The learning sciences inherently involve interdisciplinary research with an overarching objective of advancing theories of learning and to inform the design and implementation of effective instructional methods and learning technologies. In these endeavors, learning sciences encompass diverse constructs, measures, processes, and outcomes…

Summarization is an effective strategy to promote and enhance learning and deep comprehension of texts. However, summarization is seldom implemented by teachers in classrooms because the manual evaluation of students' summaries requires time and effort. This problem has led to the development of automated models of summarization quality. However,…

Theories of discourse argue that comprehension depends on the coherence of the learner's mental representation. Our aim is to create a reliable automated representation to estimate readers' level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network…

Large language models have recently been able to perform well in a wide variety of circumstances. In this work, we explore the possibility of large language models, specifically GPT-3, to write explanations for middle-school mathematics problems, with the goal of eventually using this process to rapidly generate explanations for the mathematics…

Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…

In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digital learning platforms may need to examine and provide feedback across many images of students' math work. To assess the potential of VLMs to support…

Extensive literature in artificial intelligence in education focuses on developing automated methods for detecting cases in which students struggle to master content while working with educational software. Such cases have often been called "wheel-spinning," "unproductive persistence," or "unproductive struggle." We…

Help-seeking is a valuable practice in online discussion forums. However, the asynchronicity and information overload of online discussion forums have made it challenging for help seekers and providers to connect effectively. This study formulated a new method to provide fair and accurate insights toward building a peer recommender to support…

In this entry, we define Intelligent Tutoring Systems (ITSs) and present a description of their core components. We outline a history of the development of ITSs with a focus on key issues that have driven change and innovation in ITSs from their inception to present day. We also present a brief case study on a specific ITS, Inq-ITS (Inquiry…

Early interaction is a dynamic, emotional process in which infants influence and are influ­enced by caregivers and peers. This chapter reviews new developments in behavior imag­ing--objective quantification of human action--and computational approaches to the study of early emotional interaction and development. Advances in the automated…

Open-ended "constructed responses" promote deeper processing of course materials. Further, evaluation of these explanations can yield important information about students' cognition. This study examined how students' constructed responses, generated at different points during learning, relate to their later comprehension outcomes.…

In contrast to simple feedback, which provides students with the correct answer, elaborated feedback provides an explanation of the correct answer with respect to the student's error. Elaborated feedback is thus a challenge for AI in education systems because it requires dynamic explanations, which traditionally require logical reasoning and…

Summarization enhances comprehension and is considered an effective strategy to promote and enhance learning and deep understanding of texts. However, summarization is seldom implemented by teachers in classrooms because the manual evaluation requires a lot of effort and time. Although the need for automated support is stringent, there are only a…

This article describes designs that use multiple conversational agents within the framework of intelligent tutoring systems. Agents in this case are computerized talking heads or embodied animated avatars that help students learn by performing actions and holding conversations with them in natural language. The earliest conversational intelligent…

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…