Package: LKT Title: Logistic Knowledge Tracing Version: 2.0.0 Authors@R: c(person(given = "Philip I.", family = "Pavlik Jr.", role = c("aut","ctb","cre"), email = "imrryr@gmail.com", comment = c(ORCID = "0000-0001-6467-9452")), person(given = "Luke G.", family = "Eglington", role = c("aut","ctb"), email = "luke.eglington.mail@gmail.com", comment = c(ORCID = "0000-0002-8432-9203")) ) Description: Computes Logistic Knowledge Tracing ('LKT') which is a general method for tracking human learning in an educational software system. Please see Pavlik, Eglington, and Harrell-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. License: GPL-3 Encoding: UTF-8 LazyData: true VignetteBuilder: knitr Roxygen: list(markdown = TRUE) RoxygenNote: 7.3.3 Collate: 'LKT-package.R' 'data.R' 'lkt-feature-input.R' 'lkt-feature-computation.R' 'lkt-model-interface.R' 'lkt-model-liblinear.R' 'lkt-model-online-calibration.R' 'lkt-fast-online-simple-adaptive.R' 'lkt-latency.R' 'lkt-prediction.R' 'LKTfunctions.R' 'lkt-hdi.R' 'lkt-search.R' Depends: R (>= 3.5.0), SparseM (>= 1.83), methods, Matrix, data.table (>= 1.13.2), LiblineaR (>= 2.10-8) Imports: glmnet (>= 4.0-2), lme4 (>= 1.1-23), cluster (>= 2.1.3), pROC (>= 1.16.2), crayon, HDInterval (>= 0.2.2) Suggests: rmarkdown, knitr, utils, ggplot2 Config/pak/sysreqs: cmake make Repository: https://optimal-learning-lab.r-universe.dev Date/Publication: 2026-07-11 01:51:36 UTC RemoteUrl: https://github.com/optimal-learning-lab/lkt RemoteRef: HEAD RemoteSha: e6810522c23f030845b0cd41a39b23c8fe4403d2 NeedsCompilation: yes Packaged: 2026-10-09 08:00:28 UTC; root Author: Philip I. Pavlik Jr. [aut, ctb, cre] (ORCID: ), Luke G. Eglington [aut, ctb] (ORCID: ) Maintainer: Philip I. Pavlik Jr.