Coded Dataset of a Literature Review on Learning Sequence Analysis

doi: 10.4121/10fc3a10-37aa-4292-818d-468b940b2bb7.v2
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/10fc3a10-37aa-4292-818d-468b940b2bb7
Datacite citation style:
Valle Torre, Manuel; Specht, Marcus; Oertel, Catharine (2023): Coded Dataset of a Literature Review on Learning Sequence Analysis . Version 2. 4TU.ResearchData. dataset.
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
choose version:
version 2 - 2023-12-06 (latest)
version 1 - 2023-05-24

Coded dataset of a literature review on the use of sequential analysis in learning analytics and educational data mining research. The analysis was performed on 74 publications from 2010 to 2023, obtained from queries on SCOPUS and Web of Science. The literature review contains detailed information about the search terms, inclusion rules, and coding categories (to be published in late March during the LAK24 conference, pre-print available upon request).

The worksheet named 'ArticlesByCategoty' contains the data that coded from the articles, and then used in the analysis and interpretation of the literature review. The 'QueryResults' worksheet contains the articles that resulted from the database queries.

  • 2023-05-24 first online
  • 2023-12-06 published, posted
TU Delft, Electrical Engineering, Mathematics and Computer Science, Department of Software Technology
TU Delft, Centre for Education and Learning


files (1)