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…

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…

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…

A growing body of research has shown the positive effects of peer tutoring on students' academic achievement, self-concept, attitude, social, and behavioral outcomes. There is, however, a paucity of research that focuses on peer-tutoring interventions for Hispanic students. The current study examined classroom practices, as well as program…

When encountering difficulties in conventional educational games, learners seldom self-regulate to discover and organize the learning content in the game environment. With the development of the human-computer interaction technology, computer agents are gradually being applied to educational games to provide personalized guidance or support to…

Background: Providing adaptive scaffolds to help learners develop effective self-regulated learning (SRL) behaviours has been an important goal for intelligent learning environments. Adaptive scaffolding is especially important in open-ended learning environments (OELE), where novice learners often face difficulties in completing their learning…

Reading to learn is a quintessentially self-regulated activity. In order to provide effective support for this activity it is necessary for us to understand how students adapt their self-regulation behaviors within disciplinary reading environments. In this paper, we utilize student response data from a digital literacy platform to examine the…

In recent years, we have seen the continuous and rapid increase of job openings in Science, Technology, Engineering and Math (STEM)-related fields. Unfortunately, these positions are not met with an equal number of workers ready to fill them. Efforts are being made to find durable solutions for this phenomena, and they start by encouraging young…

A student's ability to regulate their thoughts, emotions and behaviors in the face of temptation is linked to their task specific motivational goals and dispositions. Behavioral tasks are designed to strain a targeted resource to differentiate individuals through measures of their performance. In this paper, we explore how student behavior on…

The Intelligent Research and Training Platform (IRTP) of the National Center for Educational Technology (NECT) is an application designed to integrate AI technology and teacher education in response to the "Artificial Intelligence + Teacher Education" strategy, in order to provide teacher professional development and power the…

Challenges with numerical proficiency at an early age can lead to substantial gaps in learning and are associated with detrimental long-term outcomes. In addition, students with emotional-behavioral disorders (EBD) can have some of the most challenging behavioral and academic needs to address. The purpose of this study was to identify the effects…

Education researchers have recently called for the development of interventions to address the needs of students with or at risk of disabilities who exhibit co-occurring academic and behavioral needs. Teachers of these students frequently prioritize intervening on problem behavior rather than academics. However, addressing students' academic needs…

The current study introduces a model for measuring student diligence using online behaviors during intelligent tutoring system use. This model is validated using a full academic year dataset to test its predictive validity against long-term academic outcomes including end-of-year grades and total work completed by the end of the year. The model is…

This research aims to identify learning problems and the parents'roles in overcoming learning difficulties of 5th-grade students of Muhammadiyah Karangturi Elementary School, Bantul, Yogyakarta. Research participants were six students with learning difficulties, six parents, and four teachers. Selection of subjects used purposive sampling…

There is increasing evidence that fine-grained aspects of student performance and interaction within educational software are predictive of long-term learning. Machine learning models have been used to provide assessments of affect, behavior, and cognition based on analyses of system log data, estimating the probability of a student's particular…