A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education by Abu Zitar, Raed

“…This paper proposes a new deep learning method to detect student emotions. The main aim of this paper is to map the relationship between teaching practices and student learning based on emotional impact. …”
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Enhancing Personalized Learning Experiences through AI-driven Analysis of xAPI Data by ODEH, HANEEN

“…The analysis examined an eLearning lesson with 153 records and 51 participants, it concluded that blooms-level and pre-assessments are reliable predictors of student performance. …”
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Teachers' Perceptions of the Role of Artificial Intelligence in Facilitating Inclusive Practices for Students with Special Educational Needs and Disabilities: A Case Study in a Pri... by BACHIR, HIBAH AHMAD

“…The integration of Artificial Intelligence (AI) in education has raised significant discussions about its role in supporting inclusive learning for students with Special Educational Needs and Disabilities (SEND). …”
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Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

Large Language Models in Medical Education: Opportunities, Challenges, and Future Directions by Alaa Abd-alrazaq (17058018)

“…<p dir="ltr">The integration of large language models (LLMs), such as those in the Generative Pre-trained Transformers (GPT) series, into medical education has the potential to transform learning experiences for students and elevate their knowledge, skills, and competence. …”

Localizing-ground Transmitters Using Airborne Antenna Array by Daffalla, Mirghani Moutaman

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COMPUTER AIDED PROGRAMMING EDUCATION (CAPE) by Al-Sukairi, Abdallah

“…Computer Aided Education (CAE) system is a computer software that aids in the education of a student. Computer-based educational systems are valuable tools to improve learning. …”
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Face Recognition in Uncontrolled Indoor Environment by Abuqaaud, Kamal Adel

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Oversampling techniques for imbalanced data in regression by Samir Brahim Belhaouari (9427347)

“…For tabular data, we also present the Auto-Inflater neural network, utilizing an exponential loss function for Autoencoders. …”

Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic by Saeed Al-Maroof, Rana

“…The data obtained from the study were analyzed by using the partial least squares structural equation modeling (PLS-SEM) and machine learning algorithms. The main hypotheses of this study are related to the effect of COVID-19 on the adoption of Google Meet as COVID-19 rise s various types of fear. …”
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Developing an online hate classifier for multiple social media platforms by Joni Salminen (7434770)

“…We then experiment with several classification algorithms (Logistic Regression, Naïve Bayes, Support Vector Machines, XGBoost, and Neural Networks) and feature representations (Bag-of-Words, TF-IDF, Word2Vec, BERT, and their combination). …”