Titlebook: Breaking Barriers with Generative Intelligence. Using GI to Improve Human Education and Well-Being; First International Azza Basiouni,Clau

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A Transformer-Based Generative AI Model in Education: Fine-Tuning BERT for Domain-Specific in Studeswers about advising high school students toward their future. This transformer, takes the input as a pair from the context and the question, and the output defined with the start and end positions of the answer in the context. Accordingly, the collected dataset is converted into json file, and then

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Predicting Student Retention in Higher Education Using Machine Learning,categorical variables and scale numerical features, hyperparameter tuning using GridSearchCV to optimize the model, and evaluation of the model‘s performance using metrics such as accuracy, precision, recall, F1-score, and ROC curves. Visualizations were generated to provide deeper insights into the

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Building and Evaluating a Chatbot Using a University FAQs Dataset,ayers with ReLU activation functions and dropout layers to prevent overfitting. The model is trained over 200 epochs with a batch size of 5, utilizing the Adam optimizer and categorical cross-entropy loss function. The results demonstrate the chatbot’s high accuracy and effectiveness, achieving an a

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Conference proceedings 2024cietal implications of GI. Participants learned to tackle social concerns and promote diversity in research and development through keynote presentations, panel discussions, and interactive workshops..

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Carsten Q. Schneider,Claudius Wagemanne fore alarming predictions about its effects. This paper aims to describe the opportunities emerging from the use of artificial intelligence and ChatGPT to improve education, but also to provide an early assessment of ChatGPT in education.