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Jonas Flodén – British Educational Research Journal, 2025
This study compares how the generative AI (GenAI) large language model (LLM) ChatGPT performs in grading university exams compared to human teachers. Aspects investigated include consistency, large discrepancies and length of answer. Implications for higher education, including the role of teachers and ethics, are also discussed. Three…
Descriptors: College Faculty, Artificial Intelligence, Comparative Testing, Scoring
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Abdou L. J. Jammeh; Claude Karegeya; Savita Ladage – Education and Information Technologies, 2025
Clicker-integrated instruction is the current innovation in teaching and learning. Several studies used this technology to investigate learning processes, while others mainly used it to asses for learning, facilitation of group discussion and students' participation. All applications require creativity and analytical thinking and very much…
Descriptors: Chemistry, Science Instruction, Audience Response Systems, Computer Assisted Instruction
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Tahereh Firoozi; Hamid Mohammadi; Mark J. Gierl – Journal of Educational Measurement, 2025
The purpose of this study is to describe and evaluate a multilingual automated essay scoring (AES) system for grading essays in three languages. Two different sentence embedding models were evaluated within the AES system, multilingual BERT (mBERT) and language-agnostic BERT sentence embedding (LaBSE). German, Italian, and Czech essays were…
Descriptors: College Students, Slavic Languages, German, Italian
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Wen Xin Zhang; John J. H. Lin; Ying-Shao Hsu – Journal of Computer Assisted Learning, 2025
Background Study: Assessing learners' inquiry-based skills is challenging as social, political, and technological dimensions must be considered. The advanced development of artificial intelligence (AI) makes it possible to address these challenges and shape the next generation of science education. Objectives: The present study evaluated the SSI…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Inquiry, Active Learning
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Bernis Sütçübasi; Tugçe Balli; Herbert Roeyers; Jan R. Wiersema; Sami Çamkerten; Ozan Cem Öztürk; Baris Metin; Edmund Sonuga-Barke – Journal of Attention Disorders, 2025
Objective: ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions with shared etiological and pathophysiological elements. In this paper, we attempt to differentiate these conditions among the young people in terms of intrinsic patterns of brain connectivity revealed during resting state using machine learning…
Descriptors: Elementary School Students, Secondary School Students, Attention Deficit Hyperactivity Disorder, Autism Spectrum Disorders