Research on Computer-Supported Collaborative Learning (CSCL) has provided significant insights into why collaborative learning is effective and how we can effectively provide support for it. Building on this knowledge, we can investigate when collaboration is beneficial to support learning. Specifically, collaborative and individual learning are…

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…

In working towards unraveling the mechanisms of productive collaborative learning, dual eye tracking is a potentially helpful methodology. Dual eye tracking is a method where eye-tracking data from people working on a task are analyzed jointly, for example to extract measures of joint visual attention. We explore how eye gaze relates to effective…

Prior research shows that multiple representations can enhance learning, provided that students make connections among them. We hypothesized that support for connection making is most effective in enhancing learning of domain knowledge if it helps students both in making sense of these connections and in becoming perceptually fluent in making…

Prior research shows that multiple representations can enhance learning, provided that students make connections among them. We hypothesized that support for connection making is most effective in enhancing learning of domain knowledge if it helps students both in making sense of these connections and in becoming perceptually fluent in making…

Social interdependence is a key concept in CSCL research. However, investigations of students' positive and negative interdependence during collaborative activities have often relied on self-report, rather than dialogue analysis. Bringing together politeness and social interdependence theory, we assessed "dialogue indicators" of positive…

How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…

To be able to provide better support for collaborative learning in Intelligent Tutoring Systems, it is important to understand how collaboration patterns change. Prior work has looked at the interdependencies between utterances and the change of dialogue over time, but it has not addressed how dialogue changes during a lesson, an analysis that…

Prior research shows that representational competencies that enable students to use graphical representations to reason and solve tasks is key to learning in many science, technology, engineering, and mathematics domains. We focus on two types of representational competencies: (1) "sense making" of connections by verbally explaining how…

Prior research shows that representational competencies that enable students to use graphical representations to reason and solve tasks is key to learning in many science, technology, engineering, and mathematics (STEM) domains. We focus on two types of representational competencies: (1) "sense making" of connections by verbally…

Collaborative and individual learning are both frequently used in classrooms to support learning. However, little research has investigated the benefits of combining individual and collaborative learning, as compared to learning only individually or only collaboratively. With our study, we address this research gap. We compared a combined…

Intelligent Tutoring Systems (ITSs) are beneficial for individual students learning in several domains, including mathematics where they have been used to support both secondary and elementary students. Collaborative learning may be beneficial to include in ITSs, particularly for conceptual knowledge. There is little work on collaborative ITSs,…

Research shows that multiple representations can enhance student learning. Many curricula use multiple representations across multiple task types. The temporal sequence of representations and task types is likely to impact student learning. Research on contextual interference shows that interleaving learning tasks leads to better learning results…

How should a wide variety of educational activities be sequenced to maximize student learning? Although some experimental studies have addressed this question, educational data mining methods may be able to evaluate a wider range of possibilities and better handle many simultaneous sequencing constraints. We introduce Sequencing Constraint…

While collaborative Intelligent Tutoring Systems (ITSs) have been designed for older students and have been shown to support sense-making behaviors, there has not been as much work on creating systems to support collaboration between elementary school students. We have developed and tested, with 84 students, individual and collaborative versions…