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Titlebook: Generative Intelligence and Intelligent Tutoring Systems; 20th International C Angelo Sifaleras,Fuhua Lin Conference proceedings 2024 The E

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楼主: 孵化
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Cognitive Engagement Detection of Online Learners Using GloVe Embedding and Hybrid LSTMThis method utilizes deep learning models including a GloVe embedding and a hybrid long short-term memory (LSTM) network within an educational framework called interactive, constructive, active, and passives (ICAP), which classifies the students posts into interactive, constructive, active, and pass
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Profiles of Performance: Game-Based Assessment of Reading Comprehension Skill the extent to which game performance can be used to predict reading comprehension skill, as estimated by standardized tests; and (2) to explore the development of student profiles using game performance, and how these profiles relate to reading test performance. The results indicate that performanc
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Kahoot! as a Tool to Maintain Students’ Attention and Increase Retention Rates: An Experience Reportxperiment that we conducted with 39 computer science students in an introductory programming course, which aimed to investigate the use of Kahoot! in two-hour-long practice sessions. Results highlight some interesting aspects revealed from the students’ feedback: Kahoot! proved to be an exciting and
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Adoption of Digital Games as Pedagogical Aids for Teachers and Pupils in Primary Schools to Overcomenance. However, for many schoolchildren, learning arithmetic can be a difficult and often tedious task. Traditional methods of teaching arithmetic, such as rote memorization and repetitive practice, may not always be effective in engaging pupils and promoting a deep understanding of the material..To
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Educational Games for Computational Thinking: Evaluation of the Scaffolded aMazeD Gameization and design of a variety of learning tools, with particular interest given to digital games. Several studies are investigating their effectiveness in learning CT, however more research is needed on the specific features of these tools, such as scaffolding features. This study evaluates a scaf
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Detection of Pre-error States in Aircraft Pilots Through Machine Learninglanker test data from the COG-BCI dataset, and subsequently employing this model to detect pre-error states in aviation pilots. To address this issue, we applied various machine learning models to the dataset, including Support Vector Machines (SVM), and Random Forests, double Convolutional Neural N
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