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) <>. '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: 1.7.0
Depends: R (≥ 3.5.0), SparseM (≥ 1.83), methods, Matrix, data.table (≥ 1.13.2), LiblineaR (≥ 2.10-8)
Imports: glmnet (≥ 4.0-2), glmnetUtils (≥ 1.1.8), lme4 (≥ 1.1-23), cluster (≥ 2.1.3), pROC (≥ 1.16.2), crayon, HDInterval (≥ 0.2.2)
Suggests: rmarkdown, knitr, utils, caret, ggplot2
Published: 2024-07-01
DOI: 10.32614/CRAN.package.LKT
Author: Philip I. Pavlik Jr. ORCID iD [aut, ctb, cre], Luke G. Eglington ORCID iD [aut, ctb]
Maintainer: Philip I. Pavlik Jr. <imrryr at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: LKT results


Reference manual: LKT.pdf
Vignettes: Basic_Operations


Package source: LKT_1.7.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): LKT_1.7.0.tgz, r-oldrel (arm64): LKT_1.7.0.tgz, r-release (x86_64): LKT_1.7.0.tgz, r-oldrel (x86_64): LKT_1.7.0.tgz
Old sources: LKT archive


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