This paper addresses the challenge of integrating a dialog system with an ITS created for supporting procedural training in a 3D virtual environment. To this end, we first describe the desired features of the dialog to be provided to students in such system. Then, we explain some technical issues of our proposal such as the architecture; the…

Advances in immersive virtual reality (I-VR) technology have allowed for the development of I-VR learning environments (I-VRLEs) with increasing fidelity. When coupled with a sufficiently advanced computer tutor agent, such environments can facilitate asynchronous and self-regulated approaches to learning procedural skills in industrial settings.…

Background: Effective communication in education employs diverse methods, with hologram technology representing teaching staff. Holograms, using different character realism levels, aim to sustain student interest and motivation. This study explores whether student valence, influenced by hologram tutor character appearance, significantly mediates…

Healthcare professionals often receive limited training in information gathering, especially for cases of suspected child maltreatment. This pilot study evaluated a brief interview training program using an artificial intelligence-driven child avatar chatbot to simulate realistic encounters with children. GPT-3 and one-shot prompting were used to…

Biochemistry and molecular biology students are asked to understand and analyze the structures of small molecules and complex three-dimensional (3D) macromolecules. However, most tools to help students learn molecular visualization skills are limited to two-dimensional (2D) images on screens and in textbooks. The virtual reality (VR) App Nanome,…

This research presents the results of development and validation of the Cyclical Self-Regulated Learning (SRL) Simulation Model, a model of student cognitive and metacognitive experiences learning mathematics within an intelligent tutoring system (ITS). Patterned after Zimmerman and Moylan's (2009) Cyclical SRL Model, the Simulation Model depicts…

A simulator-based Intelligent Tutoring System (ITS) is a computer system that is made to provide students with a learning experience that is both customizable to a student's needs (e.g., level of expertise, pace) and includes simulation, e.g., demonstrate certain domain concepts or allow problem-solving while replicating a real-life situation.…

Learning basic programming concepts in computer science-related fields poses a challenge for students, to the extent that it becomes an academic-social problem, resulting in high failure and dropout rates. Proposed solutions to the problem can be found in the literature, such as the development of new programming languages and environments, the…

Examining the sequential patterns of self-regulated learning (SRL) behaviors is gaining popularity to understand students' performance differences. However, few studies have looked at the transition probabilities among different SRL behaviors. Moreover, there is a lack of research investigating the temporal structures of students' SRL behaviors…

Identifying critical decisions is one of the most challenging decision-making problems in real-world applications. In this work, we propose a novel Reinforcement Learning (RL) based Long-Short Term Rewards (LSTR) framework for critical decisions identification. RL is a machine learning area concerning with inducing effective decision-making…

Developing models and using mathematics are two key practices in internationally recognized science education standards, such as the Next Generation Science Standards (NGSS). However, students often struggle with these two intersecting practices, particularly when developing mathematical models about scientific phenomena. Formative…

Knowledge tracing algorithms are embedded in Intelligent Tutoring Systems (ITS) to keep track of students' learning process. While knowledge tracing models have been extensively studied in offline settings, very little work has explored their use in online settings. This is primarily because conducting experiments to evaluate and select knowledge…

Many national science frameworks (e.g., Next Generation Science Standards) argue that developing mathematical modeling competencies is critical for students' deep understanding of science. However, science teachers may be unprepared to assess these competencies. We are addressing this need by developing virtual lab performance assessments that…

The U.S. Army is interested in extending the application of intelligent tutoring systems (ITS) beyond cognitive problem spaces and into psychomotor skill domains. In this paper, we present a methodology and validation procedure for creating expert model representations in the domain of rifle marksmanship. GIFT (Generalized Intelligent Framework…

How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…