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Xuefan Li; Marco Zappatore; Tingsong Li; Weiwei Zhang; Sining Tao; Xiaoqing Wei; Xiaoxu Zhou; Naiqing Guan; Anny Chan – IEEE Transactions on Learning Technologies, 2025
The integration of generative artificial intelligence (GAI) into educational settings offers unprecedented opportunities to enhance the efficiency of teaching and the effectiveness of learning, particularly within online platforms. This study evaluates the development and application of a customized GAI-powered teaching assistant, trained…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation, Academic Achievement
Orkun Kocak; Sahin Idil – Journal of Education in Science, Environment and Health, 2025
This study is developing a Deep Learning model automating the coding of drawings students provide about climate change phenomena in our world, as a learning contribution through formative assessment. We started first with ResNet50 architecture, but ultimately, we settled on MobileNetV2 reduced architecture for the sake of being able to integrate…
Descriptors: Climate, Artificial Intelligence, Accuracy, Environmental Education
Alanna L. Peebles; Maura N. Snyder – Communication Teacher, 2025
Higher education has witnessed a paradigm shift from the rapid rise of generative artificial intelligence (genAI). Basing its name on the television show, Are You Smarter Than a 5th Grader?, this single- class activity was designed to foster media literacy students' understanding of popular genAI tools. To compare and contrast the capabilities of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Media Literacy, Digital Literacy
Jie Yang; Ehsan Latif; Yuze He; Xiaoming Zhai – Journal of Science Education and Technology, 2025
The development of explanations for scientific phenomena is crucial in science assessment. However, the scoring of students' written explanations is a challenging and resource-intensive process. Large language models (LLMs) have demonstrated the potential to address these challenges, particularly when the explanations are written in English, an…
Descriptors: Artificial Intelligence, Technology Uses in Education, Automation, Scoring
Katherine E. Reuben; Jalayne J. Arias; Shannon Self-Brown; Erin Vinoski Thomas – Journal of Autism and Developmental Disorders, 2025
Autistic individuals with higher support needs, including those with co-occurring intellectual disability (ID) and language impairment (LI), are underrepresented in research. Researchers who attempt to include this population face unique challenges regarding participant recruitment, informed consent, accurate measurement, and protecting privacy…
Descriptors: Inclusion, Autism Spectrum Disorders, Intellectual Disability, Language Impairments
Okan Yetisensoy – Journal of Pedagogical Research, 2025
Generative artificial intelligence (GenAI) models have led to many positive changes in educational settings; however, the validity of the content they produce remains a significant topic of academic discussion. This research aims to determine the validity of content produced by text-to-image models within the context of social studies education.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Validity, Models
R.-M. Gibeau; D. Cousineau – Teaching Statistics: An International Journal for Teachers, 2025
To this date, few standardized tests measuring students' performance with regards to statistics exist. Only four tests have been proposed for college or university students. The goal of the present study is to investigate these tests. University professors or instructors experienced in teaching statistics were asked to list the concepts they think…
Descriptors: Statistics Education, Student Evaluation, Standardized Tests, Mathematics Tests
Shaona Zhou; Qiuye Li; Yi Zhong; Sihang Liang; Yongxuan Li; Yifeng Ou; Xianqiu Wu – Physical Review Physics Education Research, 2025
Given the widespread presence of competition in educational settings and its complex impact on science learning, how students complete tasks in competitive environments has attracted a wide range of attention. The purpose of this study is to compare students' performance on physics conceptual questions in noncompetitive and competitive…
Descriptors: Competition, Physics, Science Education, Scientific Concepts
Sara Germansky; Patricia Snyder; BoRam Song – Journal of Early Intervention, 2025
The purpose of this study was to use a direct behavioral observation coding system to quantify and categorize children's mands and teachers' contingent responses in three types of typically occurring preschool classroom activities. Children's mands were categorized based on their presumed function, and teachers' responses were coded based on…
Descriptors: Preschool Teachers, Teacher Response, Verbal Operant Conditioning, Reinforcement
Zhao, Zhong; Wei, Jiwei; Xing, Jiayi; Zhang, Xiaobin; Qu, Xingda; Hu, Xinyao; Lu, Jianping – Journal of Autism and Developmental Disorders, 2023
This study segmented the time series of gaze behavior from nineteen children with autism spectrum disorder (ASD) and 20 children with typical development in a face-to-face conversation. A machine learning approach showed that behavior segments produced by these two groups of participants could be classified with the highest accuracy of 74.15%.…
Descriptors: Children, Autism Spectrum Disorders, Symptoms (Individual Disorders), Eye Movements
Sen, Sedat; Cohen, Allan S. – Educational and Psychological Measurement, 2023
The purpose of this study was to examine the effects of different data conditions on item parameter recovery and classification accuracy of three dichotomous mixture item response theory (IRT) models: the Mix1PL, Mix2PL, and Mix3PL. Manipulated factors in the simulation included the sample size (11 different sample sizes from 100 to 5000), test…
Descriptors: Sample Size, Item Response Theory, Accuracy, Classification
Harari, Ofir; Soltanifar, Mohsen; Cappelleri, Joseph C.; Verhoek, Andre; Ouwens, Mario; Daly, Caitlin; Heeg, Bart – Research Synthesis Methods, 2023
Effect modification (EM) may cause bias in network meta-analysis (NMA). Existing population adjustment NMA methods use individual patient data to adjust for EM but disregard available subgroup information from aggregated data in the evidence network. Additionally, these methods often rely on the shared effect modification (SEM) assumption. In this…
Descriptors: Networks, Network Analysis, Meta Analysis, Evaluation Methods
Arbain – Indonesian Journal of English Language Teaching and Applied Linguistics, 2023
This study aims to investigate the types and functions of expressions of fear realized in the form of sentences. With a special context in horror movies, the researcher attempted to reveal the types and functions of fear expressions such as directive, commissive, expressive, assertive, and declarative. This research focuses on the subtitles of the…
Descriptors: Films, Speech Acts, Accuracy, Fear
Ning, Xiaoke – International Journal of Web-Based Learning and Teaching Technologies, 2023
With the vigorous development of intelligent campus construction, great changes have taken place in the development of information technology in colleges and universities from the previous digital to intelligent development. In the teaching process, the analysis of students' classroom learning has also changed from the previous manual observation…
Descriptors: College Students, Algorithms, Student Behavior, Artificial Intelligence
Giménez-Fernández, Tamara; Vicente-Conesa, Francisco; Luque, David; Vadillo, Miguel A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
In a typical probabilistic cuing experiment, participants are asked to find a visual target among a series of distractors. Although participants are not informed about this, the target appears more frequently in one region of the display, resulting in faster search times for targets located in this region. This bias is thought to depend on a…
Descriptors: Short Term Memory, Probability, Cues, Attention

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