In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…

Having heard "a pimwit", English-speakers assume that "the pimwit" is also possible. This type of productivity is attributed to syntactic categories such as NOUN and DETERMINER, but the key question is "how" do humans become endowed with these categories in the first place. We propose a novel approach that combines…

This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…

This study is part of a series of in situ design-based research investigations within a large public university in California, assessing undergraduate science instruction while distance learning. It has become increasingly important to identify sustainable learning alternatives to support online teaching and learning while integrating educational…

Engaging in explanation while studying expository science texts can improve comprehension. The present study varied the timing of explanation activities and restudy opportunities before taking final comprehension tests on a set of 6 topics studied as part of a course in Introduction to Psychology. When students had the opportunity to restudy in…

School rating websites are increasingly used by parents to assess the quality and fit of U.S. K-12 schools for their children. These online reviews often contain detailed descriptions of a school's strengths and weaknesses, which both reflect and inform perceptions of a school. Existing work on these text reviews has focused on finding words or…

Adaptive educational software is likely to better support broader and more diverse sets of learners by considering more comprehensive views (or models) of such learners. For example, recent work proposed making inferences about "non-math" factors like reading comprehension while students used adaptive software for mathematics to better…

Developing models and using mathematics are two key practices in internationally recognized science education standards such as the Next Generation Science Standards (NGSS, 2013). In this paper, we used a virtual performance-based formative assessment to capture students' competencies at both "developing" and "evaluating"…

This full paper concerns an exploratory study that investigates students' reasoning about torsion. Mechanical reasoning is critical to engineering applications and yet students still struggle to accurately predict, analyze, and model mechanical systems using formal symbolic notations (i.e., formalizations). To understand the nature of students'…

In this article, the beta-binomial model for count data is proposed and demonstrated in terms of its application in the context of oral reading fluency (ORF) assessment, where the number of words read correctly (WRC) is of interest. Existing studies adopted the binomial model for count data in similar assessment scenarios. The beta-binomial model,…

This work proposes Dynamic Linear Epsilon-Greedy, a novel contextual multi-armed bandit algorithm that can adaptively assign personalized content to users while enabling unbiased statistical analysis. Traditional A/B testing and reinforcement learning approaches have trade-offs between empirical investigation and maximal impact on users. Our…

As evidence grows supporting the importance of non-cognitive factors in learning, computer-assisted learning platforms increasingly incorporate non-academic interventions to influence student learning and learning related-behaviors. Non-cognitive interventions often attempt to influence students' mindset, motivation, or metacognitive reflection to…

Large Language Models have recently achieved high performance on many writing tasks. In a recent study, math word problems in Carnegie Learning's MATHia adaptive learning software were rewritten by human authors to improve their clarity and specificity. The randomized experiment found that emerging readers who received the rewritten word problems…

Recent research seeks to develop more comprehensive learner models for adaptive learning software. For example, models of reading comprehension built using data from students' use of adaptive instructional software for mathematics have recently been developed. These models aim to deliver experiences that consider factors related to learning beyond…

Math performance continues to be an important focus for improvement. Many districts adopted educational technology programs to support student learning and teacher instruction. The ASSISTments program provides feedback to students as they solve homework problems and automatically prepares reports for teachers about student performance on daily…