LOGANTree: Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments

Enables researchers to model log-file data from computer-based assessments using machine-learning techniques. It allows researchers to generate new knowledge by comparing the performance of three tree-based classification models (i.e., decision trees, random forest, and gradient boosting) to predict student's outcome. It also contains a set of handful functions for the analysis of the features' influence on the modeling. Data from the Climate control item from the 2012 Programme for International Student Assessment (PISA, <https://www.oecd.org/pisa/>) is available for an illustration of the package's capability. He, Q., & von Davier, M. (2015) <doi:10.1007/978-3-319-19977-1_13> Boehmke, B., & Greenwell, B. M. (2019) <doi:10.1201/9780367816377> .

Getting started

Package details

AuthorDenise Reis Costa [aut, ths], Qi Qin [aut, cre]
MaintainerQi Qin <logantreeqq@gmail.com>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the LOGANTree package in your browser

Any scripts or data that you put into this service are public.

LOGANTree documentation built on June 23, 2022, 1:06 a.m.