NotesFAQContact Us
Collection
Advanced
Search Tips
Showing 9,796 to 9,810 of 29,030 results Save | Export
Casas, Jimmy, Ed.; Whitaker, Todd, Ed.; Zoul, Jeffrey, Ed. – Eye on Education, 2020
The best educators never stop learning about their students or their craft. In this second volume of the Routledge Great Educators Series, ten of education's most inspiring thought-leaders come together to bring you their top suggestions for improving your students' learning in the classroom and your own professional learning as an educator.…
Descriptors: Teacher Leadership, Teacher Role, Teaching Methods, Teacher Collaboration
Taneri, Grace Ufuk – Center for Studies in Higher Education, 2020
We are living in an era of artificial intelligence (AI). There is wide discussion about and experimentation with the impact of AI on education/higher education. In this paper, we give a discussion of how AI is evolving, explore the ways AI is changing education/higher education, give a concise account of the skills universities need to teach their…
Descriptors: Artificial Intelligence, Higher Education, Electronic Learning, Blended Learning
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Bosch, Nigel; Crues, R. Wes; Shaik, Najmuddin; Paquette, Luc – Grantee Submission, 2020
Online courses often include discussion forums, which provide a rich source of data to better understand and improve students' learning experiences. However, forum messages frequently contain private information that prevents researchers from analyzing these data. We present a method for discovering and redacting private information including…
Descriptors: Privacy, Discussion Groups, Asynchronous Communication, Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Beaujean, A. Alexander – Journal of Psychoeducational Assessment, 2016
One of the ways to increase the reproducibility of research is for authors to provide a sufficient description of the data analytic procedures so that others can replicate the results. The publishers of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) do not follow these guidelines when reporting their confirmatory factor…
Descriptors: Children, Intelligence Tests, Factor Analysis, Replication (Evaluation)
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Kandeel, Refat A. A. – Journal of Education and Learning, 2016
The purpose of this study was to determine the multiple intelligences patterns of students at King Saud University and its relationship with academic achievement for the courses of Mathematics. The study sample consisted of 917 students were selected a stratified random manner, the descriptive analysis method and Pearson correlation were used, the…
Descriptors: Foreign Countries, Multiple Intelligences, College Students, Mathematics Achievement
Peer reviewed Peer reviewed
Direct linkDirect link
Graesser, Arthur C. – International Journal of Artificial Intelligence in Education, 2016
AutoTutor helps students learn by holding a conversation in natural language. AutoTutor is adaptive to the learners' actions, verbal contributions, and in some systems their emotions. Many of AutoTutor's conversation patterns simulate human tutoring, but other patterns implement ideal pedagogies that open the door to computer tutors eclipsing…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Communication Strategies, Dialogs (Language)
Peer reviewed Peer reviewed
Direct linkDirect link
Goodman, Bradley; Linton, Frank; Gaimari, Robert – International Journal of Artificial Intelligence in Education, 2016
Our 1998 paper "Encouraging Student Reflection and Articulation using a Learning Companion" (Goodman et al. 1998) was a stepping stone in the progression of learning companions for intelligent tutoring systems (ITS). A simulated learning companion, acting as a peer in an intelligent tutoring environment ensures the availability of a…
Descriptors: Simulation, Cooperative Learning, Educational Benefits, Artificial Intelligence
Pelletier, Kathe; Robert, Jenay; Muscanell, Nicole; McCormack, Mark; Reeves, Jamie; Arbino, Nichole; Grajek, Susan – EDUCAUSE, 2023
Artificial intelligence (AI) has taken the world by storm, with new AI-powered tools such as ChatGPT opening up new opportunities in higher education for content creation, communication, and learning, while also raising new concerns about the misuses and overreach of technology. Our shared humanity has also become a key focal point within higher…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Trends, Higher Education
Peer reviewed Peer reviewed
Direct linkDirect link
Mason, Claire M.; Chen, Haohui; Evans, David; Walker, Gavin – International Journal of Information and Learning Technology, 2023
Purpose: This paper aims to demonstrate how skills taxonomies can be used in combination with machine learning to integrate diverse online datasets and reveal skills gaps. The purpose of this study is then to show how the skills gaps revealed by the integrated datasets can be used to achieve better labour market alignment, keep educational…
Descriptors: Taxonomy, Artificial Intelligence, Data Collection, Data Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Ipek, Ziyaeddin Halid; Gözüm, Ali Ibrahim Can; Papadakis, Stamatios; Kallogiannakis, Michail – Educational Process: International Journal, 2023
Background/purpose: ChatGPT is an artificial intelligence program released in November 2022, but even now, many studies have expressed excitement or concern about its introduction into academia and education. While there are many questions to be asked, the current study reviews the literature in order to reveal the potential effects of ChatGPT on…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Educational Benefits
Peer reviewed Peer reviewed
Direct linkDirect link
Yuan, Chia-Ching; Li, Cheng-Hsuan; Peng, Chin-Cheng – Interactive Learning Environments, 2023
Fighter jets are a critical national asset. Because of the high cost of their manufacture and that of their related equipment, both pilots and maintenance personnel must complete intensive training before coming into contact with a jet. Due to gradual military downsizing, one-on-one training is often impracticable, and the level of familiarization…
Descriptors: Artificial Intelligence, Man Machine Systems, Technology Uses in Education, Educational Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Wang, Haiyan; Yu, Haopeng – Language Acquisition: A Journal of Developmental Linguistics, 2023
This paper attempts to investigate the repetition of Relative Clauses (RCs) in Mandarin children with Developmental Language Disorder (DLD) (aged 4; 5 to 6; 0) and their typically developing (TD) peers. The results of a sentence repetition task indicate that Mandarin children with DLD perform significantly worse than both groups of TD children,…
Descriptors: Language Impairments, Phrase Structure, Mandarin Chinese, Language Acquisition
Peer reviewed Peer reviewed
Direct linkDirect link
Fong, Cathy Yui-Chi – Infant and Child Development, 2023
The present study aimed to examine the role of phonological--semantic flexibility (PSF) in learning to read Chinese. PSF refers to a specific flexibility applied to process the dual linguistic dimensions of words (i.e., sound and meaning). A correlational study (Study 1) was conducted to determine the unique contribution of PSF to three aspects of…
Descriptors: Phonology, Semantics, Reading Processes, Chinese
Nores, Milagros; Harmeyer, Erin; Connors-Tadros, Lori; Li, Zijia – National Institute for Early Education Research, 2023
The National Institute for Early Education Research (NIEER) conducted a landscape evaluation of early childhood programs in Indiana (IN) between the spring of 2021 and the summer of 2022. The evaluation included assessments of infant, toddler, and preschooler children's developmental status in multiple domains at two time points to measure growth.…
Descriptors: Young Children, Child Development, Status, Early Childhood Education
EdChoice, 2023
This poll was conducted between August 18-August 27, 2023 among a national sample of 1,000 Teens. The interviews were conducted online and the data were weighted to approximate a target sample of Teens based on gender, age, race, and region. Results from the full survey have a measure of precision of plus or minus 3.3 percentage points. Among the…
Descriptors: Adolescents, Gender Differences, Age Differences, Racial Differences
Pages: 1  |  ...  |  650  |  651  |  652  |  653  |  654  |  655  |  656  |  657  |  658  |  ...  |  1936