowski, R., Mouza, C. (eds.) Teaching, Technology, and Teacher Education during the COVID-19 Pandemic: Stories from the Field. Association for the Advancement of Computing in Education (AACE), pp. 493–497 (2020)
Greller, W., Drachsler, H.: Translating learning into numbers: a generic framework for learning analytics. Educ. Technol. Soc. 15, 42–57 (2012)
Jiang, S., Warschauer, M., Williams, A.E., Schenke, K., O’dowd, D.: Predicting MOOC performance with week 1 behavior. In: Proceedings of the 7th International Conference on Educational Data Mining (2014). https://educationaldatamining.org/EDM2014/uploads/procs2014/short%20papers/273_EDM-2014-Short.pdf
Johnson-Glenberg, M.C.: Embedded formative e-assessment: who benefits who falters. Educ. Media Int. 47(2), 153–171 (2010)
Khalil, M., Ebner, M.: A STEM MOOC for school children - what does learning analytics tell us? In: Proceedings of 2015 International Conference on Interactive Collaborative Learning (ICL), Florence, Italy, pp. 1217–1221 (2015)
Luo, H., Robinson, A.C., Park, J.-Y.: Peer grading in a MOOC: reliability, validity, and perceived effects. J. Asynchronous Learn. Netw. 18(2) (2014)
Papathoma, T., Blake, C., Clow, D., Scanlon, E.: Investigating learners’ views of assessment types in massive open online courses (MOOCs). In: Conole, G., Klobučar, T., Rensing, C., Konert, J., Lavoué, É. (eds.) EC-TEL 2015. LNCS, vol. 9307, pp. 617–621. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24258-3_72
Ren, Z., Rangwala, H., Johri, A.: Predicting performance on MOOC assessments using multi-regression models. Paper presented at the International Conference on Educational Data Mining (EDM) (9th, Raleigh, NC, Jun 29-Jul 2, 2016), International Educational Data Mining Society (2016)
Schaffert, S., Geser, G.: Open educational resources and practices. eLearning Papers 7, 14–19 (2008)
Yang, D., Kraut, R.E., Rose, C.P.: Exploring the effect of student confusion in massive open online courses. J. Educ. Data Mining 8(1), 52–83 (2016)
Yang, M., Shao, Z., Liu, Q., Liu, C.: Understanding the quality factors that influence the continuance intention of students toward participation in MOOCs. Educ. Tech. Res. Dev. 65(5), 1195–1214 (2017)
Acknowledgement
Contributions and development were partly delivered within the project “Learning Analytics: Effects of data analysis on learning success” (01/2020–12/2021) with Graz University of Technology and University of Graz as partners and the Province of Styria as funding body (12. Zukunftsfonds Steiermark).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Schön, S., Leitner, P., Ebner, M., Edelsbrunner, S., Hohla, K. (2022). Quiz Feedback in Massive Open Online Courses from the Perspective of Learning Analytics: Role of First Quiz Attempts. In: Auer, M.E., Hortsch, H., Michler, O., Köhler, T. (eds) Mobility for Smart Cities and Regional Development - Challenges for Higher Education. ICL 2021. Lecture Notes in Networks and Systems, vol 389. Springer, Cham. https://doi.org/10.1007/978-3-030-93904-5_94
Download citation
DOI: https://doi.org/10.1007/978-3-030-93904-5_94
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-93903-8
Online ISBN: 978-3-030-93904-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)