[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119115-en":3,"doc-seo-119115-105":30,"detail-sidebar-cat-0-en-105":91},{"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":29},119115,2336464648322,"Aria","https://ap-avatar.wpscdn.com/avatar/2200025388227c56fec?_k=1778556882303663488",8,"Research & Report","AI-driven analysis - optimizing tertiary education policy through machine learning insights","Tertiary education underpins human capital and societal development, and the Philippines’ Universal Access to Quality Tertiary Education (UAQTE) Act aims to expand equitable access by providing eligible students with free tertiary study. This study assesses UAQTE implementation using student perspectives through qualitative analysis combined with machine learning. Multiclass text classification with BERT and topic modeling with BERTopic analyze responses to reveal experience- and perception-based themes. Results show BERT effectiveness for certain categories while BERTopic improves topic coherence via two-word combinations, highlighting key themes including educational opportunity, implementation, financial support, and appreciation. Recommendations guide program and model optimization.","AI-driven analysis: optimizing tertiary education policy through machine learning insights  \nChristian Y. Sy a, 1,*, Lany L. Maceda a,2, Mideth B. Abisado b,3  \na, b Computer Science and Information and Technology Department, Bicol University, Legazpi City, Philippines b College of Computing and Information Technology, National University, Metro Manila, Philippines  \n[1](1 cysy@bicol-u.edu.ph)[ cysy@bicol-u.edu.ph](1 cysy@bicol-u.edu.ph); [2](2 llmaceda@bicol-u.edu.ph)[ llmaceda@bicol-u.edu.ph](2 llmaceda@bicol-u.edu.ph); [3](3 mbabisado@national-u.edu.ph)[ mbabisado@national-u.edu.ph](3 mbabisado@national-u.edu.ph)  \n* corresponding author  \nARTICLE INFO ABSTRACT  \n\n| Article history\u003Cbr>Received March 3, 2023 Revised March 19, 2024 Accepted March 29, 2024 Available online May 31, 2024\u003Cbr>Keywords\u003Cbr>Multiclass text classification\u003Cbr>Topic modeling BERT\u003Cbr>BERTopic UAQTE program | Tertiary education is universally recognized as crucial for equipping individuals with the essential knowledge and skills, advancing efforts towards equitable access to quality higher education worldwide. The Philippines' Universal Access to Quality Tertiary Education (UAQTE) Act exemplifies this commitment by providing eligible Filipino students with free tertiary education. This study evaluates the UAQTE program's implementation from the perspectives of student beneficiaries, employing a combined approach of qualitative analysis and machine learning techniques. Supervised and unsupervised machine learning methods, including multiclass text classification using BERT and topic modeling with BERTopic, are utilized to analyze student responses, revealing insights into their experiences and perceptions ofthe program. While BERT proves effective in certain categories, challenges such as overfitting and the delicate balance of sequence length versus model performance are identified BERTopic highlights the importance of capturing two-word combinations for enhancing topic coherence, with key themes identified including\"Educational Opportunity,\" \"Program Implementation,\" \"Financial Support,\" and \"Appreciation and Gratitude,\" underscoring their significance within the UAQTE program. The convergence of themes between BERT and BERTopic provides a nuanced perspective on students'experiences, emphasizing the program's commitment to addressing financial barriers. Recommendations for program enhancement encompass refining focus areas, strengthening support systems, and fostering continuous monitoring and interdisciplinary collaboration to tackle emerging challenges effectively. Additionally, technical optimization recommendations include refining model configurations, exploring advanced techniques to mitigate overfitting, and conducting further research to enhance transformer-based models' effectiveness in analyzing student experiences. This study underscores the importance of ongoing evaluation and improvement of the UAQTE program to ensure its efficacy in providing quality tertiary education and meeting the diverse needs of Filipino students.\u003Cbr>\u003Cbr>This is an open access article under the CC–BY-SA license\u003Cbr> |\n| --- | --- |\n\n1. Introduction  \nTertiary education equips individuals with the competence, ability, and proficiency needed for success across various fields. It provides professional training, empowering individuals to impact society positively. Recognizing its significance, there is a global effort to promote equal access to tertiary education, emphasizing its role in economic development, poverty reduction, and sustainable growth.  \nUnder the 4th Sustainable Development Goal (SDG), which is \"Quality Education,\" the United Nations (UN) stresses the significance of inclusive and high-quality education, particularly in nations with low incomes. This aims to ensure equitable access to high-quality tertiary education, eliminate socioeconomic barriers, and position education as a driving force for empowerment, societal progress, and sustainable development. ","cbCaimRWkrxCwkrB","https://ap.wps.com/l/cbCaimRWkrxCwkrB","pdf",702637,1,21,"English","en",105,"# Introduction\n## Global importance of tertiary education\n## UAQTE program context in the Philippines\n## Need for in-depth assessment\n# Methodology\n## Data from student beneficiary perspectives\n## Qualitative analysis and machine learning approach\n## BERT-based multiclass classification\n## BERTopic topic modeling","[{\"question\":\"What problem does the UAQTE program address in the Philippines?\",\"answer\":\"UAQTE is implemented to reduce economic barriers to tertiary education by covering tuition fees and related expenses for eligible Filipino students in public State Universities and Colleges.\"},{\"question\":\"How are student responses analyzed in this study?\",\"answer\":\"The study combines qualitative analysis with machine learning, using multiclass text classification with BERT and topic modeling with BERTopic to analyze student perspectives.\"},{\"question\":\"What key themes are identified from the machine learning models?\",\"answer\":\"Key themes include Educational Opportunity, Program Implementation, Financial Support, and Appreciation and Gratitude, reflecting students’ experiences and perceptions of UAQTE.\"}]","AI-driven analysis - 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