This paper introduces REFLECTSUMM, a novel summarization dataset specifically designed for summarizing students' reflective writing. The goal of REFLECTSUMM is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, with potential implications in the opinion summarization…

As language technologies have become more sophisticated and prevalent, there have been increasing concerns about bias in natural language processing (NLP). Such work often focuses on the effects of bias instead of sources. In contrast, this paper discusses how normative language assumptions and ideologies influence a range of automated language…

The morphological structure of complex words impacts how they are processed during visual word recognition. This impact varies over the course of reading acquisition and for different languages and writing systems. Many theories of morphological processing rely on a decomposition mechanism, in which words are decomposed into explicit…

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…

Research in discourse processing has provided us with a strong foundation for understanding the characteristics of text and discourse, as well as their influence on our processing and representation of texts. However, recent advances in computational techniques have allowed researchers to examine discourse processes in new ways. The purpose of the…

An overarching motivation driving my research has been to further our theoretical understanding of how readers successfully comprehend challenging text. This article describes the theoretical origins of this research program and my quest to understand comprehension processes through the use of technology. Coh-Metrix was developed to measure, and…

This paper provides an alternative way of document representation by treating topic probabilities as a vector representation for words and representing a document as a combination of the word vectors. A comparison on summary data shows that this representation is more effective in document classification. [This paper was published in:…

Intelligent tutoring systems for ill-defined domains, such as reading and writing, are critically needed, yet uncommon. Two such systems, the Interactive Strategy Training for Active Reading and Thinking (iSTART) and Writing Pal (W-Pal) use natural language processing (NLP) to assess learners' written (i.e., typed) responses and provide immediate,…

Intelligent Tutoring Systems (ITSs) are situated in a potential struggle between effective pedagogy and system enjoyment and engagement. iSTART, a reading strategy tutoring system in which students practice generating self-explanations and using reading strategies, employs two devices to engage the user. The first is natural language processing…

In this chapter, we describe several intelligent tutoring systems (ITSs) designed to support student literacy through reading comprehension and writing instruction and practice. Although adaptive instruction can be a powerful tool in the literacy domain, developing these technologies poses significant challenges. For example, evaluating the…

AutoTutor is a natural language tutoring system that has produced learning gains across multiple domains (e.g., computer literacy, physics, critical thinking). In this paper, we review the development, key research findings, and systems that have evolved from AutoTutor. First, the rationale for developing AutoTutor is outlined and the advantages…