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 [aut, cre], Dr. Irene Vrbik [aut, cph]
Maintainer:	Daniel Krasnov <danielkrasnovdk at hotmail.com>
BugReports:	https://github.com/Danyulll/CurricularAnalytics/issues
License:	MIT + file LICENSE
URL:	https://github.com/Danyulll/CurricularAnalytics
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	CurricularAnalytics results

Documentation:

Reference manual:	CurricularAnalytics.pdf
Vignettes:	CurricularAnalytics

Downloads:

Package source:	CurricularAnalytics_1.0.0.tar.gz
Windows binaries:	r-devel: CurricularAnalytics_1.0.0.zip, r-release: CurricularAnalytics_1.0.0.zip, 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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