Publication Date
| In 2026 | 0 |
| Since 2025 | 4 |
| Since 2022 (last 5 years) | 10 |
| Since 2017 (last 10 years) | 11 |
| Since 2007 (last 20 years) | 15 |
Descriptor
| Computer Software | 15 |
| Predictor Variables | 15 |
| Artificial Intelligence | 14 |
| Foreign Countries | 9 |
| Student Attitudes | 8 |
| College Students | 7 |
| Technology Uses in Education | 7 |
| Computer Science Education | 5 |
| English (Second Language) | 5 |
| Feedback (Response) | 5 |
| Models | 5 |
| More ▼ | |
Source
Author
| Desmarais, Michel, Ed. | 2 |
| Fang Huang | 2 |
| Timothy Teo | 2 |
| Ann-Sofie Östberg | 1 |
| Artur Strzelecki | 1 |
| Asrizal Asrizal | 1 |
| Barnes, Tiffany, Ed. | 1 |
| Bin Zou | 1 |
| Birte Keller | 1 |
| Derling Jose Mendoza | 1 |
| Dingyang Peng | 1 |
| More ▼ | |
Publication Type
| Reports - Research | 10 |
| Journal Articles | 9 |
| Collected Works - Proceedings | 3 |
| Speeches/Meeting Papers | 2 |
| Dissertations/Theses -… | 1 |
| Reports - Evaluative | 1 |
| Tests/Questionnaires | 1 |
Education Level
Audience
Location
| China | 3 |
| Australia | 2 |
| Brazil | 2 |
| Israel | 2 |
| Netherlands | 2 |
| Pennsylvania | 2 |
| Spain | 2 |
| Washington | 2 |
| Asia | 1 |
| Connecticut | 1 |
| Czech Republic | 1 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
| Massachusetts Comprehensive… | 1 |
What Works Clearinghouse Rating
Marco Lünich; Birte Keller; Frank Marcinkowski – Technology, Knowledge and Learning, 2024
Artificial intelligence in higher education is becoming more prevalent as it promises improvements and acceleration of administrative processes concerning student support, aiming for increasing student success and graduation rates. For instance, Academic Performance Prediction (APP) provides individual feedback and serves as the foundation for…
Descriptors: Predictor Variables, Artificial Intelligence, Computer Software, Higher Education
Xiaoming Cao; Zhuo Huang; Junchen Wu; Mingzhu Li; Tao He – Education and Information Technologies, 2025
Cyberbullying has garnered growing attention, yet existing research lacks nuanced insights into the dynamics of students' cyberbullying profiles and the associated risk factors across multiple domains. This study aims to (1) investigate K-12 students' cyberbullying profiles, (2) develop an AI predictive model for cyberbullying roles, and (3)…
Descriptors: Bullying, Computer Mediated Communication, Victims, Artificial Intelligence
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
Niklas Humble; Jonas Boustedt; Hanna Holmgren; Goran Milutinovic; Stefan Seipel; Ann-Sofie Östberg – Electronic Journal of e-Learning, 2024
Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant…
Descriptors: Cheating, Artificial Intelligence, Technology Uses in Education, Computer Science Education
Artur Strzelecki – Interactive Learning Environments, 2024
ChatGPT is an AI tool that assisted in writing, learning, solving assessments and could do so in a conversational way. The purpose of the study was to develop a model that examined the predictors of adoption and use of ChatGPT among higher education students. The proposed model was based on a previous theory of technology adoption. Seven…
Descriptors: Computer Software, Artificial Intelligence, Synchronous Communication, Technology Uses in Education
Tsabari, Stav; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2023
Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…
Descriptors: College Students, Computer Science Education, Programming, Error Patterns
Fang Huang; Dingyang Peng; Timothy Teo – European Journal of Education, 2025
Contextualised in the AI--supported English-speaking learning, this study examined the roles of AI affordances in influencing EFL learners' emotional, cognitive, and behavioural speaking engagement, and explored the moderating roles of gender and learner types (on-campus vs. on-job) in influencing AI-supported English-speaking engagement. Data…
Descriptors: Learner Engagement, Second Language Learning, Second Language Instruction, English (Second Language)
Jiaozhi Liang; Fang Huang; Timothy Teo – International Journal of Computer-Assisted Language Learning and Teaching, 2024
Artificial intelligence (AI) is useful to English as a foreign language (EFL) learners, but there is a paucity of research on how they perceive AI. Contextualized in a Chinese university setting, this study investigated Chinese university EFL learners' perceptions of Grammarly in English writing. Based on an extended technology acceptance model…
Descriptors: English (Second Language), Second Language Instruction, Second Language Learning, Writing Processes
Bin Zou; Qinglang Lyu; Yining Han; Zijing Li; Weilei Zhang – Computer Assisted Language Learning, 2025
Adapted from the Technology Acceptance Model (TAM), the Integrated Model of Technology Acceptance (IMTA) has been used to examine the perceptions and acceptance of computer-assisted language learning (CALL), such as online learning, mobile learning, and learning management systems. However, whether IMTA can be applied to empirical research on…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Artificial Intelligence
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
Snowdeal-Carden, Betty A. – ProQuest LLC, 2013
Software engineering is team oriented and intensely complex, relying on human collaboration and creativity more than any other engineering discipline. Poor software estimation is a problem that within the United States costs over a billion dollars per year. Effective measurement of team cohesion is foundationally important to gain accurate…
Descriptors: Information Technology, Computer Software, Teamwork, Engineering
Madhyastha, Tara M.; Tanimoto, Steven – International Working Group on Educational Data Mining, 2009
Most of the emphasis on mining online assessment logs has been to identify content-specific errors. However, the pattern of general "consistency" is domain independent, strongly related to performance, and can itself be a target of educational data mining. We demonstrate that simple consistency indicators are related to student outcomes,…
Descriptors: Web Based Instruction, Computer Assisted Testing, Computer Software, Computer Science Education
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
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

Peer reviewed
Direct link
