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Dapeng Qu; Ruiduo Li; Tianqi Yang; Songlin Wu; Yan Pan; Xingwei Wang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
There are many important and interesting academic competitions that attract an increasing number of students. However, traditional student team building methods usually have strong randomness or involve only some first-class students. To choose more suitable students to compose a team and improve students' abilities overall, a competition-oriented…
Descriptors: Competition, Teamwork, Student Behavior, Methods
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
Mao, Shun; Zhan, Jieyu; Wang, Yizhao; Jiang, Yuncheng – IEEE Transactions on Learning Technologies, 2023
For offering adaptive learning to learners in intelligent tutoring systems, one of the fundamental tasks is knowledge tracing (KT), which aims to assess learners' learning states and make prediction for future performance. However, there are two crucial issues in deep learning-based KT models. First, the knowledge concepts are used to predict…
Descriptors: Intelligent Tutoring Systems, Learning Processes, Prediction, Prior Learning
Divasón, Jose; Martinez-de-Pison, Francisco Javier; Romero, Ana; Saenz-de-Cabezon, Eduardo – IEEE Transactions on Learning Technologies, 2023
The evaluation of student projects is a difficult task, especially when they involve both a technical and a creative component. We propose an artificial intelligence (AI)-based methodology to help in the evaluation of complex projects in engineering and computer science courses. This methodology is intended to evaluate the assessment process…
Descriptors: Student Projects, Student Evaluation, Artificial Intelligence, Models
Nan Zhang; Hongkai Wang; Tianqi Huang; Xinran Zhang; Hongen Liao – IEEE Transactions on Learning Technologies, 2024
Trunk anatomy education is critical in the training of the surgeon. Most trunk anatomy education systems use a personal or synthetic anatomical model. It remains difficult to obtain appropriate population anatomy information and create individualized anatomy customization based on a quantity of diverse data. Furthermore, the naked-eye virtual…
Descriptors: Computer Simulation, Simulated Environment, Human Body, Anatomy
Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
Singer, Gonen; Golan, Maya; Shiff, Rachel; Kleper, Dvir – IEEE Transactions on Learning Technologies, 2022
In most academic institutions, students with learning impairments (LIs) are entitled to various accommodations as a means of compensating for their impairment. Ensuring that the appropriate accommodations were selected requires an intelligent support tool to track their effectiveness. In this article, we regard the effectiveness of such…
Descriptors: Academic Accommodations (Disabilities), Students with Disabilities, Program Effectiveness, Equal Education
Mangaroska, Katerina; Vesin, Boban; Kostakos, Vassilis; Brusilovsky, Peter; Giannakos, Michail N. – IEEE Transactions on Learning Technologies, 2021
With the wide expansion of distributed learning environments the way we learn became more diverse than ever. This poses an opportunity to incorporate different data sources of learning traces that can offer broader insights into learner behavior and the intricacies of the learning process. We argue that combining analytics across different…
Descriptors: Learning Analytics, Electronic Learning, Educational Technology, Instructional Design
Alvarez, Ronald Perez; Jivet, Ioana; Perez-Sanagustin, Mar; Scheffel, Maren; Verbert, Katrien – IEEE Transactions on Learning Technologies, 2022
Self-regulated learning (SRL) is a crucial higher-order skill required by learners of the 21st century, who will need to become lifelong learners to adapt to the continually changing environments. Literature provides examples of tools for scaffolding SRL in online environments. In this article, we provide the state-of-the-art concerning tools that…
Descriptors: Metacognition, Teaching Methods, Research Reports, Goal Orientation
Tracy Bobko; Mikiko Corsette; Minjuan Wang; Erin Springer – IEEE Transactions on Learning Technologies, 2024
This article discusses the transformative impact of technology on knowledge acquisition and sharing, focusing on the emergence of the metaverse as a virtual community with vast potential for virtual learning. Learning in the metaverse is found to enhance engagement, motivation, and retention, while fostering 21st-century skills. It also offers…
Descriptors: Educational Innovation, Computer Simulation, Technology Uses in Education, Models
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
Wang, Fei; Huang, Zhenya; Liu, Qi; Chen, Enhong; Yin, Yu; Ma, Jianhui; Wang, Shijin – IEEE Transactions on Learning Technologies, 2023
To provide personalized support on educational platforms, it is crucial to model the evolution of students' knowledge states. Knowledge tracing is one of the most popular technologies for this purpose, and deep learning-based methods have achieved state-of-the-art performance. Compared to classical models, such as Bayesian knowledge tracing, which…
Descriptors: Cognitive Measurement, Diagnostic Tests, Models, Prediction
Lin, Jian-Wei; Koong Lin, Hao-Chiang; Chen, Hong-Ren – IEEE Transactions on Learning Technologies, 2022
Conventional e-learning platforms require a high self-regulatory learning (SRL) ability to ensure learning effectiveness. However, because not everyone has high autonomy and a high SRL ability, many students quit during the online learning period. To enhance the SRL ability, many studies have developed e-learning platforms based on Zimmerman's SRL…
Descriptors: Metacognition, Role Models, Learning Strategies, Personal Autonomy
Jiang, Bo; Wu, Simin; Yin, Chengjiu; Zhang, Haifeng – IEEE Transactions on Learning Technologies, 2020
Accurately tracing the state of learner knowledge contributes to providing high-quality intelligent support for computer-supported programming learning. However, knowledge tracing is difficult when learners have only had a few practice opportunities, which is often common in block-based programming. This article proposed two knowledge tracing…
Descriptors: Programming, Computer Assisted Instruction, Problem Solving, Task Analysis
Vrablecová, Petra; Šimko, Marián – IEEE Transactions on Learning Technologies, 2016
The domain model is an essential part of an adaptive learning system. For each educational course, it involves educational content and semantics, which is also viewed as a form of conceptual metadata about educational content. Due to the size of a domain model, manual domain model creation is a challenging and demanding task for teachers or…
Descriptors: Semantics, Models, Metadata, Programming
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