Publication Date
| In 2025 | 1 |
| Since 2024 | 1 |
| Since 2021 (last 5 years) | 3 |
| Since 2016 (last 10 years) | 3 |
| Since 2006 (last 20 years) | 3 |
Descriptor
Source
| Education and Information… | 3 |
Author
| Arzu Deveci Topal | 1 |
| Asiye Toker Gokce | 1 |
| Aynur Kolburan Geçer | 1 |
| Canan Dilek Eren | 1 |
| Göktepe Körpeoglu, Seda | 1 |
| Göktepe Yildiz, Sevda | 1 |
| Khatibi, Toktam | 1 |
| Parhizkar, Amirmohammad | 1 |
| Tejeddin, Golnaz | 1 |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 3 |
Education Level
| Higher Education | 2 |
| Postsecondary Education | 2 |
| Junior High Schools | 1 |
| Middle Schools | 1 |
| Secondary Education | 1 |
Audience
Location
| Turkey (Istanbul) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkAsiye Toker Gokce; Arzu Deveci Topal; Aynur Kolburan Geçer; Canan Dilek Eren – Education and Information Technologies, 2025
Artificial intelligence (AI) literacy is critical to shaping students' academic experiences and future opportunities inhigher education. This study examines AI literacy among university students, examining variables such as gender, frequency of use of AI applications, completion of AI-related courses, and field of study. The research involved 664…
Descriptors: Artificial Intelligence, Technological Literacy, College Students, Decision Making
Göktepe Körpeoglu, Seda; Göktepe Yildiz, Sevda – Education and Information Technologies, 2023
Examining students' attitudes towards STEM (science, technology, engineering, and mathematics) fields starting from middle school level is important in their career choices and future planning. However, there is a need to investigate which variables affect students' attitudes towards STEM. Here, we aimed to estimate middle school students'…
Descriptors: Comparative Analysis, Algorithms, Data Collection, Student Attitudes
Parhizkar, Amirmohammad; Tejeddin, Golnaz; Khatibi, Toktam – Education and Information Technologies, 2023
Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…
Descriptors: Algorithms, Grade Point Average, Interdisciplinary Approach, Prediction
