clustering undergraduate students based on their self-esteem and academic achievement via the k-means approach

Introduction: self-esteem is one of the key foundations of human personality and is known as an important component in mental health and social psychology. paying attention to the factors that contribute to students' academic achievement is a step toward long-term development and leads to proper planning to advance educational goals. this study was devoted to cluster undergraduate students of shahrekord university of medical sciences based on their self-esteem and academic achievement.methods: the multi-stage cluster sampling method was used to select 260 undergraduate students from various fields in 2022. the data collection tool included a background information checklist, a 10-item self-esteem questionnaire, and a 39-item academic achievement questionnaire. the elbow method was used to estimate the number of optimal clusters. the nbclust package in r 4.2.1 software was used for clustering analysis based on the k-means approach.results: in this study, out of 260 participating students, 176 (67.7%) were girls and 84 (32.3%) were boys. the overall average ± standard deviation of academic achievement was 105.2 ± 10.3. there is a positive and significant correlation (r = 0.44) between academic achievement and self-esteem (p-value <0.001). the optimal number of clusters was estimated as four based on the elbow method. self-esteem in cluster number 1 with 35 students was at the lowest level at -2.6±2.9. cluster number 4 with 48 students had less academic progress with 94.0 ± 6.1 than the other three clusters.conclusion: based on the obtained findings, performing effective interventions for promoting self-esteem and academic achievement seems necessary.