In the context of the critical need to support children's early language development, teacher knowledge may enhance children's opportunities to build linguistic skills. In this study we explored how early childhood teachers' (n = 86) pedagogical content knowledge for language and vocabulary, and their book-reading implementation across the school…

Home-school partnerships between teachers and caregivers of students with or at risk of emotional/behavioral disorders (EBD) are critical to support positive student outcomes. Yet, effective home-school partnerships may be particularly challenging to foster for students with or at risk of EBD, and little is known about how teachers and caregivers…

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.…

Adaptive learning technology solutions often use a learner model to trace learning and make pedagogical decisions. The present research introduces a formalized methodology for specifying learner models, logistic knowledge tracing (LKT), that consolidates many extant learner modeling methods. The strength of LKT is the specification of a symbolic…

Statistical analysis of categorical data often relies on multiway contingency tables; yet, as the number of categories and/or variables increases, the number of table cells with few (or zero) observations also increases. Unfortunately, sparse contingency tables invalidate the use of standard good-ness-of-fit statistics. Limited-information fit…

When text datasets are very large, manually coding line by line becomes impractical. As a result, researchers sometimes try to use machine learning algorithms to automatically code text data. One of the most popular algorithms is topic modeling. For a given text dataset, a topic model provides probability distributions of words for a set of…

This paper explores the concept of dynamically generating definitions using a deep-learning model. We do this by creating a dataset that contains definition entries and contexts associated with each definition. We then fine-tune a GPT-2 based model on the dataset to allow the model to generate contextual definitions. We evaluate our model with…

This paper presents WikiMorph, a tool that automatically breaks down words into morphemes, etymological compounds (morphemes from root languages), and generates contextual definitions for each component. It comes in two flavors: a dataset and a deep-learning-based model. The dataset was extracted from Wiktionary and contains over 450k entries. We…

This paper explores a general approach to paraphrase generation using a pre-trained seq2seq model fine-tuned using a back-translated anatomy and physiology textbook. Human ratings indicate that the paraphrase model generally preserved meaning and grammaticality/fluency: 70% of meaning ratings were above 75, and 40% of paraphrases were considered…

Automated Essay Scoring (AES) can reliably grade essays at scale and reduce human effort in both classroom and commercial settings. There are currently three dominant supervised learning paradigms for building AES models: feature-based, neural, and hybrid. While feature-based models are more explainable, neural network models often outperform…

Cloze items are commonly used for both assessing learning and as a learning activity. This paper investigates the selection of sentences for cloze item creation by comparing methods ranging from simple heuristics to deep learning summarization models. An evaluation using human-generated cloze items from three different science texts indicates that…

The relation of various math attitudes to math achievement has been extensively studied in adolescents and adults. Recently, researchers have begun to examine the math attitude-math achievement relation in young children. We review theories and research on four attitudes relevant to early math learning--math anxiety, math self-concept, mindset,…

We describe a data mining pipeline to convert data from educational systems into knowledge component (KC) models. In contrast to other approaches, our approach employs and compares multiple model search methodologies (e.g., sparse factor analysis, covariance clustering) within a single pipeline. In this preliminary work, we describe our approach's…

Early childhood interventions can improve self-regulation, but there are few economic evaluations of such interventions. This study analyzed the cost-effectiveness of an early childhood self-regulation intervention ("Red Light Purple Light!"; RLPL), comparing three different models of implementation across stages of intervention…

Research with school-age readers suggests that the contributions of reading and language skills vary across reading comprehension assessments and proficiency levels. With a sample of 168 struggling adult readers, we estimated the explanatory effects of decoding, oral vocabulary, listening comprehension, fluency, background knowledge, and…