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Jae-Sang Han; Hyun-Joo Kim – Journal of Science Education and Technology, 2025
This study explores the potential to enhance the performance of convolutional neural networks (CNNs) for automated scoring of kinematic graph answers through data augmentation using Deep Convolutional Generative Adversarial Networks (DCGANs). By developing and fine-tuning a DCGAN model to generate high-quality graph images, we explored its…
Descriptors: Performance, Automation, Scoring, Models
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Niloy Meharchandani – Journal of Computers in Mathematics and Science Teaching, 2025
The aim of this paper is to explore the use of function graphs to model a given picture of the Golden Gate Bridge, an iconic architectural structure located in San Francisco. This illustration is sourced from the guide on drawing the Golden Gate Bridge ("How to Draw the Golden Gate Bridge", n.d.). We use the digital graphing calculator…
Descriptors: Models, Graphs, Architecture, Building Design
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Sheng Bi; Zeyi Miao; Qizhi Min – IEEE Transactions on Learning Technologies, 2025
The objective of question generation from knowledge graphs (KGQG) is to create coherent and answerable questions from a given subgraph and a specified answer entity. KGQG has garnered significant attention due to its pivotal role in enhancing online education. Encoder-decoder architectures have advanced traditional KGQG approaches. However, these…
Descriptors: Grammar, Models, Questioning Techniques, Graphs
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Liqing Qiu; Lulu Wang – IEEE Transactions on Education, 2025
In recent years, knowledge tracing (KT) within intelligent tutoring systems (ITSs) has seen rapid development. KT aims to assess a student's knowledge state based on past performance and predict the correctness of the next question. Traditional KT often treats questions with different difficulty levels of the same concept as identical…
Descriptors: Intelligent Tutoring Systems, Technology Uses in Education, Questioning Techniques, Student Evaluation
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Keith C. Radley; Evan H. Dart – Journal of Behavioral Education, 2025
Recent research has indicated that the manner in which single-case data are typically displayed for visual analysis may influence rater decisions regarding the effect of an intervention. Subsequently, researchers have encouraged adherence to a standard assembly for linear graphs in order to control these effects. Others, however, have encouraged…
Descriptors: Graphs, Research Design, Visual Aids, Data Analysis
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Anca Muresan; Mihaela Cardei; Ionut Cardei – International Educational Data Mining Society, 2025
Early identification of student success is crucial for enabling timely interventions, reducing dropout rates, and promoting on-time graduation. In educational settings, AI-powered systems have become essential for predicting student performance due to their advanced analytical capabilities. However, effectively leveraging diverse student data to…
Descriptors: Artificial Intelligence, At Risk Students, Learning Analytics, Technology Uses in Education
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Chao-Jung Wu; Chia-Yu Liu – Journal of Computer Assisted Learning, 2025
Background: Although comprehending illustrated texts is essential, adult readers in this era may not have acquired reading comprehension strategies. Eye-movement modelling example (EMME) is promising for helping less-skilled learners master these strategies; however, its benefits for adults remain unknown. Another understudied factor in the EMME…
Descriptors: Eye Movements, Models, Reading Strategies, Reading Comprehension