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

Valle Torre, Manuel; Specht, Marcus; Oertel, Catharine (2023): Coded Dataset of a Literature Review on Learning Sequence Analysis . Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/10fc3a10-37aa-4292-818d-468b940b2bb7.v1

Dataset

• Education Systems
• Other Information and Computing Sciences
• Information and Computing Sciences
• Education

Educational Data Mining, Learning Analytics, Learning Sequence Analysis, Literature Review, Sequence Analysis

2006-2021

CC0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Manuel Valle Torre, Marcus Specht, Catharine Oertel

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 44 publications from 2006 to 2022, obtained from queries on SCOPUS and Web of Science. Visit the literature review for detailed information about the search terms, inclusion rules, and coding categories.

The worksheet named 'Finished' contains the data that resulted in the analysis and interpretation of the literature review, while the 'Raw' worksheet contains the information as it was extracted from Atlas.ti, where it was originally coded.

• 2023-05-24 first online, published, posted

4TU.ResearchData

*.xlsx

TU Delft, Electrical Engineering, Mathematics and Computer Science, Department of Software Technology
TU Delft, Centre for Education and Learning