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Tian Song; Hang Zhang; Yijia Xiao – IEEE Transactions on Learning Technologies, 2024
High-quality programming projects for education are critically required in teaching. However, it is hard to develop those projects efficiently and artificially constrained by the lecturers' experience and background. The recent popularity of large language models (LLMs) has led to a great number of applications in the field of education, but…
Descriptors: Artificial Intelligence, Education, Intellectual Disciplines, Undergraduate Students
Sonsoles Lopez-Pernas; Kamila Misiejuk; Rogers Kaliisa; Mohammed Saqr – IEEE Transactions on Learning Technologies, 2025
Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…
Descriptors: Students, Artificial Intelligence, Man Machine Systems, Interaction
Lifang Bai; Yijia Wei – IEEE Transactions on Learning Technologies, 2024
ChatGPT can promptly reformulate a text and improve its quality in content and form while preserving the original meaning. Yet, little is known about how learners respond to such reformulations. Here, we employed a three-stage writing task (composing-comparison-rewriting) to investigate how learners notice, integrate, and perceive ChatGPT's…
Descriptors: English (Second Language), Second Language Learning, Writing Evaluation, Artificial Intelligence
Shurui Bai; Donn Emmanuel Gonda; Khe Foon Hew – IEEE Transactions on Learning Technologies, 2024
This case study explored the use of generative artificial intelligence (GenAI), specifically chat generative pretraining transformer (ChatGPT), in writing scenarios for scenario-based learning (SBL). Our research addressed three key questions: 1) how do teachers leverage GenAI to write scenarios for SBL purposes? 2) what is the quality of…
Descriptors: Vignettes, Teaching Methods, Engineering Education, Guidelines
Gerardo Ibarra-Vazquez; Maria Soledad Ramirez-Montoya; Mariana Buenestado-Fernandez – IEEE Transactions on Learning Technologies, 2024
This article aims to study the performance of machine learning models in forecasting gender based on the students' open education competency perception. Data were collected from a convenience sample of 326 students from 26 countries using the eOpen instrument. The analysis comprises 1) a study of the students' perceptions of knowledge, skills, and…
Descriptors: Gender Differences, Open Education, Cross Cultural Studies, Student Attitudes
Jian Liao; Linrong Zhong; Longting Zhe; Handan Xu; Ming Liu; Tao Xie – IEEE Transactions on Learning Technologies, 2024
ChatGPT has received considerable attention in education, particularly in programming education because of its capabilities in automated code generation and program repairing and scoring. However, few empirical studies have investigated the use of ChatGPT to customize a learning system for scaffolding students' computational thinking. Therefore,…
Descriptors: Scaffolding (Teaching Technique), Thinking Skills, Computation, Artificial Intelligence
Zhao, Anping; Yu, Yu – IEEE Transactions on Learning Technologies, 2022
To provide insight into online learners' interests in various knowledge from course discussion texts, modeling learners' sentiments and interests at different granularities are of great importance. In this article, the proposed framework combines a deep convolutional neural network and a hierarchical topic model to discover the hidden structure of…
Descriptors: Online Courses, Student Attitudes, Knowledge Level, Networks
Thi Thuy An Ngo; Thanh Tu Tran; Gia Khuong An; Phuong Thy Nguyen – IEEE Transactions on Learning Technologies, 2024
The growing prevalence of advanced generative artificial intelligence chatbots, such as ChatGPT, in the educational sector has raised considerable interest in understanding their impact on student knowledge and exploring effective and sustainable implementation strategies. This research investigates the influence of knowledge management factors on…
Descriptors: Artificial Intelligence, Educational Environment, Knowledge Management, Student Satisfaction
Kangkang Li; Qian Yang; Xianmin Yang – IEEE Transactions on Learning Technologies, 2024
The student-generated question (SGQ) strategy is an effective instructional strategy for developing students' higher order cognitive and critical thinking. However, assessing the quality of SGQs is time consuming and domain experts intensive. Previous automatic evaluation work focused on surface-level features of questions. To overcome this…
Descriptors: Computer Simulation, Artificial Intelligence, Computer Assisted Testing, Automation
Chad C. Tossell; Nathan L. Tenhundfeld; Ali Momen; Katrina Cooley; Ewart J. de Visser – IEEE Transactions on Learning Technologies, 2024
This article examined student experiences before and after an essay writing assignment that required the use of ChatGPT within an undergraduate engineering course. Utilizing a pre-post study design, we gathered data from 24 participants to evaluate ChatGPT's support for both completing and grading an essay assignment, exploring its educational…
Descriptors: Student Attitudes, Computer Software, Artificial Intelligence, Grading
Ye Zhang; Mo Wang; Jinlong He; Niantong Li; Yupeng Zhou; Haoxia Huang; Dunbo Cai; Minghao Yin – IEEE Transactions on Learning Technologies, 2024
Diagnosing aesthetic perception plays a crucial role in deepening our understanding of student creativity, emotional expression, and the pursuit of lifelong learning within art education. This task encompasses the evaluation and analysis of students' sensitivity, preference, and capacity to perceive and appreciate beauty across different sensory…
Descriptors: Aesthetics, Creativity, Emotional Response, Lifelong Learning
Jiaqi Yin; Tiong-Thye Goh; Yi Hu – IEEE Transactions on Learning Technologies, 2024
This study aimed to examine sustainable effects of chatbot-based formative feedback on intrinsic motivation, cognitive load, and learning performance. A longitudinal quasi-experimental design with 173 undergraduate students was conducted. The experiment is a between-subject design. Students either received formative feedback from a chatbot or a…
Descriptors: Artificial Intelligence, Synchronous Communication, Feedback (Response), Longitudinal Studies
Geller, Shay A.; Gal, Kobi; Segal, Avi; Sripathi, Kamali; Kim, Hyunsoo G.; Facciotti, Marc T.; Igo, Michele; Hoernle, Nicholas; Karger, David – IEEE Transactions on Learning Technologies, 2021
This article provides computational and rule-based approaches for detecting confusion that is expressed in students' comments in couse forums. To obtain reliable, ground truth data about which posts exhibit student confusion, we designed a decision tree that facilitates the manual labeling of forum posts by experts. However, manual labeling is…
Descriptors: Identification, Misconceptions, Student Attitudes, Computer Mediated Communication
Auerbach, Joshua E.; Concordel, Alice; Kornatowski, Przemyslaw M.; Floreano, Dario – IEEE Transactions on Learning Technologies, 2019
It has often been found that students appreciate hands-on work, and find that they learn more with courses that include a project than those relying solely on conventional lectures and tests. This type of project driven learning is a key component of "Inquiry-based learning" (IBL), which aims at teaching methodology as well as content by…
Descriptors: Active Learning, Inquiry, Robotics, Artificial Intelligence
Terzidou, Theodouli; Tsiatsos, Thrasyvoulos; Miliou, Christina; Sourvinou, Athanasia – IEEE Transactions on Learning Technologies, 2016
This study proposes and applies a novel concept for an AI enhanced serious game collaborative environment as a supplementary learning tool in tertiary education. It is based on previous research that investigated pedagogical agents for a serious game in the OpenSim environment. The proposed AI features to support the serious game are the…
Descriptors: Educational Games, Computer Games, Artificial Intelligence, Student Attitudes