Philip J. Guo
ABSTRACT
The current generation of Massive Open Online Courses (MOOCs) attract a diverse student audience from all age groups and over 196 countries around the world. Researchers, educators, and the general public have recently become interested in how the learning experience in MOOCs differs from that in traditional courses. A major component of the learning experience is how students navigate through course content.
This paper presents an empirical study of how students navigate through MOOCs, and is, to our knowledge, the first to investigate how navigation strategies differ by demographics such as age and country of origin. We performed data analysis on the activities of 140,546 students in four edX MOOCs and found that certificate earners skip on average 22% of the course content, that they frequently employ non-linear navigation by jumping backward to earlier lecture sequences, and that older students and those from countries with lower student-teacher ratios are more comprehensive and non-linear when navigating through the course.
From these findings, we suggest design recommendations such as for MOOC platforms to develop more detailed forms of certification that incentivize students to deeply engage with the content rather than just doing the minimum necessary to earn a passing grade. Finally, to enable other researchers to reproduce and build upon our findings, we have made our data set and analysis scripts publicly available.
- MaxMind GeoIP databases and web services. http://www.maxmind.com/en/geolocation_landing.Google Scholar
- Bates, T. What's Right and What's Wrong About Coursera-style MOOCs?, 2012. Blog entry retrieved from http://www.tonybates.ca/2012/08/05/whats-right-and-whats-wrong-about-coursera-\\style-moocs/.Google Scholar
- Breslow, L., Pritchard, D. E., DeBoer, J., Stump, G. S., Ho, A. D., and Seaton, D. T. Studying Learning in the Worldwide Classroom: Research into edX's First MOOC. Research and Practice in Assessment 8 (2013).Google Scholar
- Chen, S. Y., and Ford, N. J. Modelling User Navigation Behaviours in a Hypermedia-based Learning System : An Individual Differences Approach. Knowledge organization 25, 3 (1998), 67--78.Google Scholar
- Cheng, Y. W., Sudweeks, F., Cheng, Y. W., and Sudweeks, F. A Longitudinal Study on the Effect of Hypermedia on Learning Dimensions, Culture and Teaching Evaluation. In Proc. Cultural Attitudes Towards Technology and Communication (2012), 146--162.Google Scholar
- Clarà, M., and Barberà, E. Learning Online: Massive Open Online Courses (MOOCs), Connectivism, and Cultural Psychology. Distance Education 34, 1 (2013), 129--136.Google ScholarCross Ref
- Coetzee, D., Fox, A., Hearst, M. A., and Hartmann, B. Should Your MOOC Forum Use a Reputation System? In Proc. CSCW'14, ACM (2014). Google ScholarDigital Library
- E. Truluck, Bradley C. Courtenay, J. Learning Style Preferences Among Older Adults. Educational Gerontology 25, 3 (1999), 221--236.Google Scholar
- Ford, N., and Chen, S. Y. Matching/Mismatching Revisited: An Empirical Study of Learning and Teaching Styles. British Journal of Educational Technology 32, 1 (2001), 5--22.Google Scholar
- Grünewald, F., Meinel, C., Totschnig, M., and Willems, C. Designing MOOCs for the Support of Multiple Learning Styles. In Scaling up Learning for Sustained Impact. Springer, 2013, 371--382.Google Scholar
- Hofstede, G. Cultural Differences in Teaching and Learning. International Journal of Intercultural Relations 10 (1986), 301--320.Google ScholarCross Ref
- Kennedy, P. Learning Cultures and Learning Styles: Myth-understandings about Adult (Hong Kong) Chinese Learners. International Journal of Lifelong Education 21, 5 (2002), 430--445.Google Scholar
- Kizilcec, R. F. Collaborative Learning in Geographically Distributed and In-person Groups. In AIED 2013 Workshop on Massive Open Online Courses (2013).Google Scholar
- Kizilcec, R. F., Piech, C., and Schneider, E. Deconstructing Disengagement: Analyzing Learner Subpopulations in Massive Open Online Courses. In Proc. Learning Analytics and Knowledge, ACM (2013), 170--179. Google ScholarDigital Library
- Lee, C., Sudweeks, F., and Cheng, Y. The Role of Unit Evaluation, Learning and Culture Dimensions Related to Students Cognitive Style in Hypermedia Learning. In Proc. Cultural Attitudes Towards Communication and Technology (2010).Google Scholar
- Lee, M. W., Y., C. S., Chrysostomou, K., and Liu, X. Mining Students' Behavior in Web-based Learning Programs. Expert Systems with Applications 36, 2 (2009), 3459--3464. Google ScholarDigital Library
- Liegle, J. O., and Janicki, T. N. The Effect of Learning Styles on the Navigation Needs of Web-based Learners. Computers in Human Behavior 22, 5 (2006), 885--898.Google Scholar
- McLoughlin, C. E. The Pedagogy of Personalised Learning: Exemplars, MOOCS and Related Learning Theories. In Proc. EdMedia (2013).Google Scholar
- Milligan, C., Littlejohn, A., and Margaryan, A. Patterns of Engagement in Connectivist MOOCs. MERLOT Journal of Online Learning and Teaching 9, 2 (2013).Google Scholar
- Naidu, S. Learning About Learning and Teaching Online. Distance Education 34, 1 (2013), 1--3.Google Scholar
- Pask, G. Styles and Strategies of Learning. British Journal of Educational Psychology 46, 2 (1976), 128--148.Google Scholar
- Reed, W., and Oughton, J. Computer Experience and Interval-based Hypermedia Navigation. Journal of Research on Computing in Education 30 (1997), 38--52.Google Scholar
- UNESCO Institute for Statistics. Pupil-teacher ratio, primary. http://data.worldbank.org/indicator/SE.PRM.ENRL.TC.ZS.Google Scholar
- Witkin, H. A., Moore, C. A., and Goodenough, D. R. Field-Dependent and Field-Independent Cognitive Styles and Their Educational Implications. Review of Educational Research 47, 1 (1977).Google Scholar
Index Terms
- Demographic differences in how students navigate through MOOCs
Recommendations
MOOCs: So Many Learners, So Much Potential ...
Massive open online courses (MOOCs) have exploded onto the scene, promising to satisfy a worldwide thirst for a high-quality, personalized, and free education. This article explores where MOOCs fit within the e-learning and Artificial Intelligence in ...
On the path to self-determined learning: a mixed methods study of learners' attributes and strategies to learn in language MOOCs
In this study, we employ heutagogy (self-determined learning) to learn about autonomous learning characteristics of language MOOC learners using an embedded correlational mixed methods design. We administered quantitative and qualitative questionnaires to ...
Problem-Based Learning in a MOOC
CSEDU 2016: Proceedings of the 8th International Conference on Computer Supported EducationThis paper describes a MOOC about PBL which is designed â as far as possible in the setting of a MOOC- in
line with modern learning principles that are also at the basis of PBL: constructive, contextual,
collaborative and self-directed learning: Problem-...
Comments