Assessment and thematic analysis of activities of the Schools Division of Benguet based on clustering algorithm

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creativework.keywordsassessment, clustering algorithm, online activity evaluation system, thematic analysis
dc.contributor.advisorCadaoas, Genevieve C.
dc.contributor.authorFrondarina, Gary B.
dc.contributor.chairLedda, Mark Kristian C.
dc.contributor.committeememberSapuay-Guillen, Sheena I.
dc.contributor.committeememberMique Jr., Eusebio L.
dc.contributor.committeememberAgtani, Joven B.
dc.date.accessioned2026-03-16T07:32:04Z
dc.date.available2026-03-16T07:32:04Z
dc.date.issued2024-07
dc.descriptionFull text
dc.description.abstractEvaluation is a critical tool in systematically assessing the effectiveness, efficiency, and output of various projects, programs, and activities. This research delves into the essential steps in activity evaluation, emphasizing the significance of clear goal definition, meticulous data collection, rigorous analysis, and insightful interpretation. It aimed to enhance activity evaluation methodologies and practices for activities within the Schools Division of Benguet (SDO). The study developed an Assessment and Thematic Analysis system using aClustering Algorithm for data analysis. This system processes and analyzes data from activities, providing a comprehensive overview of feedback and participants’ engagement. The study employed both descriptive and applied research designs, integrating the Cross Industry Standard Process for Data Mining (CRISP-DM) framework and the K-means clustering algorithm as the primary analysis tool. Concurrently, the Agile Kanban model was used for system development. The SDO Benguet Online Activity Evaluation System facilitates user segmentation, thematic analysis, and clustering. Rigorous testing ensured adherence to user acceptability standards, indicating the system's reliability and efficiency. Recommendations include encouraging full adoption of the online platform by program owners, providing proper ICT training and technical assistance, and implementing comprehensive monitoring and evaluation strategies. Further studies are suggested to expand assessment processes across different organizational settings, considering additional system configurations for improved outcomes.
dc.format.extentix, 83 p.: ill. (col.).
dc.identifier.citationFrondarina, G. B. (2024). Assessment and thematic analysis of activities of the schools division of benguet based on clustering algorithm. [Unpublished Master's Thesis]. Don Mariano Marcos Memorial State University - Mid La Union Campus, City of San Fernando, La Union. Lakasa ti Sirib, DMMMSU Institutional Repository.
dc.identifier.urihttps://lakasa.dmmmsu.edu.ph/handle/123456789/1208
dc.language.isoEnglish
dc.publisherDon Mariano Marcos Memorial State University - Mid La Union Campus
dc.rights.licenseCC BY 4.0
dc.sdgSDG 4
dc.subjectEducational tests and measurements
dc.subjectEvaluation
dc.subjectEnvironmental impact analysis
dc.subjectExaminations
dc.subjectEducational evaluation
dc.subjectDocument clustering
dc.subjectCluster analysis--Data processing
dc.subjectData mining
dc.subjectElementary school libraries--Activity programs
dc.subjectHigh school libraries--Activity programs
dc.subjectMiddle school libraries--Activity programs
dc.subjectJunior high school libraries--Activity programs
dc.subjectThematic Apperception Test
dc.titleAssessment and thematic analysis of activities of the Schools Division of Benguet based on clustering algorithm
dc.typeThesis
dcterms.accessRightsOpen access
thesis.degree.disciplineCollege of Information Technology,
thesis.degree.levelMaster
thesis.degree.nameMaster in Information Technology
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