NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing all 14 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Kevser Hava; Özgür Babayigit – Education and Information Technologies, 2025
In recent years, there has been a growing emphasis on integrating Artificial Intelligence (AI) applications in educational settings. As a result, it is essential to assess teachers' competencies in Technological, Pedagogical, and Content Knowledge (TPACK) as it pertains to AI and examine the factors that influence these competencies. This study…
Descriptors: Technological Literacy, Pedagogical Content Knowledge, Artificial Intelligence, Technology Integration
Peer reviewed Peer reviewed
Direct linkDirect link
Mizumoto, Atsushi – Language Learning, 2023
Researchers often make claims regarding the importance of predictor variables in multiple regression analysis by comparing standardized regression coefficients (standardized beta coefficients). This practice has been criticized as a misuse of multiple regression analysis. As a remedy, I highlight the use of dominance analysis and random forests, a…
Descriptors: Predictor Variables, Artificial Intelligence, Evaluation Methods, Multiple Regression Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Elizeth Mayrene Flores Hinostroza; Derling Jose Mendoza; Mercedes Navarro Cejas; Edinson Patricio Palacios Trujillo – International Electronic Journal of Mathematics Education, 2025
This study builds on the increasing relevance of technology integration in higher education, specifically in artificial intelligence (AI) usage in educational contexts. Background research highlights the limited exploration of AI training in educational programs, particularly within Latin America. AI has become increasingly pivotal in educational…
Descriptors: Science Instruction, Artificial Intelligence, Technology Integration, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
So, Joseph Chi-Ho; Ho, Yik Him; Wong, Adam Ka-Lok; Chan, Henry C. B.; Tsang, Kia Ho-Yin; Chan, Ada Pui-Ling; Wong, Simon Chi-Wang – IEEE Transactions on Learning Technologies, 2023
Generic competence (GC) development is an integral part of higher education to provide holistic education and enhance student career development. It also plays a critical role in complementing the curriculum. Many tertiary institutions provide various GC development activities (GCDA). Moreover, institutions strongly need to further understand…
Descriptors: Predictor Variables, Higher Education, Online Courses, Correlation
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Muhammad Aizri Fadillah; Usmeldi Usmeldi; Asrizal Asrizal – Journal of Baltic Science Education, 2024
The role of ChatGPT and higher-order thinking skills (HOTS) as predictors of physics inquiry among uppersecondary students has yet to be widely explored. Therefore, this research aimed to examine upper-secondary students' role in ChatGPT (convenience and quality (CQ), motivation and engagement (ME), and accuracy and trust (AT)) and HOTS as…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Thinking Skills
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Soysal, Dilek; Bani-Yaghoub, Majid; Riggers-Piehl, Tiffani A. – Pedagogical Research, 2022
The relationships between math anxiety and other variables such as students' motivation and confidence have been extensively studied. The main purpose of the present study was to employ a machine learning approach to provide a deeper understanding of variables associated with math anxiety. Specifically, we applied classification and regression…
Descriptors: Mathematics Anxiety, STEM Education, Predictor Variables, Self Esteem
Peer reviewed Peer reviewed
Direct linkDirect link
Immekus, Jason C.; Jeong, Tai-sun; Yoo, Jin Eun – Large-scale Assessments in Education, 2022
Large-scale international studies offer researchers a rich source of data to examine the relationship among variables. Machine learning embodies a range of flexible statistical procedures to identify key indicators of a response variable among a collection of hundreds or even thousands of potential predictor variables. Among these, penalized…
Descriptors: Foreign Countries, Secondary School Students, Artificial Intelligence, Educational Technology
Peer reviewed Peer reviewed
Direct linkDirect link
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
Balyan, Renu; Crossley, Scott A.; Brown, William, III; Karter, Andrew J.; McNamara, Danielle S.; Liu, Jennifer Y.; Lyles, Courtney R.; Schillinger, Dean – Grantee Submission, 2019
Limited health literacy is a barrier to optimal healthcare delivery and outcomes. Current measures requiring patients to self-report limitations are time-consuming and may be considered intrusive by some. This makes widespread classification of patient health literacy challenging. The objective of this study was to develop and validate…
Descriptors: Patients, Literacy, Health Services, Profiles
Peer reviewed Peer reviewed
Direct linkDirect link
Gabriel, Florence; Signolet, Jason; Westwell, Martin – International Journal of Research & Method in Education, 2018
Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…
Descriptors: Artificial Intelligence, Mathematics Instruction, Numeracy, Models
Rachmatullah, Arif – ProQuest LLC, 2021
This dissertation conducted a science classroom intervention using two instructional approaches, computational modeling and paper-based pictorial modeling, in the context of food webs. A series of research papers were written on the impact of the intervention on students' attitudes and learning, and on teachers via professional development and…
Descriptors: Teaching Methods, Science Instruction, Food, Intervention
Peer reviewed Peer reviewed
Direct linkDirect link
Yoo, Jaebong; Kim, Jihie – International Journal of Artificial Intelligence in Education, 2014
Although many college courses adopt online tools such as Q&A online discussion boards, there is no easy way to measure or evaluate their effect on learning. As a part of supporting instructional assessment of online discussions, we investigate a predictive relation between characteristics of discussion contributions and student performance.…
Descriptors: Discussion Groups, Participation, Group Activities, Student Projects
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers