Developing an early-warning system for spotting at-risk students by using eBook interaction logs

Smart Learning Environments

Table 4 Average scores of the models in terms of Accuracy and Kappa

Algorithm	Raw Data		Transformed Data		Categorical Data
Algorithm	Accuracy	Kappa	Accuracy	Kappa	Accuracy	Kappa
Adaboost	0.790	0.580	0.783	0.567	0.748	0.494
bartMachine	0.811	0.620	0.813	0.625	0.792	0.583
gbm	0.795	0.589	0.793	0.586	0.782	0.565
glm	0.753	0.504	0.728	0.454	0.680	0.359
J48	0.813	0.625	0.833	0.665	0.766	0.530
JRip	0.795	0.587	0.782	0.564	0.755	0.509
knn	0.813	0.627	0.798	0.595	0.805	0.611
naive_bayes	0.823	0.646	0.801	0.601	0.811	0.621
nnet	0.710	0.420	0.780	0.558	0.754	0.505
rf	0.823	0.647	0.824	0.644	0.782	0.563
rpart	0.752	0.501	0.759	0.516	0.727	0.454
svmLinear	0.776	0.550	0.749	0.498	0.684	0.369
xgbLinear	0.798	0.596	0.780	0.560	0.726	0.452

Note: Bold values show the top three best-performed algorithms' results for each data form