Recent research seeks to develop more comprehensive learner models for adaptive learning software. For example, models of reading comprehension built using data from students' use of adaptive instructional software for mathematics have recently been developed. These models aim to deliver experiences that consider factors related to learning beyond…

Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…

Integrating Augmented Reality (AR) technology into Intelligent Tutoring Systems (ITS) has the potential to enhance science education outcomes among middle school students. The purpose of this research was to determine the benefits of an ITS-AR system over traditional science teaching methods regarding science learning outcomes, motivation,…

Personalized recommendation plays an important role on content selection during the adaptive learning process. It is always a challenge on how to recommend effective items to improve learning performance. The aim of this study was to examine the feasibility of applying adaptive testing technology for personalized recommendation. We proposed the…

Understanding a student's problem-solving strategy can have a significant impact on effective math learning using Intelligent Tutoring Systems (ITSs) and Adaptive Instructional Systems (AISs). For instance, the ITS/AIS can better personalize itself to correct specific misconceptions that are indicated by incorrect strategies, specific problems can…

Adaptive educational software is likely to better support broader and more diverse sets of learners by considering more comprehensive views (or models) of such learners. For example, recent work proposed making inferences about "non-math" factors like reading comprehension while students used adaptive software for mathematics to better…

In numerous studies, intelligent tutoring systems (ITSs) have proven effective in helping students learn mathematics. Prior work posits that their effectiveness derives from efficiently providing eventually-correct practice opportunities. Yet, there is little empirical evidence on how learning processes with ITSs compare to other forms of…

Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…

Intelligent tutoring systems (ITS) can help students learn successfully, yet little work has explored the role of caregivers in shaping that success. Past interventions to support caregivers in supporting their child's homework have been largely disjunct from educational technology. The paper presents prototyping design research with nine middle…

To enhance the effectiveness of educational games, researchers have advocated adding learning supports in educational games, but this may come at the cost of disrupting the learning experience. Embedding virtual companions to provide learning supports may be an effective solution that naturally integrates learning supports into the game. However,…

This research used a comparative quasi-experimental design to investigate the impacts of an IRS in the ILE on students' academic performance, cognitive load, and satisfaction with the lesson. A total of 31 middle school students were divided into the experimental group and the control group. Mann-Whitney U tests yielded three major results. (1)…

Integrating visual representations in an interactive learning activity effectively scaffolds performance and learning. However, it is unclear whether and how "sustaining" or "interleaving" visual scaffolding helps learners solve problems efficiently and learn from problem solving. We conducted a classroom study with 63…

Intelligent learning technologies are often applied within the educational industries. While these technologies can be used to create learning experiences tailored to an individual student, they cannot address students' affect accurately and quickly during the learning process. This paper focuses on two core research questions. How do students…

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…

Learners' choices as to whether and how to use visual representations during learning are an important yet understudied aspect of self-regulated learning. To gain insight, we developed a "choice-based" intelligent tutor in which students can choose whether and when to use diagrams to aid their problem solving in algebra. In an…