NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 465 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Melissa Kay Diliberti; Heather L. Schwartz; Sy Doan; Anna Shapiro; Lydia R. Rainey; Robin J. Lake – RAND Corporation, 2024
The release of such generative artificial intelligence (AI) tools as ChatGPT in 2022 was a major advancement in the field of AI. Two burning questions for kindergarten through grade 12 (K--12) educators are to what extent new generative AI tools will change teaching and whether they will improve learning. The answers to these questions are not yet…
Descriptors: Artificial Intelligence, Instructional Materials, Elementary School Teachers, Secondary School Teachers
Peer reviewed Peer reviewed
Direct linkDirect link
Kim, Keunjae; Kwon, Kyungbin; Ottenbreit-Leftwich, Anne; Bae, Haesol; Glazewski, Krista – Education and Information Technologies, 2023
This study aims to explore the middle schoolers' common naive conceptions of AI and the evolution of these conceptions during an AI summer camp. Data were collected from 14 middle school students (12 boys and 2 girls) from video observations and learning artifacts. The findings revealed 6 naive conceptions about AI concepts: (1) AI was the same as…
Descriptors: Middle School Students, Misconceptions, Artificial Intelligence, Summer Programs
Jeff Schiel; Becky L. Bobek; Joyce Z. Schnieders – ACT, Inc., 2023
There is growing interest in artificial intelligence (AI) tools, especially high-profile tools like ChatGPT, and these tools now appear to be part of the education experience for many high school students. To investigate students' use of AI tools for school assignments, their impressions of how using the tools might affect them cognitively and…
Descriptors: High School Students, Artificial Intelligence, Learner Engagement, Technology Uses in Education
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Fletcher Wadsworth; Josh Blaney; Matthew Springsteen; Bruce Coburn; Nischal Khanal; Tessa Rodgers; Chase Livingston; Suresh Muknahallipatna – International Journal of Technology in Education and Science, 2024
Artificial Intelligence (AI) and, more specifically, Machine Learning (ML) methodologies have successfully tailored commercial applications for decades. However, the recent profound success of large language models like ChatGPT and the enormous subsequent funding from governments and investors have positioned ML to emerge as a paradigm-shifting…
Descriptors: Secondary School Students, Artificial Intelligence, High School Teachers, College Faculty
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Ayse Alkan; Ezgi Pelin Yildiz – International Journal of Research in Education and Science, 2024
The main goal of this study is to reveal special talented primary school students' perceptions of artificial intelligence, one of the popular concepts of recent times, through metaphors. In this study, the phenomenological design, which is within the scope of qualitative research, was used. In this study, Türkiye Science and Art Center included…
Descriptors: Foreign Countries, Gifted, Elementary School Students, Middle School Students
Peer reviewed Peer reviewed
Direct linkDirect link
Febri Yanti; Lufri Lufri; Yuni Ahda – Open Education Studies, 2025
Augmented reality (AR) became increasingly popular in education worldwide as a useful tool for improving student engagement, teamwork, and problem-solving abilities to enhance students' skills in Education 4.0 (E4.0). This research aimed to analyze and highlight several research publications that examined the use of AR to improve the skills of…
Descriptors: Computer Simulation, High School Seniors, Skill Development, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Héctor J. Pijeira-Díaz; Sophia Braumann; Janneke van de Pol; Tamara van Gog; Anique B. H. Bruin – British Journal of Educational Technology, 2024
Advances in computational language models increasingly enable adaptive support for self-regulated learning (SRL) in digital learning environments (DLEs; eg, via automated feedback). However, the accuracy of those models is a common concern for educational stakeholders (eg, policymakers, researchers, teachers and learners themselves). We compared…
Descriptors: Computational Linguistics, Independent Study, Secondary School Students, Causal Models
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Belle Dang; Andy Nguyen; Sanna Järvelä – Journal of Learning Analytics, 2024
