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…

Advances in machine learning (ML) are poised to contribute to our understanding of the linguistic processes associated with successful reading comprehension, which is a critical aspect of children's educational success. We used ML techniques to investigate and compare associations between children's reading comprehension and 260 linguistic…

This study focuses on how teachers' pedagogical content knowledge (PCK) of mathematics may differ depending on teacher interactions in an online teacher community of practice (CoP). The study utilizes data from 26,857 posts collected from the South Korean self-generated online teacher CoP, 'Indischool'. This data was then analyzed using natural…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

Recent studies have accumulated to suggest that children, akin to adults, exhibit a processing advantage for formulaic language (e.g. "save energy") over novel language (e.g. "sell energy"), as well as sensitivity to phrase frequencies. The majority of these studies are based on formulaic sequences in their canonical form. In…

Children's oral language proficiency (OLP) is integral for developing literacy skills. Storytelling or retelling is often used by parents and educators to elicit children's OLP, yet it is less commonly used for assessment purposes. Leveraged by natural language processing and machine learning, this study examined the extent to which computational…

The ability to automatically assess the quality of paraphrases can be very useful for facilitating literacy skills and providing timely feedback to learners. Our aim is twofold: a) to automatically evaluate the quality of paraphrases across four dimensions: lexical similarity, syntactic similarity, semantic similarity and paraphrase quality, and…

Individuals with lower proficiency in a second language tend to produce more disfluent speech patterns in the second language. Speech disfluencies refer to interruptions in the forward flow of speech and are distinct from the colloquial use of "fluency," to characterize knowledge of a language. Prior research indicates that some speech…

While recent studies find that contextual diversity (CD) is a better determinant of visual word recognition than token frequency, there is a dearth of work comparing contextual diversity and token frequency in developing readers. In two sets of character and lexical decision experiments we examined token frequency and contextual diversity effects…

Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies, and similarities in how they construe and communicate meaning. This study examines the extent to which discourse…

A number of studies have demonstrated strong links between students' language features (as found in spoken and written production) and their math performance. However, no studies have examined links between the students' language features and measures of their Math Identity. This project extends prior studies that use natural language processing…

This study examined the theoretical controversy on the impact of syllables and bigrams in handwriting production. French children and adults wrote words on a digitizer so that we could collect data on the local, online processing of handwriting production. The words differed in the position of the lowest frequency bigram. In one condition, it…

Automated scoring by means of Latent Semantic Analysis (LSA) has been introduced lately to improve the traditional human scoring system. The purposes of the present study were to develop a LSA-based assessment system to evaluate children's Chinese sentence construction skills and to examine the effectiveness of LSA-based automated scoring function…

Background: The computational grammatical complexity (CGC) hypothesis claims that children with G(rammatical)-specific language impairment (SLI) have a domain-specific deficit in the computational system affecting syntactic dependencies involving 'movement'. One type of such syntactic dependencies is filler-gap dependencies. In contrast, the…