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Nan Xie; Zhengxu Li; Haipeng Lu; Wei Pang; Jiayin Song; Beier Lu – IEEE Transactions on Learning Technologies, 2025
Classroom engagement is a critical factor for evaluating students' learning outcomes and teachers' instructional strategies. Traditional methods for detecting classroom engagement, such as coding and questionnaires, are often limited by delays, subjectivity, and external interference. While some neural network models have been proposed to detect…
Descriptors: Learner Engagement, Artificial Intelligence, Technology Uses in Education, Educational Technology
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Israel Ulises Cayetano-Jimenez; Erick Axel Martinez-Rios; Rogelio Bustamante-Bello; Ricardo A. Ramirez-Mendoza; Maria Soledad Ramirez-Montoya – IEEE Transactions on Learning Technologies, 2024
Educational robotics (ER) is a discipline of applied robotics focused on teaching robot design, analysis, application, and operation. Traditionally, ER has favored rigid robots, overlooking the potential of soft robots (SRs). While rigid robots offer insights into dynamics, kinematics, and control, they have limitations in exploring the depths of…
Descriptors: Robotics, Educational Technology, Teaching Methods, Learning Activities
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Chih-Hsuan Chen; Chia-Ru Chung; Hsuan-Yu Yang; Shih-Ching Yeh; Eric Hsiao-Kuang Wu; Hsin-Jung Ting – IEEE Transactions on Learning Technologies, 2024
Possible symptoms of intellectual disability (ID) include delayed physical development that becomes more pronounced as the disability progresses, delayed development of gross and fine motor skills, sensory perception problems, and difficulty grasping the integrity of objects. Although there is no cure or reversal, research has shown that extensive…
Descriptors: Intellectual Disability, Disability Identification, Simulated Environment, Computer Simulation
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Lishan Zhang; Linyu Deng; Sixv Zhang; Ling Chen – IEEE Transactions on Learning Technologies, 2024
With the popularity of online one-to-one tutoring, there are emerging concerns about the quality and effectiveness of this kind of tutoring. Although there are some evaluation methods available, they are heavily relied on manual coding by experts, which is too costly. Therefore, using machine learning to predict instruction quality automatically…
Descriptors: Automation, Classification, Artificial Intelligence, Tutoring
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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
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Qiyun Wang; Qian Huang – IEEE Transactions on Learning Technologies, 2024
Blended synchronous learning enables online learners to participate in class activities from geographically separated sites. Due to various challenges, however, online learners are often harder to be engaged and their engagement levels are lower than that of classroom counterparts. This review summarized and synthesized the challenges that led to…
Descriptors: Journal Articles, Blended Learning, Synchronous Communication, Barriers
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Ricardo Conejo Muñoz; Beatriz Barros Blanco; José del Campo-Ávila; José L. Triviño Rodriguez – IEEE Transactions on Learning Technologies, 2024
Automatic question generation and the assessment of procedural knowledge is still a challenging research topic. This article focuses on the case of it, the techniques of parsing grammars for compiler construction. There are two well-known techniques for parsing: top-down parsing with LL(1) and bottom-up with LR(1). Learning these techniques and…
Descriptors: Automation, Questioning Techniques, Knowledge Level, Language
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Liang Zhang; Jionghao Lin; John Sabatini; Conrad Borchers; Daniel Weitekamp; Meng Cao; John Hollander; Xiangen Hu; Arthur C. Graesser – IEEE Transactions on Learning Technologies, 2025
Learning performance data, such as correct or incorrect answers and problem-solving attempts in intelligent tutoring systems (ITSs), facilitate the assessment of knowledge mastery and the delivery of effective instructions. However, these data tend to be highly sparse (80%90% missing observations) in most real-world applications. This data…
Descriptors: Artificial Intelligence, Academic Achievement, Data, Evaluation Methods
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Mario Vallarino; Saverio Iacono; Edoardo Bellanti; Gianni V. Vercelli – IEEE Transactions on Learning Technologies, 2024
This article introduces a novel approach to remote laboratory instruction, specifically designed for teaching three-dimensional modeling using Blender software. The lab uses virtual machines to provide students with the necessary computational power to carry out the course activities, along with the correct version of the software. The flipped…
Descriptors: Flipped Classroom, Distance Education, Laboratories, Peer Evaluation
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Nikola M. Luburic; Luka Z. Doric; Jelena J. Slivka; Dragan Lj. Vidakovic; Katarina-Glorija G. Grujic; Aleksandar D. Kovacevic; Simona B. Prokic – IEEE Transactions on Learning Technologies, 2025
Software engineers are tasked with writing functionally correct code of high quality. Maintainability is a crucial code quality attribute that determines the ease of analyzing, modifying, reusing, and testing a software component. This quality attribute significantly affects the software's lifetime cost, contributing to developer productivity and…
Descriptors: Intelligent Tutoring Systems, Coding, Computer Software, Technical Occupations
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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
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Qiuyu Zheng; Zengzhao Chen; Mengke Wang; Yawen Shi; Shaohui Chen; Zhi Liu – IEEE Transactions on Learning Technologies, 2024
The rationality and the effectiveness of classroom teaching behavior directly influence the quality of classroom instruction. Analyzing teaching behavior intelligently can provide robust data support for teacher development and teaching supervision. By observing verbal and nonverbal behaviors of teachers in the classroom, valuable data on…
Descriptors: Teacher Behavior, Teacher Student Relationship, Verbal Communication, Nonverbal Communication