Developing the Short Form of the Survey on Social and Emotional Skills (SSES-SF).

Given the critical role of socio-emotional skills in students' academic success, psychological well-being, and other critical life outcomes, the Organization for Economic Cooperation and Development (OECD) developed the Survey on Social and Emotional Skills (SSES) to measure these skills among school-age students. However, the broad conceptual scope of socio-emotional skills necessitated the use of a large number of items (i.e., 120 items) in the original SSES, which poses challenges regarding survey administration and participant fatigue. To address these issues, this study aimed to develop a short form of the SSES (i.e., SSES-SF). The sample included 29,798 15-year-old students across 10 regions. We developed a 45-item version of SSES-SF using the machine learning approach of genetic algorithm, which is 62.5% shorter than the original 120-item SSES. The reliability, construct validity, reproduced information, concurrent validity, and measurement invariance of the SSES-SF were investigated. We found that the SSES-SF demonstrated satisfactory reliability, construct validity, and concurrent validity. Furthermore, the SSES-SF was able to reproduce a substantial amount of information from the original full-form SSES and exhibited measurement invariance across genders, regions, and language groups. Theoretical and practical implications of the findings are discussed.