This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering…

A key goal in cognitive training research is understanding whether cognitive training enhances general cognitive capacity or provides only task-specific improvements. Here, we developed a quantitative model for describing the temporal dynamics of these two processes. We analyzed data from 1300 children enrolled in an 8 week working memory training…

With Big Data revolution, the education sector is being reshaped. The current data-driven education system provides many opportunities to utilize the enormous amount of collected data about students' activities and performance for personalized education, adapting teaching methods, and decision making. On the other hand, such benefits come at a…

Increasing use of intelligent tutoring systems in education calls for analytic methods that can unravel students' learning behaviors. In this study, we explore a latent variable modeling approach for tracking learning flow during computer-interactive artificial tutoring. The study considers three models that give discrete profiles of a latent…

High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…

Forced-choice (FC) measures have been widely used in many personality or attitude tests as an alternative to rating scales, which employ comparative rather than absolute judgments. Several response biases, such as social desirability, response styles, and acquiescence bias, can be reduced effectively. Another type of data linked with comparative…

Learning interaction activities are the key part of tracking and evaluating learning behaviors, that plays an important role in data-driven autonomous learning and optimized learning in interactive learning environments. In this study, a big data set of learning behaviors with multiple learning periods is selected. According to the instance…

The use of Bayesian Knowledge Tracing (BKT) models in predicting student learning and mastery, especially in mathematics, is a well-established and proven approach in learning analytics. In this work, we report on our analysis examining the generalizability of BKT models across academic years attributed to "detector rot." We compare the…

Cognitive diagnosis models (CDMs) are the statistical framework for cognitive diagnostic assessment in education and psychology. They generally assume that subjects' latent attributes are dichotomous--mastery or nonmastery, which seems quite deterministic. As an alternative to dichotomous attribute mastery, attention is drawn to the use of a…

Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history of knowledge tracing model research and introduce pyBKT, an accessible and computationally efficient library…

Understanding the teacher's technology adoption process is essential to comprehend and narrow the digital divide in the post-epidemic age. During the pandemic, the stay-at-home orders not only intervened schooling and teaching but also increased digital accessibility to teachers. This research studies teacher heterogeneity and adoption controls in…

This study proposed a dynamic model of organizational technology adoption within a school institute culture. We described an implementation of a nonhomogeneous hidden Markov model based on a downscaling scheme that can project the cultural factors of the institute onto a teacher's implementation behavior. To reveal the dynamics of cultural…

There has been considerable interest in techniques for modelling student learning across practice problems to drive real-time adaptive learning, with particular focus on variants of the classic Bayesian Knowledge Tracing (BKT) model proposed by Corbett & Anderson, 1995. Over time researches have proposed many variants of BKT with…

Prompting students to generate constructed responses as they read provides a window into the processes and strategies that they use to make sense of complex text. In this study, Markov models examined the extent to which: (1) patterns of strategies; and (2) strategy combinations could be used to inform computational models of students' text…

Greater eyes-focused eye movement pattern during face recognition is associated with better performance in adults but not in children. We test the hypothesis that higher eye movement consistency across trials, instead of a greater eyes-focused pattern, predicts better performance in children since it reflects capacity in developing visual…