[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122114-en":3,"doc-seo-122114-105":29,"detail-sidebar-cat-0-en-105":89},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":11},122114,1099514068035,"Ezra","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Unlocking Untapped Potential - How Machine Learning Can Bridge the Gifted Identification Gap","This research poster presents a compelling investigation into the potential of machine learning to address the critical gap in gifted identification, particularly within educational frameworks. The study, spearheaded by Al Mansor Helal at the University of Arkansas, Fayetteville, and advised by Jonathan Wai, explores how advanced computational methods can identify and nurture latent talent more effectively than traditional approaches. The document details the methodology, expected outcomes, and implications of utilizing machine learning algorithms to analyze diverse datasets, aiming to provide a more equitable and comprehensive system for recognizing giftedness. The research posits that by leveraging the predictive power of machine learning, educational institutions can unlock untapped potential in students who might otherwise be overlooked by conventional assessment tools. This innovative approach could revolutionize how gifted programs are designed and implemented, ensuring that a broader spectrum of students receives the support and enrichment necessary to thrive. The work is part of the Three-Minute Thesis Research Posters collection, highlighting concise yet impactful research presentations.","University of Arkansas, Fayetteville  \nScholarWorks@UARK  \n\n| Three-Minute Thesis Research Posters | Three-Minute Thesis |\n| --- | --- |\n| 2024\u003Cbr>Unlocking Untapped Potential: How Machine Learning Can Bridge the Gifted Identification Gap (2024)\u003Cbr>Al Mansor Helal\u003Cbr>University of Arkansas, Fayetteville\u003Cbr>Follow this and additional works at: [https://scholarworks.uark.edu/mtsturpc](https://scholarworks.uark.edu/mtsturpc)\u003Cbr> Part of the Higher Education Commons |  |\n\nCitation  \nHelal, A. (2024) . Unlocking Untapped Potential: How Machine Learning Can Bridge the Gifted Identification Gap (2024) . Three-Minute Thesis Research Posters. Retrieved from  \n[https://scholarworks.uark.edu/mtsturpc/72](https://scholarworks.uark.edu/mtsturpc/72)  \nThis Poster is brought to you for free and open access by the Three-Minute Thesis at ScholarWorks@UARK. It has been accepted for inclusion in Three-Minute Thesis Research Posters by an authorized administrator of ScholarWorks@UARK. For more information, please contact [uarepos@uark.edu](uarepos@uark.edu).  \nAl Mansor Helal  \nUnlocking Untapped Potential: How Machine Learning Can Bridge the Gifted Identification Gap  \nFaculty Advisor: Jonathan Wai  \nUNLOCKING UNTAPPED POTENTIAL: HOW MACHINE LEARNING CAN BRIDGE THE GIFTED IDENTIFICATION GAP","cbCaimbbJVgu9ETN","https://ap.wps.com/l/cbCaimbbJVgu9ETN","pdf",540157,1,3,"English","en",105,"# Unlocking Untapped Potential: How Machine Learning Can Bridge the Gifted Identification Gap\n## Three-Minute Thesis Research Posters\n## 2024\n## Al Mansor Helal","[{\"question\":\"What is the primary goal of this research?\",\"answer\":\"The primary goal is to explore how machine learning can improve the identification of gifted individuals, bridging the gap left by traditional methods.\"},{\"question\":\"Who conducted this research and where?\",\"answer\":\"The research was conducted by Al Mansor Helal from the University of Arkansas, Fayetteville, under the advisement of Jonathan Wai.\"},{\"question\":\"What is the significance of using machine learning in gifted identification?\",\"answer\":\"Machine learning offers the potential to analyze diverse datasets and identify giftedness more equitably and comprehensively than conventional assessment tools.\"}]","Unlocking Untapped Potential - 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