Socially shared regulation in learning (SSRL) contributes to successful collaborative learning (CL). Empirical research into SSRL has received considerable attention recently, with increasingly available multimodal data, advanced learning analytics (LA), and artificial intelligence (AI) providing promising research avenues. Yet, integrating these…
Descriptors: Learning Analytics, Cooperative Learning, Artificial Intelligence, Epistemology
Peer reviewed Peer reviewed
Direct linkDirect link
Zexuan Pan; Maria Cutumisu – British Journal of Educational Psychology, 2024
Background: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. Objective: Using ML algorithms, the current study predicts…
Descriptors: Artificial Intelligence, Secondary School Students, Life Satisfaction, Foreign Countries
Peer reviewed Peer reviewed
Direct linkDirect link
Yannik Fleischer; Susanne Podworny; Rolf Biehler – Statistics Education Research Journal, 2024
This study investigates how 11- to 12-year-old students construct data-based decision trees using data cards for classification purposes. We examine the students' heuristics and reasoning during this process. The research is based on an eight-week teaching unit during which students labeled data, built decision trees, and assessed them using test…
Descriptors: Decision Making, Data Use, Cognitive Processes, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Nasri, Nurfaradilla Mohamad; Nasri, Nurfarahin; Nasri, Nur Faraliyana; Talib, Mohamad Asyraf Abd – IEEE Transactions on Learning Technologies, 2023
Intelligent personal assistants (IPAs) carry massive potential in enhancing students' performance through individualized dynamic scaffolding strategy. Despite IPAs being increasingly recognized among educationists, little is known about their application in the development of students' scientific inquiry skills, particularly in physics. This study…
Descriptors: Academic Achievement, Artificial Intelligence, Handheld Devices, Inquiry
Peer reviewed Peer reviewed
Direct linkDirect link
Jiang, Shiyan; Qian, Yingxiao; Tang, Hengtao; Yalcinkaya, Rabia; Rosé, Carolyn P.; Chao, Jie; Finzer, William – Education and Information Technologies, 2023
As artificial intelligence (AI) technologies are increasingly pervasive in our daily lives, the need for students to understand the working mechanisms of AI technologies has become more urgent. Data modeling is an activity that has been proposed to engage students in reasoning about the working mechanism of AI technologies. While Computational…
Descriptors: Computation, Thinking Skills, Cognitive Processes, Artificial Intelligence
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Karumbaiah, Shamya; Zhang, Jiayi; Baker, Ryan S.; Scruggs, Richard; Cade, Whitney; Clements, Margaret; Lin, Shuqiong – International Educational Data Mining Society, 2022
Considerable amount of research in educational data mining has focused on developing efficient algorithms for Knowledge Tracing (KT). However, in practice, many real-world learning systems used at scale struggle to implement KT capabilities, especially if they weren't originally designed for it. One key challenge is to accurately label existing…
Descriptors: Artificial Intelligence, Middle School Students, Models, Concept Mapping
Peer reviewed Peer reviewed
Direct linkDirect link
Xiao-Fan Lin; Yue Zhou; Weipeng Shen; Guoyu Luo; Xiaoqing Xian; Bo Pang – Education and Information Technologies, 2024
K-12 artificial intelligence (AI) education requires cultivating students' computational thinking in the school curriculum so as to transfer their computational thinking to diverse problems and authentic contexts. However, students may be limited by traditional computational thinking development activities because they may have a lower degree of…
Descriptors: Secondary School Students, Artificial Intelligence, Foreign Countries, Computation
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Garry Vanz V. Blancia; Eddie G. Fetalvero; Philip R. Baldera; Merian C. Mani – Problems of Education in the 21st Century, 2024
These days' educational landscape forces teachers to adapt to changing demands and embrace innovations. In this study, Artificial Intelligence (AI) literacy was analyzed as how it mediates the association between Computational Thinking Skills (CTS) and Organizational Agility (OA) among secondary teachers. A quantitative causal mediation analysis…
Descriptors: Artificial Intelligence, Technological Literacy, Mental Computation, Secondary School Teachers
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7  |  8  |  9  |  10  |  11  |  ...  |  31