{"id":23389,"date":"2025-12-22T16:24:36","date_gmt":"2025-12-22T16:24:36","guid":{"rendered":"https:\/\/scientificassociation.org\/?post_type=journal-paper&#038;p=23389"},"modified":"2025-12-22T16:24:36","modified_gmt":"2025-12-22T16:24:36","slug":"neutrosophic-deep-learning-for-student-performance-prediction-a-novel-approach-with-uncertainty-integration-and-ethical-considerations","status":"publish","type":"journal-paper","link":"https:\/\/scientificassociation.org\/ar\/journal-paper\/neutrosophic-deep-learning-for-student-performance-prediction-a-novel-approach-with-uncertainty-integration-and-ethical-considerations\/","title":{"rendered":"Neutrosophic Deep Learning for Student Performance Prediction: A Novel Approach with Uncertainty Integration and Ethical Considerations"},"content":{"rendered":"<p>This paper presents a methodology for predicting student performance using neutrosophic sets and deep learning techniques. The proposed approach involves feature selection and representation using neutrosophic sets, followed by model development using a suitable deep learning architecture. Uncertainty integration is achieved by incorporating neutrosophic values during training using specialized activation functions and modified loss functions. The model&#8217;s performance is evaluated using appropriate metrics, and interpretation techniques are employed to understand the decision-making processes. Ethical considerations regarding student data collection and usage are also addressed. The proposed methodology offers a novel approach to student performance prediction that considers uncertainty and provides insights into the decision-making process, which can help educators, identify areas for improvement and provide targeted interventions.<\/p>\n<p>Keywords: Neutrosophic sets, Deep Learning, Student Performance Prediction, Uncertainty Integration, Feature Representation<\/p>\n<p>Keywords: Neutrosophic sets, Deep Learning, Student Performance Prediction, Uncertainty Integration, Feature Representation<\/p>\n<p>Keywords: Neutrosophic sets, Deep Learning, Student Performance Prediction, Uncertainty Integration, Feature Representation<\/p>\n","protected":false},"featured_media":23398,"template":"","meta":{"_acf_changed":false},"journal-name":[219],"paper-tag":[240],"class_list":["post-23389","journal-paper","type-journal-paper","status-publish","has-post-thumbnail","hentry","journal-name-jcese","paper-tag--3--2"],"acf":[],"_links":{"self":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-paper\/23389","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-paper"}],"about":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/types\/journal-paper"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/media\/23398"}],"wp:attachment":[{"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/media?parent=23389"}],"wp:term":[{"taxonomy":"journal-name","embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/journal-name?post=23389"},{"taxonomy":"paper-tag","embeddable":true,"href":"https:\/\/scientificassociation.org\/ar\/wp-json\/wp\/v2\/paper-tag?post=23389"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}