Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments
Plot for Chi-square Statistics
Chi-square Statistics Table
Compute the chi-square scores of features
Data for PISA 2012, CP025, Q01 (selected countries)
Treated data for PISA 2012, CP025, Q01 (selected countries)
Data Partition
Decision Tree Result in Text View and Plot
LOGANTree: Tree-based models for the analysis of log files from comput...
Flag the features that have (near) zero variance
Partial Dependence Plot
Report table with the performance metrics for tree-based learning meth...
ROC Curves Plot
Tree-based Model Training
Data Partition and Tree-based Model Training
Barplot comparing the feature importance across different learning met...
Table comparing the feature importance for tree-based learning methods...
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> .