Background: Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has…

The ability of children to ask curiosity-driven questions is an important skill that helps improve their learning. For this reason, previous research has explored designing specific exercises to train this skill. Several of these studies relied on providing semantic and linguistic cues to train them to ask more of such questions (also called…

Self-directed learning and self-assessment require student responsibility over learning needs, goals, processes, and outcomes. However, this student-led learning can be challenging to achieve in a classroom limited by a one-to-many teacher-led instruction. We, thus, have designed and prototyped a generative artificial intelligence chatbot…

This paper presents a multidimensional model of variation in writing quality, register, and genre in student essays, trained and tested via confirmatory factor analysis of 1.37 million essay submissions to ETS' digital writing service, Criterion®. The model was also validated with several other corpora, which indicated that it provides a…

In this research, we aimed to determine whether students' math achievements improved using ChatGPT, one of the chatbot tools, to prepare lesson plans in primary school math courses. The research was conducted with a pretest-posttest control group experimental design. The study comprises 39 third-grade students (experimental group = 24, control…

Written answers to open-ended questions can have a higher long-term effect on learning than multiple-choice questions. However, it is critical that teachers immediately review the answers, and ask to redo those that are incoherent. This can be a difficult task and can be time-consuming for teachers. A possible solution is to automate the detection…

This research examines the influence of integrating generative artificial intelligence (GAI) in education, focusing on its acceptance and utilization among elementary education students. Grounded in the Task-Technology Fit (TTF) Theory and an expanded iteration of the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the study…

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…

The potential of artificial intelligence (AI) in transforming education has received considerable attention. This study aims to explore the potential of large language models (LLMs) in assisting students with studying and passing standardized exams, while many people think it is a hype situation. Using primary education as an example, this…

This work explores the integration of artificial intelligence (AI) custom chatbots in educational settings, with a particular focus on their applicability in the context of mathematics and physics. In view of the increasing deployment of AI tools such as ChatGPT in educational contexts, the present study explores their potential in generating…

Background: Formative assessments are needed to enable monitoring how student knowledge develops throughout a unit. Constructed response items which require learners to formulate their own free-text responses are well suited for testing their active knowledge. However, assessing such constructed responses in an automated fashion is a complex task…

Recent developments in technology have accelerated the influence of artificial intelligence (AI) on our lives. The National Literacy Trust is interested in exploring how such platforms might influence, and potentially redefine, what it means to be literate in the digital age. Based on data from more than 50,000 children and young people taking…

We used multivariate generalizability theory to examine the reliability of hand-scoring and automated essay scoring (AES) and to identify how these scoring methods could be used in conjunction to optimize writing assessment. Students (n = 113) included subsamples of struggling writers and non-struggling writers in Grades 3-5 drawn from a larger…

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…

This study builds on prior research by leveraging natural language processing (NLP), click-stream analyses, and survey data to predict students' mathematics success and math identity (namely, self-concept, interest, and value of mathematics). Specifically, we combine NLP tools designed to measure lexical sophistication, text cohesion, and…