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Ayfer Sayin; Mark Gierl – Educational Measurement: Issues and Practice, 2024
The purpose of this study is to introduce and evaluate a method for generating reading comprehension items using template-based automatic item generation. To begin, we describe a new model for generating reading comprehension items called the text analysis cognitive model assessing inferential skills across different reading passages. Next, the…
Descriptors: Algorithms, Reading Comprehension, Item Analysis, Man Machine Systems
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Anna Keune – International Journal of Computer-Supported Collaborative Learning, 2024
A key commitment of computer-supported collaborative learning research is to study how people learn in collaborative settings to guide development of methods for capture and design for learning. Computer-supported collaborative learning research has a tradition of studying how the physical world plays a part in collaborative learning. Within the…
Descriptors: Design Crafts, Visual Arts, Algorithms, Cooperation
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Line Have Musaeus; Deborah Tatar; Peter Musaeus – Journal of Biological Education, 2024
Computational modelling is widely used in biological science. Therefore, biology students need to learn computational modelling. However, there is a lack of evidence about how to teach computational modelling in biology and what the effects are on student learning. The purpose of this intervention-control study was to investigate how knowledge in…
Descriptors: Computation, Models, High School Students, Biology
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Yaohua Huang; Chengbo Zhang – International Journal of Web-Based Learning and Teaching Technologies, 2024
This study combines link grammar (LG) detector with N-grammar model to analyze and evaluate grammar in compositions. And then the composition level is judged through information entropy. Finally, the composition score is calculated based on the overall composition level and grammar weight. The experimental results show that the combined weight of…
Descriptors: Grammar, Student Evaluation, Artificial Intelligence, Writing (Composition)
Jessica Adams-Grigorieff – ProQuest LLC, 2023
With recent advances in generative artificial intelligence, it may come as no surprise that AI influences our society in profound ways. This dissertation project examines how educational and social media platforms and their algorithms shape educational practices and the identity, digital literacies and views of middle school youth participants.…
Descriptors: Digital Literacy, Critical Literacy, Algorithms, Artificial Intelligence
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Karimov, Ayaz; Saarela, Mirka; Kärkkäinen, Tommi – International Educational Data Mining Society, 2023
Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…
Descriptors: Student Attitudes, Feedback (Response), Educational Games, Information Retrieval
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Hu, Jie; Peng, Yi; Chen, Xiao – IEEE Transactions on Learning Technologies, 2023
The prevalence of information and communication technologies (ICTs) has brought about profound changes in the field of reading, resulting in a large and rapidly growing number of young digital readers. The article intends to identify key contextual factors that synergistically differentiate high and low performers, high and average performers, and…
Descriptors: Decoding (Reading), Educational Technology, Information Technology, Reading Skills
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating