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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
George Veletsianos; Shandell Houlden; Nicole Johnson – TechTrends: Linking Research and Practice to Improve Learning, 2024
Much of the literature on artificial intelligence (AI) in education imagines AI as a tool in the service of teaching and learning. Is such a one-way relationship all that exists between AI and learners? In this paper we report on a thematic analysis of 92 participant responses to a story completion exercise which asked them to describe a classroom…
Descriptors: Artificial Intelligence, Technology Uses in Education, Man Machine Systems, Interaction
Xiang Wei; Shuping Sun – International Journal of Information and Communication Technology Education, 2024
To effectively avoid subjective bias in manual evaluation. This article proposes a MIDI piano teaching performance evaluation method based on bidirectional LSTM. This method utilizes a three-layer bidirectional LSTM neural network mechanism to make it easier for the model to capture useful information. In addition, the Spark clustering training…
Descriptors: Musical Instruments, Music Education, Teaching Methods, Educational Technology
Yu Lu; Deliang Wang; Penghe Chen; Zhi Zhang – IEEE Transactions on Learning Technologies, 2024
Amid the rapid evolution of artificial intelligence (AI), the intricate model structures and opaque decision-making processes of AI-based systems have raised the trustworthy issues in education. We, therefore, first propose a novel three-layer knowledge tracing model designed to address trustworthiness for an intelligent tutoring system. Each…
Descriptors: Models, Intelligent Tutoring Systems, Artificial Intelligence, Technology Uses in Education
Carla Quinci – Interpreter and Translator Trainer, 2024
This study combines product- and process-oriented research methods and tools to observe whether and how the presence of pre-translated text affects translation quality and influences the translator's research patterns. It is part of the LeMaTTT project, a simulated longitudinal empirical study exploring the impact of MT on info-mining and thematic…
Descriptors: Artificial Intelligence, Translation, Data Collection, Information Retrieval
Yongyan Zhao; Jian Li – International Journal of Web-Based Learning and Teaching Technologies, 2024
The attention time of students studying in MOOC (Massive Open Online Courses) classroom was analyzed to optimize and further improve their performance. On this basis, a student class model based on convolutional neural networks (CNN) feature extraction was proposed. Through Pr (Adobe Premiere) technology, students' class videos were processed by…
Descriptors: Higher Education, MOOCs, Artificial Intelligence, Networks
Ridvan Elmas; Merve Adiguzel-Ulutas; Mehmet Yilmaz – Education and Information Technologies, 2024
Many people use technological tools that are widely accessible, respond quickly, and have extensive information networks today. Due to recent technological advances in education and the increasing acceptance of Artificial Intelligence (AI) technologies, the issues regarding their implementation in education require identification and analysis.…
Descriptors: Artificial Intelligence, Science Education, Biochemistry, Information Dissemination
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
Han Wan; Hongzhen Luo; Mengying Li; Xiaoyan Luo – IEEE Transactions on Learning Technologies, 2024
Automatic program repair (APR) tools are valuable for students to assist them with debugging tasks since program repair captures the code modification to make a buggy program pass the given test-suite. However, the process of manually generating catalogs of code modifications is intricate and time-consuming. This article proposes contextual error…
Descriptors: Programming, Computer Science Education, Introductory Courses, Assignments
Xuelin Liu; Hua Zhang; Yue Cheng – International Journal of Web-Based Learning and Teaching Technologies, 2024
In this article, a dialogue text feature extraction model based on big data and machine learning is constructed, which transforms the high-dimensional space of text features into the low-dimensional space that is easy to process, so that the best feature words can be selected to represent the document set. Tests show that in most cases, the…
Descriptors: Artificial Intelligence, Data, Text Structure, Classification
Thulasi M. Santhi; K. Srinivasan – IEEE Transactions on Learning Technologies, 2024
Cloud adoption in industrial sectors, such as process, manufacturing, health care, and finance, is steadily rising, but as it grows, the risk of targeted cyberattacks has increased. Hence, effectively defending against such attacks necessitates skilled cybersecurity professionals. Traditional human-based cyber-physical education is resource…
Descriptors: Artificial Intelligence, Information Security, Computer Security, Prevention
Chandan Kumar Tiwari; Mohd. Abass Bhat; Shagufta Tariq Khan; Rajaswaminathan Subramaniam; Mohammad Atif Irshad Khan – Interactive Technology and Smart Education, 2024
Purpose: The purpose of this paper is to identify the factors determining students' attitude toward using newly emerged artificial intelligence (AI) tool, Chat Generative Pre-Trained Transformer (ChatGPT), for educational and learning purpose based on technology acceptance model. Design/methodology/approach: The recommended model was empirically…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Student Attitudes
Bryan Abendschein; Xialing Lin; Chad Edwards; Autumn Edwards; Varun Rijhwani – Journal of Computer Assisted Learning, 2024
Background: Education is often the primary arena for exploring and integrating new technologies. AI and human-machine communication (HMC) are prevalent in the classroom, yet we are still learning how student perceptions of these tools will impact education. Objectives: We sought to understand student perceptions of credibility related to written…
Descriptors: Students, Student Attitudes, Feedback (Response), Writing (Composition)
Yang Zhen; Xiaoyan Zhu – Educational and Psychological Measurement, 2024
The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…
Descriptors: Artificial Intelligence, Models, Cheating, Identification