The purpose of this study was to identify time use patterns of low-achieving university students through latent profile analysis and to examine the characteristics of each profile. The study also explored how individual and institutional factors influ...
The purpose of this study was to identify time use patterns of low-achieving university students through latent profile analysis and to examine the characteristics of each profile. The study also explored how individual and institutional factors influence the likelihood of belonging to each profile and how these time use patterns relate to student outcomes. Data were drawn from the 2024 Korean National Survey of Student Engagement (K-NSSE), including 4,222 students from 104 universities whose previous semester GPA was C+ or below (i.e., less than 3.0). After identifying profiles for the overall sample, additional analyses were conducted separately for metropolitan and local university students. The R3STEP method was used to examine predictors of profile membership, including individual characteristics (gender, academic year, major, high school GPA, household income, career maturity, and institutional commitment) and institutional characteristics (location and size). The BCH method examined differences in student outcomes—information technology proficiency, critical and analytical thinking, problem-solving ability, collaboration skills, diversity understanding, and civic engagement—across the identified profiles.
The research results were summarized as follows. First, five distinct time use patterns were identified among low-achieving university students: campus activity–oriented, social participation–oriented, indifferent, ordinary, and actively engaged. All five profiles appeared in local universities, whereas only three—excluding the ordinary and actively engaged types— were identified in metropolitan universities. This indicates that there are regional differences in the campus experiences of low-achieving students. Second, both individual and institutional factors significantly affected profile membership. In particular, male students, students in higher academic years, and those with higher levels of household income, career maturity, and institutional commitment showed a higher probability of belonging to profiles investing more time in overall activities. Third, student outcomes also differed by time use patterns. In terms of information technology proficiency, critical and analytical thinking, problem-solving ability, and civic engagement, outcomes were highest among the actively engaged group, followed by the campus activity–oriented, ordinary, social participation–oriented, and indifferent groups. For collaboration skills and diversity understanding, the order was: actively engaged, campus activity–oriented, social participation–oriented, ordinary, and indifferent.
These findings suggest several implications. First, it is necessary to shift the perception of student success from academic performance to an experience- and competency-based perspective. Some low-achieving students with strong career maturity and institutional commitment showed active engagement, indicating they should not be considered an at-risk solely based on grades. Second, the ‘indifferent group’, which includes the majority of low-achieving students, showed low participation in both academic and non-academic activities. This group can be seen as an at-risk group, due to its lowest cognitive and non-cognitive outcomes. Universities should make efforts to expand the university experience and prepare an environment in which students develop their academic skills, social relations, and internal growth in a balanced manner.
This study has limitations, including the absence of multilevel analysis and reliance on self-reported questionnaire measuring student outcomes. Future studies should use more detailed data on time use items and conduct comparative analyses with high-achieving student groups.