LKT: Logistic Knowledge Tracing

Computes Logistic Knowledge Tracing ('LKT') which is a general method for tracking human learning in an educational software system. Please see Pavlik, Eglington, and Harrel-Williams (2021) <arXiv:2005.00869>. 'LKT' is a method to compute features of student data that are used as predictors of subsequent performance. 'LKT' allows great flexibility in the choice of predictive components and features computed for these predictive components. The system is built on top of 'LiblineaR', which enables extremely fast solutions compared to base glm() in R.

Version: 1.0
Depends: R (≥ 3.5.0)
Imports: lme4 (≥ 1.1-23), pROC (≥ 1.16.2), SparseM (≥ 1.78), utils, Matrix, methods, knitr, data.table (≥ 1.13.2), LiblineaR (≥ 2.10-8), glmnet (≥ 4.0-2), glmnetUtils (≥ 1.1.8), caret
Published: 2021-06-07
Author: Philip I. Pavlik Jr. ORCID iD [aut, ctb, cre], Luke G. Eglington ORCID iD [aut, ctb]
Maintainer: Philip I. Pavlik Jr. <imrryr at gmail.com>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: LKT results

Documentation:

Reference manual: LKT.pdf
Vignettes: Basic_Operations

Downloads:

Package source: LKT_1.0.tar.gz
Windows binaries: r-devel: LKT_1.0.zip, r-release: LKT_1.0.zip, r-oldrel: LKT_1.0.zip
macOS binaries: r-release (arm64): LKT_1.0.tgz, r-release (x86_64): LKT_1.0.tgz, r-oldrel: LKT_1.0.tgz

Linking:

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