The aim of this study is to investigate the causes of reading problems experienced by third-grade students because of the instructional malpractices in education and develop a modeling with artificial neural networks. It was carried out according to the exploratory sequential model and consisted of two stages. In the qualitative part, a data pool…

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…

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…

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…

Purpose: Explore how different automated scoring (AS) models score reliably the expressive language and vocabulary knowledge in depth of young second grade Latino English learners. Design/methodology/approach: Analyze a total of 13,471 English utterances from 217 Latino English learners with random forest, end-to-end memory networks, long…