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Jure Žabkar; Tajda Urankar; Karmen Javornik; Milena Košak Babuder – Center for Educational Policy Studies Journal, 2023
Measurement of readability is an important tool for assessing reading disorders such as dyslexia. Among the screening procedures for dyslexia is the reading fluency test, which is defined as the ability to read with speed, accuracy and proper expression. The reading fluency test often consists of a sequence of unrelated written texts ranging from…
Descriptors: Foreign Countries, Dyslexia, Elementary School Students, Grade 3
DiCarlo, Cynthia F.; Deris, Aaron R.; Deris, Thomas P. – Journal of Behavioral Education, 2023
The purpose of this study was to investigate the impact of mLearning or mobile device practice on the attention and accuracy of student's use of math concepts, specifically, telling time. A single subject, alternating treatment design was used to compare mLearning to paper and pencil practice in four 3rd grade male students. Results were mixed;…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Handheld Devices, Attention
Patel, Nirmal; Nagpal, Pooja; Shah, Tirth; Sharma, Aditya; Malvi, Shrey; Lomas, Derek – Journal of Computer Assisted Learning, 2023
Background: Readability metrics provide us with an objective and efficient way to assess the quality of educational texts. We can use the readability measures for finding assessment items that are difficult to read for a given grade level. Hard-to-read math word problems can put some students at a disadvantage if they are behind in their literacy…
Descriptors: Mathematics Tests, Readability, Word Problems (Mathematics), Mathematics Achievement
Muhammet Remzi Karaman; I?dris Göksu – International Journal of Technology in Education, 2024
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…
Descriptors: Artificial Intelligence, Natural Language Processing, Lesson Plans, Instructional Effectiveness
Tiffany Wu; Christina Weiland – Annenberg Institute for School Reform at Brown University, 2024
Chronic absenteeism is a critical issue that has been linked to many adverse student outcomes. The current study focuses on improving a key system already in place in many school districts--early warning systems (EWSs)--in order to decrease chronic absenteeism in students' earliest schooling years. Using a demographically diverse population of…
Descriptors: Elementary School Students, Kindergarten, Grade 1, Grade 2
Çelik, Cemal; Kartal, Hülya – International Online Journal of Primary Education, 2023
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…
Descriptors: Reading Difficulties, Models, Elementary School Students, Artificial Intelligence
Hyejeong Lee – ProQuest LLC, 2024
This dissertation explores the strategies of personalized learning through AI and its effectiveness, with a focus on third-grade mathematics education. The primary objective is to investigate how AI tools can tailor learning experiences to individual needs, particularly for students who struggle academically, and thereby help reduce educational…
Descriptors: Artificial Intelligence, Individualized Instruction, Instructional Effectiveness, Grade 3
Yijia Yuan – Interactive Learning Environments, 2024
This experimental research examined the effectiveness of using chatbots in English as a Foreign Language (EFL) classrooms at a Chinese elementary school. Seventy-four students were divided into two groups: one employing traditional methods, and the other using chatbots. Before and after the 3-month teaching period, pre- and post-tests were used to…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, English (Second Language)
Ting-Chia Hsu; Ching Chang; Tien-Hsiu Jen – Interactive Learning Environments, 2024
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…
Descriptors: Metacognition, Multisensory Learning, Vocabulary Development, Learning Strategies
Younes-Aziz Bachiri; Hicham Mouncif; Belaid Bouikhalene; Radoine Hamzaoui – Turkish Online Journal of Distance Education, 2024
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…
Descriptors: Foreign Countries, Artificial Intelligence, Speech Communication, Identification
Rose E. Wang; Ana T. Ribeiro; Carly D. Robinson; Susanna Loeb; Dorottya Demszky – Annenberg Institute for School Reform at Brown University, 2024
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…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Tutors, Elementary School Students
Lee, JiHye; Lee, Hyun-Kyung; Jeong, Dabin; Lee, JiEun; Kim, TaeRyun; Lee, JiHyon – International Journal of Art & Design Education, 2021
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…
Descriptors: Museums, Cultural Education, Computer Simulation, History Instruction
Tiffany Wu; Christina Weiland – Society for Research on Educational Effectiveness, 2024
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…
Descriptors: Attendance, Early Childhood Education, Intervention, Artificial Intelligence
L. Hannah; E. E. Jang; M. Shah; V. Gupta – Language Assessment Quarterly, 2023
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,…
Descriptors: Validity, Automation, Scoring, Writing Assignments
Erbeli, Florina; He, Kai; Cheek, Connor; Rice, Marianne; Qian, Xiaoning – Scientific Studies of Reading, 2023
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…
Descriptors: At Risk Students, Reading Difficulties, Classification, Comparative Analysis
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