CurricularAnalytics: Exploring and Analyzing Academic Curricula

Provides an implementation of ‘Curricular Analytics’, a framework for analyzing and quantifying the complexity of academic curricula. Curricula are modelled as directed acyclic graphs and analytics are provided based on path lengths and edge density. This work directly comes from Heileman et al. (2018) <doi:10.48550/arXiv.1811.09676>.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: dplyr (≥ 1.1.4), igraph (≥ 2.0.3), stats (≥ 4.4.0), tools (≥ 4.4.0), utils (≥ 4.4.0), visNetwork (≥ 2.1.2)
Suggests: knitr, rmarkdown
Published: 2024-05-29
DOI: 10.32614/CRAN.package.CurricularAnalytics
Author: Daniel Krasnov ORCID iD [aut, cre], Dr. Irene Vrbik [aut, cph]
Maintainer: Daniel Krasnov <danielkrasnovdk at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: CurricularAnalytics results


Reference manual: CurricularAnalytics.pdf
Vignettes: CurricularAnalytics


Package source: CurricularAnalytics_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel: not available
macOS binaries: r-release (arm64): CurricularAnalytics_1.0.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): CurricularAnalytics_1.0.0.tgz, r-oldrel (x86_64): not available


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