Hierarchical Cluster Analysis Of Medical Student Performance Across Multiple Assessment Modalities

Pillian, Gerald Mahapranaja (2026) Hierarchical Cluster Analysis Of Medical Student Performance Across Multiple Assessment Modalities. Diploma thesis, Institut Teknologi Sepuluh Nopember.

Text 5026221050_Undergraduate_Thesis.pdf Restricted to Repository staff only Download (2MB) | Request a copy

Abstract

Medical education assessment is complex because it involves various examination modalities such as written theory, practical skills, standardised patients, and problem-based learning. Conventional statistical methods often evaluate each modality separately, thus obscuring cross-modality performance patterns. This study applies hierarchical cluster analysis to identify the performance profiles of medical students at the Faculty of Medicine and Health (FKK) ITS Surabaya. Data were collected from 98students from the 2023 and 2024 cohorts who had complete scores across four modalities. Ward’s method with Euclidean distance was applied after Z-score standardisation. The study yielded three statistically distinct clusters (ANOVA, p<0.001): Cluster 1 (At-Risk, 26.5%) with broad deficits across three modalities; Cluster 2 (Mixed Performance, 9.2%) with strengths in structured examinations but catastrophic failure in problem-based assessment (Z=2.236); and Cluster 3 (Average, 64.3%) with balanced above-average performance. A Silhouette Coefficient of 0.3913 and Cophenetic Correlation of 0.6401indicate moderate but acceptable cluster separation. These findings support targeted educational interventions, optimisation of assessment strategies, and an early identification framework for at-risk students. The methodology is reproducible and can be adopted by other medical education institutions.

Item Type:	Thesis (Diploma)
Uncontrolled Keywords:	hierarchical clustering, medical education, multimodal assessment, student performance, Ward's method, educational data mining
Subjects:	L Education > LB Theory and practice of education > LB2300 Higher Education
Divisions:	Faculty of Information Technology > Information System > 57201-(S1) Undergraduate Thesis
Depositing User:	Gerald Mahapranaja Pillian
Date Deposited:	30 Jul 2026 05:07
Last Modified:	30 Jul 2026 05:07
URI:	http://repository.its.ac.id/id/eprint/140001

Actions (login required)

View Item