David Stephens, a 4th grade teacher in Washington State, was preparing a lesson plan about desert wildlife (all names are pseudonyms). He was planning on assigning his students the chapter book, "Desert Giant: The World of the Saguaro Cactus." The students had divergent knowledge about the topic. For example, Maryam had grown up in…

Research has shown assistance can provide many benefits to novices lacking the mental models needed for problem solving in a new domain. However, varying approaches to assistance, such as subgoals and next-step hints, have been implemented with mixed results. Next-Step hints are common in data-driven tutors due to their straightforward generation…

An intelligent tutoring system (ITS, henceforth) is currently defined as a computer system that delivers personalized instruction to students by using computational techniques to evaluate the learner in a variety of ways, including (but not limited to) their prior knowledge, competency/skill levels, motivation, and affective states. ITSs are…

Jim Greer and his colleagues argued that student modelling is essential to provide adaptive instruction in tutoring systems and showed that effective modelling is possible, despite being enormously challenging. Student modelling plays a prominent role in many intelligent tutoring systems (ITSs) that address problem-solving domains. However,…

Developing models, using mathematics, and constructing explanations are three practices essential for science inquiry learning according to education reform efforts, such as the Next Generation Science Standards (NGSS Lead States, 2013). However, students struggle with these intersecting practices, especially when developing and interpreting…

The overarching goal of our project is to design effective learning activities for PyKinetic, a smartphone Python tutor. In this paper, we present a study using a variant of Parsons problems we designed for PyKinetic. Parsons problems contain randomized code which needs to be re-ordered to produce the desired effect. In our variant of Parsons…

Prior research shows that self-explanation promotes understanding by helping learners connect new knowledge with prior knowledge. However, despite ample evidence supporting the effectiveness of self-explanation, an instructional design challenge emerges in how best to scaffold self-explanation. In particular, it is an open challenge to design…

Previous research has shown that providing video recommendations to students in virtual learning environments implemented at scale positively affects student achievement. However, it is also critical to evaluate whether the treatment effects are heterogeneous, and whether they depend on contextual variables such as disadvantaged student status and…

Many studies have shown that visual representations can enhance student understanding of STEM concepts. However, prior research suggests that visual representations alone are not necessarily effective across a broad range of students. To address this problem, we created a novel, scaffolded form of diagrammatic self-explanation in which students…

Bayesian Knowledge Tracing (BKT) is a commonly used approach for student modeling, and Long Short Term Memory (LSTM) is a versatile model that can be applied to a wide range of tasks, such as language translation. In this work, we directly compared three models: BKT, its variant Intervention-BKT (IBKT), and LSTM, on two types of student modeling…

A common drawback in traditional language education is that all students in the same class use the same content. Since students may have different backgrounds such as prior knowledge and learning speed, one single curriculum may not be able to accommodate every student. Unfortunately, most students cannot afford personalized language learning,…

Agency refers to the level of control the student has over learning. Most studies on agency in computer-based learning environments have been conducted in the context of educational games and multimedia learning, while there is little research done in the context of learning with Intelligent Tutoring Systems (ITSs). We conducted a study in the…

In this paper, we propose a computational approach to model the Zone of Proximal Development (ZPD) using predicted probabilities of correctness and engaging students in reflective dialogue. To that end, we employ a predictive model that uses a linear function of a variety of parameters, including difficulty and student knowledge and we analyze the…

In this paper, we propose a computational approach to modeling the Zone of Proximal Development of students who learn using a natural language tutoring system for physics. We employ a student model that predicts students' performance based on their prior knowledge and their activity when using a dialogue tutor to practice with conceptual,…

Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem-solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one-to-one personalized and…