Publication Date
In 2025 | 14 |
Since 2024 | 107 |
Descriptor
Source
Author
Danielle S. McNamara | 4 |
Mihai Dascalu | 4 |
Stefan Ruseti | 4 |
Dragan Gaševic | 3 |
Andreea Dutulescu | 2 |
Dongkwang Shin | 2 |
Héctor J. Pijeira-Díaz | 2 |
Ionut Paraschiv | 2 |
Jang Ho Lee | 2 |
Janneke van de Pol | 2 |
Kangkang Li | 2 |
More ▼ |
Publication Type
Education Level
Audience
Practitioners | 1 |
Researchers | 1 |
Location
Germany | 2 |
Hong Kong | 2 |
Turkey | 2 |
United Kingdom | 2 |
California | 1 |
California (Stanford) | 1 |
Canada | 1 |
China | 1 |
Egypt | 1 |
Florida | 1 |
Indonesia | 1 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
Trends in International… | 1 |
What Works Clearinghouse Rating
Lisa Ruth Brunner; Wei William Tao – Journal of International Students, 2024
Artificial intelligence (AI) and automation are newly impacting the governance of international students, a temporary resident category significant for both direct economic contributions and the formation of a "pool" of potential future immigrants in many immigrant-dependent countries. This paper focuses on tensions within Canada's…
Descriptors: Artificial Intelligence, Automation, Migration, Foreign Students
Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
Yi Xue – Education and Information Technologies, 2024
The new era of generative artificial intelligence has sparked the blossoming academic fireworks in the realm of education and information technologies. Driven by natural language processing (NLP), automated writing evaluation (AWE) tools become a ubiquitous practice in intelligent computer-assisted language learning (CALL) environments. Based on…
Descriptors: Literature Reviews, Meta Analysis, Bibliometrics, Artificial Intelligence
Karima Bouziane; Abdelmounim Bouziane – Discover Education, 2024
The evaluation of student essay corrections has become a focal point in understanding the evolving role of Artificial Intelligence (AI) in education. This study aims to assess the accuracy, efficiency, and cost-effectiveness of ChatGPT's essay correction compared to human correction, with a primary focus on identifying and rectifying grammatical…
Descriptors: Artificial Intelligence, Essays, Writing Skills, Grammar
Anderson Pinheiro Cavalcanti; Rafael Ferreira Mello; Dragan Gaševic; Fred Freitas – International Journal of Artificial Intelligence in Education, 2024
Educational feedback is a crucial factor in the student's learning journey, as through it, students are able to identify their areas of deficiencies and improve self-regulation. However, the literature shows that this is an area of great dissatisfaction, especially in higher education. Providing effective feedback becomes an increasingly…
Descriptors: Prediction, Feedback (Response), Artificial Intelligence, Automation
Fan Zhang; Xiangyu Wang; Xinhong Zhang – Education and Information Technologies, 2025
Intersection of education and deep learning method of artificial intelligence (AI) is gradually becoming a hot research field. Education will be profoundly transformed by AI. The purpose of this review is to help education practitioners understand the research frontiers and directions of AI applications in education. This paper reviews the…
Descriptors: Learning Processes, Artificial Intelligence, Technology Uses in Education, Educational Research
Alejandra J. Magana; Syed Tanzim Mubarrat; Dominic Kao; Bedrich Benes – IEEE Transactions on Learning Technologies, 2024
Fostering productive engagement within teams has been found to improve student learning outcomes. Consequently, characterizing productive and unproductive time during teamwork sessions is a critical preliminary step to increase engagement in teamwork meetings. However, research from the cognitive sciences has mainly focused on characterizing…
Descriptors: Artificial Intelligence, Technology Uses in Education, Teamwork, Learner Engagement
Leonora Kaldaras; Kevin Haudek; Joseph Krajcik – International Journal of STEM Education, 2024
We discuss transforming STEM education using three aspects: learning progressions (LPs), constructed response performance assessments, and artificial intelligence (AI). Using LPs to inform instruction, curriculum, and assessment design helps foster students' ability to apply content and practices to explain phenomena, which reflects deeper science…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, STEM Education, Learning Trajectories
Andreea Dutulescu; Stefan Ruseti; Denis Iorga; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
The process of generating challenging and appropriate distractors for multiple-choice questions is a complex and time-consuming task. Existing methods for an automated generation have limitations in proposing challenging distractors, or they fail to effectively filter out incorrect choices that closely resemble the correct answer, share synonymous…
Descriptors: Multiple Choice Tests, Artificial Intelligence, Attention, Natural Language Processing

Andreea Dutulescu; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Assessing the difficulty of reading comprehension questions is crucial to educational methodologies and language understanding technologies. Traditional methods of assessing question difficulty rely frequently on human judgments or shallow metrics, often failing to accurately capture the intricate cognitive demands of answering a question. This…
Descriptors: Difficulty Level, Reading Tests, Test Items, Reading Comprehension
Ngoc My Bui; Jessie S. Barrot – Education and Information Technologies, 2025
With the generative artificial intelligence (AI) tool's remarkable capabilities in understanding and generating meaningful content, intriguing questions have been raised about its potential as an automated essay scoring (AES) system. One such tool is ChatGPT, which is capable of scoring any written work based on predefined criteria. However,…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
Rebecca L. Pharmer; Christopher D. Wickens; Benjamin A. Clegg – Cognitive Research: Principles and Implications, 2025
In two experiments, we examine how features of an imperfect automated decision aid influence compliance with the aid in a simplified, simulated nautical collision avoidance task. Experiment 1 examined the impact of providing transparency in the pre-task instructions regarding which attributes of the task that the aid uses to provide its…
Descriptors: Accountability, Automation, Compliance (Psychology), Task Analysis
Sungbok Shin – ProQuest LLC, 2024
Data visualization is a powerful strategy for using graphics to represent data for effective communication and analysis. Unfortunately, creating effective data visualizations is a challenge for both novice and expert design users. The task often involves an iterative process of trial and error, which by its nature, is time-consuming. Designers…
Descriptors: Artificial Intelligence, Computer Simulation, Visualization, Feedback (Response)
Hosnia M. M. Ahmed; Shaymaa E. Sorour – Education and Information Technologies, 2024
Evaluating the quality of university exam papers is crucial for universities seeking institutional and program accreditation. Currently, exam papers are assessed manually, a process that can be tedious, lengthy, and in some cases, inconsistent. This is often due to the focus on assessing only the formal specifications of exam papers. This study…
Descriptors: Higher Education, Artificial Intelligence, Writing Evaluation, Natural Language Processing
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