{ "_id": "6ac8a10ede46216d5edd4c29", "Package": "LKT", "Title": "Logistic Knowledge Tracing", "Version": "2.0.0", "Authors@R": "c(person(given = \"Philip I.\",\nfamily = \"Pavlik Jr.\",\nrole = c(\"aut\",\"ctb\",\"cre\"),\nemail = \"imrryr@gmail.com\",\ncomment = c(ORCID = \"0000-0001-6467-9452\")),\nperson(given = \"Luke G.\",\nfamily = \"Eglington\",\nrole = c(\"aut\",\"ctb\"),\nemail = \"luke.eglington.mail@gmail.com\",\ncomment = c(ORCID = \"0000-0002-8432-9203\"))\n)", "Description": "Computes Logistic Knowledge Tracing ('LKT') which is a\ngeneral method for tracking human learning in an educational\nsoftware system. Please see Pavlik, Eglington, and\nHarrell-Williams (2021) . 'LKT'\nis a method to compute features of student data that are used\nas predictors of subsequent performance. 'LKT' allows great\nflexibility in the choice of predictive components and features\ncomputed for these predictive components. 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