This project contains supplementary the full materials and methods including an extended description methodology and code utilize to generate the results of the following paper: > J.A. Ruipérez-Valiente et al. (2022). Large Scale Analytics of Global and > Regional MOOC Providers: Differences in Learners' Demographics, > Preferences, and Perceptions. *Computers & Education*, 180, 104426. DOI: > [10.1016/j.compedu.2021.104426][1] The next image provides an overview of the methodology that we have followed: @[osf](9evq6) The base project contains two pdfs: 1. **Proposal** ([link][2]): It contains the partnership proposal that we launched to gather a large number of providers . 2. **Survey** ([link][3]): It describes the survey that we designed and launched across six MOOC providers to compare preferences and perceptions in global and regional settings. Then, the project has three additional components described as follow: 1. **Multi-platform Replication Procedure and Code** ([link][4]): It contains a document with the description of the methodology that we have pursued to replicate exactly the same analysis across 15 MOOC providers and the Jupyter IPython script that has been executed to analyze the replication code. 2. **R Analysis of Joint Dataset** ([link][5]): It contains the full array of R scripts that have been used to join the data from all the MOOC providers together, and perform a diverse set of analyses that are used as part of the study. 3. **Aggregate Data and Visualizations** ([link][6]): It contains the entire data output with aggregate data from all the MOOC providers that are the result from the whole analysis, and also diverse visualizations that plot these aggregate data. [1]: https://doi.org/10.1016/j.compedu.2021.104426 [2]: https://osf.io/v6mfh/ [3]: https://osf.io/aqnyt/ [4]: https://osf.io/cm8j7/ [5]: https://osf.io/3ncxe/ [6]: https://osf.io/rbcsy/