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…

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…

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…

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…

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…