Why do Institutions Offer MOOCs?
Open accessAbstract
By reviewing the literature and interviewing 83 individuals knowledgeable about massive open online courses (MOOCs), we investigate the goals of institutions of higher education that are currently developing and delivering such courses. We identify six major goals for MOOC initiatives: extending reach and access; building and maintaining brand; improving economics by reducing costs or increasing revenues; improving educational outcomes; innovation in teaching and learning; and conducting research on teaching and learning. Comparing these goals with the data being collected about MOOCs, their participants, and educational outcomes, as well as the resource requirements and cost drivers of the development and delivery process, we assess whether these goals are being met, or are likely to be in the future. While quantification of success in achieving these goals is for the most part lacking, we conclude that institutions are experiencing at least partial success in achieving each of these goals except for improving economics. We identify obstacles to fuller achievement of the goals and some potential solutions.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the past few years, the popularity of Massive Online Open Courses (MOOCS) has grown exponentially with the emergence of platforms like Coursera, Udemy, Udacity, LinkedIn Learning and edX.
“In the past few years, the popularity of Massive Online Open Courses (MOOCS) has grown exponentially with the emergence of platforms like Coursera, Udemy, Udacity, LinkedIn Learning and edX [5, 16, 28].”
From Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021 (2022) · cites this paper as [28]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 36 · Cited by 101
Research works printed but not linked: 4
- Dernoncourt, F., Taylor, C., O'Reilly, U., Veeramachaneni, K., Wu, S., Do, C., & Halawa, S. (2013, December). MoocViz: A large scale, open access, collaborative, data analytics platform for MOOCs. Paper presented at NIPS Workshop on Data-Driven Education, Lake Tahoe, Nevada. Retrieved from http://groups.csail.mit.edu/EVO- DesignOpt/groupWebSite/uploads/Site/MoocViz.pdf
- Ghadiri, K., Qayoumi, M. H., Junn, E., Hsu, P., & Sujitparapitaya, S. (2013). The transformative potential of blended learning using MIT edX's 6.002x online MOOC content combined with student team- based learning in class. JUCE (Japanese Universities Association for Computer Education) Journal, 3.
- Ho, A. D., Reich, J., Nesterko, S. O., Seaton, D. T., Mullaney, T., Waldo, J., & Chuang, I. (2014). HarvardX and MITx: The first year of open online courses [HarvardX and MITx Working Paper No. 1]. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2381263
- Nguyen, A., Piech, C., Huang, J., & Guibas, L. (2014). Codewebs: Scalable homework search for massive open online programming courses. Proceedings of the 23rd International World Wide Web Conference, Seoul, Korea. Retrieved from http://www.stanford.edu/~jhuang11/research/pubs/www14/nphg-www14.pdf
- Authors
- Hollands, F. M., & Tirthali, D.
- Affiliations
- Columbia University (US)
- Brown University (US)
- Venue
- Online Learning
- Publisher
- The Online Learning Consortium
- Published
- 2014-08-25
- Volume
- 18
- Issue
- 3
- ISSN
- 1092-8235 (ISSN-L)
- 2472-5730
- 2472-5749
- OpenAlex
- W2109492167
- Cited by
- 101
- References
- 36
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 3 · 2023: 5 · 2022: 9 · 2021: 13 · 2020: 12 · 2019: 13 · 2018: 12 · 2017: 11 · 2016: 9 · 2015: 7
- FWCI
- 13.40
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- other-oa
- Locations
- Online Learning (publishedVersion, other-oa)
- Scholarly Commons (University of Pennsylvania) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Education › Online and Blended Learning
- Physical Sciences › Computer Science › Computer Science Applications › Open Education and E-Learning
- Keywords
- massive open online courses, MOOCs, higher education institutions, institutional goals, access to education, institutional branding, educational outcomes, educational innovation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
