Society's future depends on informed perspectives of Artificial Intelligence (AI) and AI related skills, a prognosis that greatly impacts K-12 education. To best prepare students to be AI savvy, there is a need to integrate AI tools, skills, and lessons into the K-12 curriculum. In order for teachers to develop the knowledge and skills, and have…

This study investigated the application of an artificial intelligence (AI) coach for second language (L2) learning in a primary school involving 327 participants. In line with Community of Inquiry, learners were expected to perceive social, cognitive, and teaching presences when interacting with the AI coach, which was considered a humanized…

Purpose: We aim to identify the most accurate model for predicting adolescent (Grade 9) reading difficulties (RD) in reading fluency and reading comprehension using 17 kindergarten-age variables. Three models (neural networks, linear, and mixture) were compared based on their accuracy in predicting RD. We also examined whether the same or a…

In a randomized trial that collects text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by human raters. An impact analysis can then be conducted to compare treatment and control groups, using the hand-coded scores as a measured outcome. This…

Young learners' vocabulary learning needs interaction with language input when they are engaged in an activity. Given that AI-supported image recognition technologies offer hands-on learning in authentic contexts, and that self-regulated learning (SRL) enables learners to monitor and evaluate their learning when interacting with multi-sensory…

This study examined the integration of artificial intelligence-powered speech recognition technology within early reading assessments in Morocco's Teaching at the Right Level (TaRL) program. The purpose was to evaluate the effectiveness of an automated speech recognition tool compared to traditional paper-based assessments in improving reading…

Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited. For example, in education, training novice educators with expert guidance is important for effectiveness but expensive, creating significant barriers to improving education…

Traditional museums of culture and history are failing to develop or make effective use of augmented reality (AR) technology. To address this deficit, the present study sought to develop online and offline experiential AR learning tools that would enable children to more fully explore museum artefacts. The study approach was based on the Blended…

Background/Context: Chronic absenteeism is a serious problem that has been linked to lower academic achievement, diminished socioemotional skills, and an increased likelihood of high school dropout (Allensworth et al., 2021; Gottfried, 2014). As a result, many schools have begun to embrace early warning systems (EWS) as a tool to identify and flag…

This article proposes two innovative approaches, the one-channel learning image recognition and the three-channel learning image recognition, to convert student's course involvements into images for early warning predictive analysis. Multiple experiments with 5235 students and 576 absolute/1728 relative input variables were conducted to verify…

This study explores the use of interactive Artificial Intelligence (AI)-interfaced robotic toys within early childhood (EC) settings to develop children's inquiry literacy. Arguments about the appropriate role of AI in EC education have received much attention when examining the potential of the integration of technology into children's play and…

Although Machine Learning (ML) is used already in our daily lives, few are familiar with the technology. This poses new challenges for students to understand ML, its potential, and limitations as well as to empower them to become creators of intelligent solutions. To effectively guide the learning of ML, this article proposes a scoring rubric for…

Machines have a long-demonstrated ability to find statistical relationships between qualities of texts and surface-level linguistic indicators of writing. More recently, unlocked by artificial intelligence, the potential of using machines to identify content-related writing trait criteria has been uncovered. This development is significant,…

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…

Purpose: Researchers have developed a constellation model of decodingrelated reading disabilities (RD) to improve the RD risk determination. The model's hallmark is its inclusion of various RD indicators to determine RD risk. Classification methods such as logistic regression (LR) might be one way to determine RD risk within the constellation…