000			02814nam a22002417a 4500
003			FT8769
005			20251106134810.0
008			251106b ||||| |||| 00| 0 eng d
041			_aengtag
050			_a T173 A36 2025
082			_2.
100	1		_a Akmad, Shellamie B.; Carranza, Genevieve V.; Danque, Paulo B.
245			_aThomasights: Evaluating nursery student’ learning styles through body language and engagement
264		1	_a. _b. _cc2025
300			_bCapstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025
336			_2ext _atext _btext
337			_2unmediated _aunmediated _bunmediated
338			_2 volume _a volume _b.
505			_aABSTRACT: Identifying diverse learning styles in early childhood education is a significant challenge that can impact academic progress. This study, titled ThomaSIGHTS: Evaluating Nursery Students Learning Styles through Body Language and Engagement, presented a system designed to analyze nursery students body language and engagement to predict learning style percentages and recommend tailored teaching approaches. ThomaSIGHTS integrated YOLO and DeepSORT algorithm for body language detection, Random Forest for predicting visual, auditory, and kinesthetic learning style percentages, and Hybrid Filtering for personalized teaching recommendations. The system successfully achieved its objectives by detecting body language, predicting learning style percentages, and offering appropriate teaching strategies. The system was evaluated through a survey of IT professionals and nursery teachers based on ISO/TEC 25010 standards, resulting in high scores for Functional Suitability (4.17), Usability (4.35), Reliability (4.33), and Performance Efficiency (4.36), which reflected positive user experiences and system effectiveness. Aditionally, ThomaSIGHTS demonstrated strong classification metrics, including a mean precision of 82.08%, an average recall of 59.42%, an F1 score of 68.25%, accuracy of 62.17%, and average precision (AP) of 79.5%. The conclusion matrix results revealed 4,305 true positive and 3,195 true negatives, through areas for improvement were identified with 2,272 false positives and 917 false negatives. Feedback from IT professionals confirmed the system’s effectiveness in detecting body language and predicting learning style percentages, highlighting its technical reliability and usability. Nursery teachers expressed positive views on the system’s ability to recommend teaching approaches tailored to students learning needs. This feedback underscored ThomaSIGHTS potential as a valuable tool for enhancing classroom engagement and addressing diverse learning styles in early childhood education.
526			_aF
655			_aacademic writing
942			_2lcc _cMS
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