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Xueqiao Zhang; Chao Zhang; Jianwen Sun; Jun Xiao; Yi Yang; Yawei Luo – IEEE Transactions on Learning Technologies, 2025
Large language models (LLMs) have significantly advanced smart education in the artificial general intelligence era. A promising application lies in the automatic generalization of instructional design for curriculum and learning activities, focusing on two key aspects: 1) customized generation: generating niche-targeted teaching content based on…
Descriptors: Artificial Intelligence, Instructional Design, Technology Uses in Education, Cognitive Ability
Pallavi Singh; Phat K. Huynh; Dang Nguyen; Trung Q. Le; Wilfrido Moreno – IEEE Transactions on Learning Technologies, 2025
In organizational and academic settings, the strategic formation of teams is paramount, necessitating an approach that transcends conventional methodologies. This study introduces a novel application of multicriteria integer programming (MCIP), which simultaneously accommodates multiple criteria, thereby innovatively addressing the complex task of…
Descriptors: Teamwork, Group Dynamics, Research Design, Models
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
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
Pelanek, Radek – IEEE Transactions on Learning Technologies, 2020
Learning systems can utilize many practice exercises, ranging from simple multiple-choice questions to complex problem-solving activities. In this article, we propose a classification framework for such exercises. The framework classifies exercises in three main aspects: (1) the primary type of interaction; (2) the presentation mode; and (3) the…
Descriptors: Integrated Learning Systems, Classification, Multiple Choice Tests, Problem Solving
Crowston, Kevin; Østerlund, Carsten; Lee, Tae Kyoung; Jackson, Corey; Harandi, Mahboobeh; Allen, Sarah; Bahaadini, Sara; Coughlin, Scott; Katsaggelos, Aggelos K.; Larson, Shane L.; Rohani, Neda; Smith, Joshua R.; Trouille, Laura; Zevin, Michael – IEEE Transactions on Learning Technologies, 2020
We present the design of a citizen science system that uses machine learning to guide the presentation of image classification tasks to newcomers to help them more quickly learn how to do the task while still contributing to the work of the project. A Bayesian model for tracking volunteer learning for training with tasks with uncertain outcomes is…
Descriptors: Citizen Participation, Scientific Research, Man Machine Systems, Training
Demmans Epp, Carrie; Bull, Susan – IEEE Transactions on Learning Technologies, 2015
Adding uncertainty information to visualizations is becoming increasingly common across domains since its addition helps ensure that informed decisions are made. This work has shown the difficulty that is inherent to representing uncertainty. Moreover, the representation of uncertainty has yet to be thoroughly explored in educational domains even…
Descriptors: Visual Aids, Data Analysis, Ambiguity (Context), Design
Cocea, Mihaela; Magoulas, George D. – IEEE Transactions on Learning Technologies, 2017
Exploratory learning environments (ELEs) promote a view of learning that encourages students to construct and/or explore models and observe the effects of modifying their parameters. The freedom given to learners in this exploration context leads to a variety of learner approaches for constructing models and makes modelling of learner behavior a…
Descriptors: Generalization, Mathematics Instruction, Computer Simulation, Discovery Learning
Bañeres, David; Clarisó, Robert; Jorba, Josep; Serra, Montse – IEEE Transactions on Learning Technologies, 2014
The synthesis of digital circuits is a basic skill in all the bachelor programmes around the ICT area of knowledge, such as Computer Science, Telecommunication Engineering or Electrical Engineering. An important hindrance in the learning process of this skill is that the existing educational tools for the design of circuits do not allow the…
Descriptors: Electronics, Design, Program Validation, Electronic Learning
Magnisalis, Ioannis; Demetriadis, Stavros – IEEE Transactions on Learning Technologies, 2017
This article presents evaluation data regarding the MAPIS3 architecture which is proposed as a solution for the data-transfer among various tools to promote flexible collaborative learning designs. We describe the problem that this architecture deals with as "tool orchestration" in collaborative learning settings. This term refers to a…
Descriptors: Computer Uses in Education, Cooperative Learning, Computer System Design, Internet
Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
Mejia, Carolina; Florian, Beatriz; Vatrapu, Ravi; Bull, Susan; Gomez, Sergio; Fabregat, Ramon – IEEE Transactions on Learning Technologies, 2017
Existing tools aim to detect university students with early diagnosis of dyslexia or reading difficulties, but there are not developed tools that let those students better understand some aspects of their difficulties. In this paper, a dashboard for visualizing and inspecting early detected reading difficulties and their characteristics, called…
Descriptors: Clinical Diagnosis, Dyslexia, Visualization, Metacognition
Al-Hmouz, A.; Shen, Jun; Al-Hmouz, R.; Yan, Jun – IEEE Transactions on Learning Technologies, 2012
With recent advances in mobile learning (m-learning), it is becoming possible for learning activities to occur everywhere. The learner model presented in our earlier work was partitioned into smaller elements in the form of learner profiles, which collectively represent the entire learning process. This paper presents an Adaptive Neuro-Fuzzy…
Descriptors: Electronic Learning, Blended Learning, Educational Technology, Media Adaptation
Gluga, R.; Kay, J.; Lever, T. – IEEE Transactions on Learning Technologies, 2013
It is important, but very challenging, to design degree programs, so that the sequence of learning activities, topics, and assessments over three to five years give an effective progression in learning of generic skills, discipline-specific learning goals and accreditation competencies. Our CUSP (Course and Unit of Study Portal) system tackles…
Descriptors: College Curriculum, Computer Uses in Education, Educational Objectives, Academic Degrees
Sinclair, J.; Joy, M.; Yau, J. Y.-K.; Hagan, S. – IEEE Transactions on Learning Technologies, 2013
Reusable learning objects support packaging of educational materials allowing their discovery and reuse. Open educational resources emphasize the need for open licensing and promote sharing and community involvement. For both teachers and learners, finding appropriate tried and tested resources on a topic of interest and being able to incorporate…
Descriptors: Resource Units, Shared Resources and Services, Computer Uses in Education, Educational Resources
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