Table 4.

Student characteristics modeled using interaction-based data.

Student characteristics modeled	Studies that used interaction-based data	Machine learning algorithms with effective performance	Accuracy of the models
Affective states		Recurrent neural network, logistic regression, random forest, and K*	Ranges from 70 to 85%
	Botelho et al., 2017; DeFalco et al., 2018; Salmeron-Majadas et al., 2018; Ghaleb et al., 2019; Hutt et al., 2019; Khan et al., 2019; Wang et al., 2019
Engagement	Edmond Meku Fotso et al., 2020; Erkan et al., 2020; Raj and Renumol, 2022	Recurrent neural network and random forest	Ranges from 80 to 95%
Learning style	Amir et al., 2017; Aissaoui et al., 2019; Lwande et al., 2019; Hmedna et al., 2020	Naïve bayes, support vector machine, and decision tree	Ranges from 83.6 to 98%
Motivation	Babić, 2017; Al-Shabandar et al., 2018	Decision tree and neural network	75.5 and 76.9%
Personality	Abyaa et al., 2018	Random forest	83.3%