Knowledge tracing aims to model and predict students' knowledge states during learning activities. Traditional methods like Bayesian Knowledge Tracing (BKT) and logistic regression have limitations in granularity and performance, while deep knowledge tracing (DKT) models often suffer from lacking transparency. This paper proposes a…

Students process qualitatively and quantitatively different information during the dynamic self-regulated learning (SRL) process, and thus they may experience varying cognitive load in different SRL behaviors. However, there is limited research on the role of cognitive load in SRL. This study examined students' cognitive load in micro-level SRL…

Despite the prevalence of undergraduate drop-in mathematics tutoring, little is known about the behaviors of this specific group of tutors. This study serves as a starting place for identifying their behaviors by addressing the research question: what observable behaviors do undergraduate drop-in mathematics tutors exhibit as they interact with…

Research into "gaming the system" behavior in intelligent tutoring systems (ITS) has been around for almost two decades, and detection has been developed for many ITSs. Machine learning models can detect this behavior in both real-time and in historical data. However, intelligent tutoring system designs often change over time, in terms…

To better understand the self-regulated learning process in online learning environments, this research applied a data mining method, the two-layer hidden Markov model (TL-HMM), to explore the patterns of learning activities. We analyzed 25,818 entries of behavior log data from an intelligent tutoring system. Results indicated that students with…

Students' effort and emotions are important contributors to math learning. In a recent study evaluating the efficacy of MathSpring, a scalable web-based intelligent tutoring system that provides students with personalized math problems and affective support, system usage data were collected for 804 U.S. 10-12-year-olds. To understand the patterns…

Students are termed "multitaskers," and it is likely that they easily fall prey to other subjects or topics that most interest them. They occasionally took heed or gave close and thoughtful attention to the lectures they were on. In the current educational system, our young generations receive materials from their leftovers, and their…

Detecting wheel-spinning behaviors of students who interact with an Intelligent Tutoring System (ITS) is important for generating pertinent and effective feedback and developing more enriching learning experiences. This analysis compares decision tree and bagged tree models of student productive persistence (i.e., mastering a skill) using the…

Teaching elementary students how to read is undeniably crucial, yet a substantial number of children encounter difficulties despite early interventions (NCES, 2022). Cross-age tutoring, a pedagogical approach that pairs older students with younger peers, emerges as a cost-effective solution that brings academic and social benefits to both the…

This study examined how task complexity affected the temporal characteristics of self-regulated learning (SRL) behaviours in clinical reasoning. Eight-eight (N = 88) medical students participated in this study. They were required to diagnose two virtual patients of varying complexity in BioWorld, an intelligent tutoring system (ITS) designed to…

Effective teachers recognize the importance of transitioning students into learning activities for the day and accounting for the natural drift of student attention while creating lesson plans. In this work, we analyze temporal patterns of gaming behaviors during work on an intelligent tutoring system with a broader goal of detecting temporal…

Intelligent Personal Assistants (IPAs) are becoming more prevalent in daily and educational contexts, increasing the possibility of using them as learning partners that can provide more personalized and learner-centric learning opportunities. However, research has primarily focused on educational advantages that IPAs may provide, overlooking…

The automation of learning object recommendation and learning styles detection processes has attracted the interest of many researchers. Some works consider learning styles to recommend learning objects. On the other hand, other works automatically detect learning styles, analyzing the behavior of students in intelligent tutorial systems in…

Background: Medical students use a variety of self-regulated learning (SRL) strategies in different medical reasoning (MR) processes to solve patient cases of varying complexity. However, the interplay between SRL and MR processes is still unclear. Objectives: This study investigates how self-regulated learning (SRL) and medical reasoning (MR)…

In the study, it is aimed to investigate the academic procrastination behaviors of teacher candidates in the management of personal learning environments within intelligent tutoring systems. In the study, which was structured in the phenomenological pattern, included in the qualitative research method, the participants were formed from 52 teacher…