Advances in computational language models increasingly enable adaptive support for self-regulated learning (SRL) in digital learning environments (DLEs; eg, via automated feedback). However, the accuracy of those models is a common concern for educational stakeholders (eg, policymakers, researchers, teachers and learners themselves). We compared…

While mathematics achievement continues to decline across the United States, minimal research has been conducted on the use of CT skills to increase proficiency. This explanatory, nonexperimental quantitative study focused on the self-assessment of teachers' content knowledge in computational thinking skills and the relationship to students'…

Phraseology has been flourishing in the field of English writing studies in recent years. However, the focus has primarily been on items with less variability, such as ngrams or lexical bundles. To address this gap, this study investigates concgrams (Cheng et al., 2006), which encompass both constituency and positional variations, in advanced…

This study uses a quasi-experimental design to explore the role of natural language processing (NLP) and speech recognition technologies in supporting teacher interventions during collaborative STEM activities. The Speech Recognition Keywords Analysis System (SRKAS) was developed to extract keywords from student discussions, enabling real-time…

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…

Learning vocabulary is a central but yet complex aspect of learning a language. Hence, researchers stress the importance of facilitating vocabulary development via a structured approach to target words and recycling. While teaching materials have the potential to provide this structure to all students in a classroom, few studies have investigated…

As the development and application of large language models (LLMs) in physics education progress, the well-known AI-based chatbot ChatGPT4 has presented numerous opportunities for educational assessment. Investigating the potential of AI tools in practical educational assessment carries profound significance. This study explored the comparative…

Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…

This paper introduces AMMORE, a new dataset of 53,000 math open-response question-answer pairs from Rori, a mathematics learning platform used by middle and high school students in several African countries. Using this dataset, we conducted two experiments to evaluate the use of large language models (LLM) for grading particularly challenging…

Broadly defined, academic language (AL) is a set of lexical-grammatical norms and registers commonly used in educational and academic discourse. Mastery of academic language in writing is an important aspect of writing instruction and assessment. The purpose of this study was to use Natural Language Processing (NLP) tools to examine the extent to…

With recent improvements in machine translation (MT) accuracy, MT has gained unprecedented popularity in second language (L2) learning. Despite the significant number of studies on MT use, the effects of using MT on students' retention of learning or secondary school students' use of MT in L2 writing has rarely been researched. The current study…

This study explored the lexical coverage of corpus-based vocabulary lists (general, academic, and content-specific) across several million tokens gathered from digital science resources (DSR) for middle school (6-8 grade) students in the United States. The goal was to estimate the extent to which a combination of well-known word lists, mostly…

This study explores the use of Large Language Models (LLMs), specifically GPT-4, in analysing classroom dialogue--a key task for teaching diagnosis and quality improvement. Traditional qualitative methods are both knowledge- and labour-intensive. This research investigates the potential of LLMs to streamline and enhance this process. Using…

The present study attempted to examine the effect of using the connectivist approach on developing secondary-stage students' cross-cultural awareness and translation performance. The study comprised thirty-two first-year secondary stage students enrolled in El-Jalawea Institute, Sohag Governorate. The study adopted the quasi-experimental design.…

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…