Causal model of creative problem-solving behavior in undergraduate students

Abstract

This study examined the relationships among psychological traits, situational factors, and psychological states with creative problem-solving behavior, and identified key predictors of such behavior among undergraduate students. The sample comprised 480 fourth-year undergraduates from four autonomous universities, selected through multi-stage sampling. Analyses were conducted on the overall sample and 22 subgroups classified by biosocial backgrounds.

The study’s conceptual framework was grounded in the interactionism model, which guided the identification of five variable groups. The first group, psychological traits, included core self-evaluations, openness to experience, and mental health. The second group, situational factors, encompassed perceived problem-solving modeling, past experience, and activities in educational institutions. The third group, psychological states, comprised attitudes toward creative problem-solving and perceived behavioral control. The fourth group represented creative problem-solving behavior itself, consisting of causal problem-solving, knowledge integration, and divergent problem-solving behaviors. The fifth group involved biosocial background variables. Measurement tools primarily employed summative rating scales, with reliabilities ranging between .75 and .88.

Five major findings emerged. First, the three forms of creative problem-solving behavior correlated positively at moderate levels, with coefficients from .59 to .66. Second, six variables from psychological traits and situational factors predicted two psychological states. Attitude toward creative problem-solving was predicted at 44.6%, with openness to experience, core self-evaluations, and perceived problem-solving modeling as strongest predictors. Perceived behavioral control was predicted at 59.2%, primarily by core self-evaluations, openness to experience, and past experience.

Third, eight variables from traits, factors, and states jointly predicted three types of creative problem-solving behavior. Causal problem-solving was predicted at 43.9%, with perceived behavioral control, attitude, modeling, and past experience as key predictors. Knowledge integration behavior was predicted at 45.8%, with perceived behavioral control, attitude, past experience, and activities in institutions as main predictors. Divergent problem-solving behavior was predicted at 57.2%, driven by perceived behavioral control, attitude, past experience, and openness to experience.

Fourth, structural equation modeling indicated that creative problem-solving behavior was directly influenced by psychological traits (.308), situational factors (.211), and psychological states (.436). Together, they explained 86.6% of variance in the latent construct of creative problem-solving behavior. Fit indices demonstrated good fit (χ² = 32.826, df = 22, p = 0.0644, RMSEA = 0.032, CFI = 0.997, TLI = 0.991, SRMR = 0.047, N = 480). Psychological traits and situational factors also indirectly influenced creative problem-solving through psychological states, with coefficients of 0.201 and 0.208, respectively. These findings highlight the mediating role of psychological states, indicating that suitable traits and situational supports foster positive states that enhance creative problem-solving.

Fifth, analysis revealed at-risk groups of students with lower levels of all three components of creative problem-solving behavior. These groups included males, first-born students, those with low GPAs, and those lacking work experience. Protective factors identified as most crucial for development were perceived behavioral control, attitudes toward creative problem-solving, and past experience.

The study proposes three directions for future research. First, findings should inform the design of training programs to strengthen creative problem-solving, followed by experimental evaluations of program effectiveness. Second, identified at-risk groups should be studied further using mixed-method approaches, enabling deeper understanding of their needs and targeted interventions that reduce disparities and foster skill enhancement. Third, longitudinal studies should examine the long-term links between creative problem-solving and career or life success. Tracking graduates over three to five years would help validate the importance of these skills and encourage institutions to prioritize their development. Such findings could also guide curriculum reforms to meet future labor market demands.

In conclusion, this research confirms the significant roles of psychological traits, situational factors, and psychological states in shaping creative problem-solving behavior. The findings underscore the mediating function of psychological states, identify at-risk groups needing urgent support, and offer practical implications for educational program design and policy. By addressing these areas, higher education can better prepare students to meet complex challenges with creativity and adaptability.