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Underwood, Joshua – Research-publishing.net, 2017
The main objective of this study was to identify ways to incorporate voice-driven Artificial Intelligence (AI) effectively in classroom language learning. This nine month teacher-led design research study employed technology probes (Amazon's Alexa, Apple's Siri, Google voice search) and co-design methods with a class of primary age English as a…
Descriptors: English (Second Language), Elementary School Students, FLES, Second Language Learning
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
Gadanidis, George – International Journal of Information and Learning Technology, 2017
Purpose: The purpose of this paper is to examine the intersection of artificial intelligence (AI), computational thinking (CT), and mathematics education (ME) for young students (K-8). Specifically, it focuses on three key elements that are common to AI, CT and ME: agency, modeling of phenomena and abstracting concepts beyond specific instances.…
Descriptors: Artificial Intelligence, Computation, Mathematics Education, Elementary School Mathematics
Sano, Makoto; Baker, Doris Luft; Collazo, Marlen; Le, Nancy; Kamata, Akihito – Grantee Submission, 2020
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…
Descriptors: English Language Learners, Hispanic American Students, Elementary School Students, Grade 2
Akgün, Ergün; Demir, Metin – International Journal of Assessment Tools in Education, 2018
In this study, it was aimed to predict elementary education teacher candidates' achievements in "Science and Technology Education I and II" courses by using artificial neural networks. It was also aimed to show the independent variables importance in the prediction. In the data set used in this study, variables of gender, type of…
Descriptors: Elementary School Teachers, Preservice Teachers, Artificial Intelligence, Science Education
Hannah, L.; Kim, H.; Jang, E. E. – Language Assessment Quarterly, 2022
As a branch of artificial intelligence, automated speech recognition (ASR) technology is increasingly used to detect speech, process it to text, and derive the meaning of natural language for various learning and assessment purposes. ASR inaccuracy may pose serious threats to valid score interpretations and fair score use for all when it is…
Descriptors: Task Analysis, Artificial Intelligence, Speech Communication, Audio Equipment
Utecht, Jeff; Keller, Doreen – Critical Questions in Education, 2019
This paper will examine the eight principles of Connectivism Learning Theory and provide examples of how institutions of learning--K-12 and higher education--may think about applying them. Engaging in such work will allow institutions to take advantage of technological platforms as they exist today and into the future. While the Internet has…
Descriptors: Learning Theories, Elementary Schools, Secondary Schools, Critical Thinking
Akgün, Ergün; Demir, Metin – Online Submission, 2018
In this study, it was aimed to predict elementary education teacher candidates' achievements in "Science and Technology Education I and II" courses by using artificial neural networks. It was also aimed to show the independent variables importance in the prediction. In the data set used in this study, variables of gender, type of…
Descriptors: Elementary School Teachers, Preservice Teachers, Artificial Intelligence, Science Education
Giannakos, Michail, Ed. – Lecture Notes in Educational Technology, 2020
This book introduces the reader to evidence-based non-formal and informal science learning considerations (including technological and pedagogical innovations) that have emerged in and empowered the information and communications technology (ICT) era. The contributions come from diverse countries and contexts (such as hackerspaces, museums,…
Descriptors: Nonformal Education, Informal Education, Science Education, Computer Uses in Education
EdChoice, 2023
This poll was conducted between April 26-May 6, 2023 among a sample of 961 Teachers. The interviews were conducted online. Results based on the full survey have a measure of precision of plus or minus 3.46 percentage points. Among the key findings are: (1) Private school and charter school teachers say they are thriving to a much higher degree…
Descriptors: Teacher Attitudes, Kindergarten, Elementary Secondary Education, Well Being
Nipitpon Nanthawong – Higher Education Studies, 2024
This research aims to compare the social studies curricula of Thailand and New York State, USA, analyze their similarities and differences, and propose guidelines for improving the Thai social studies curriculum. The study employed a qualitative research methodology, using documentary analysis of the Thai Basic Education Core Curriculum B.E. 2551…
Descriptors: Comparative Education, Social Studies, Core Curriculum, Foreign Countries
Bahadir, Elif – Journal of Education and Training Studies, 2016
The purpose of this study is to examine a neural network based approach to predict achievement in graduate education for Elementary Mathematics prospective teachers. With the help of this study, it can be possible to make an effective prediction regarding the students' achievement in graduate education with Artificial Neural Networks (ANN). Two…
Descriptors: Preservice Teachers, Graduate Study, Academic Achievement, Elementary Education
Mat Roni, Saiyidi; Merga, Margaret Kristin – Australian Journal of Education, 2019
Children's attitudes towards, and frequency of recreational reading influence their reading skill level. The aim of this study was to determine the relative influence of research-supported intrinsic and extrinsic variables that can shape this attitude and practice, and to investigate the use of artificial neural network as an adjunct approach in…
Descriptors: Children, Elementary School Students, Grade 4, Grade 6
Xu, Junyan; He, Sining; Jiang, Haozhe; Yang, Yang; Cai, Su – International Association for Development of the Information Society, 2019
In recent years, the development of mobile technology and devices makes Artificial Intelligence (AI) and Augmented Reality (AR) available tools in classroom teaching and learning. AI and AR are used to improve the learning effect as well as motivate the students' learning enthusiasm. In English as a second language (ESL) learning, several previous…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Handwriting
Kelly, Sean; Olney, Andrew M.; Donnelly, Patrick; Nystrand, Martin; D'Mello, Sidney K. – Educational Researcher, 2018
Analyzing the quality of classroom talk is central to educational research and improvement efforts. In particular, the presence of authentic teacher questions, where answers are not predetermined by the teacher, helps constitute and serves as a marker of productive classroom discourse. Further, authentic questions can be cultivated to improve…
Descriptors: Middle School Students, Natural Language Processing, Artificial Intelligence, Teaching Methods