As modern higher education increasingly prioritizes personalized and student-centered learning environments, study crafting—the proactive process by which students independently tailor their educational experiences to align with their unique strengths, interests, and goals—has emerged as a vital mechanism for fostering lifelong learning, academic success, and psychological well-being. Adapted from the concept of job crafting in organizational psychology, study crafting empowers students to actively redesign their learning tasks, social interactions, and cognitive perceptions. However, while emerging literature highlights the benefits of these proactive, self-directed behaviors, prior research has predominantly relied on cross-sectional and variable-centered approaches assuming population homogeneity. This approach fundamentally obscures the heterogeneous and dynamic ways students reshape their learning environments over time. Grounded in the Study Demands-Resources (SD-R) theory, the present study addressed these issues by exploring the heterogeneous developmental trajectories of college students' study crafting. Specifically, the present study aimed to identify distinct latent profiles of study crafting, track their dynamic transitions over a one-year period, and investigate whether perceived social support and subjective sense of fit could effectively facilitate and maintain positive crafting behaviors.

A two-wave longitudinal design with a one-year interval was adopted. The final sample comprised 1,711 undergraduate students from seven universities across six provinces in China. At Time 1, participants completed validated measures of study crafting (cognitive, task, and relational dimensions), perceived social support, and subjective sense of fit. At Time 2, study crafting was reassessed. Latent profile analysis (LPA) was used to identify underlying subpopulations with distinct crafting patterns at each time point. Latent transition analysis (LTA) was then employed to model the probabilities of individuals transitioning between these specific profiles over the one-year period, while multinomial logistic regression was used to examine the predictive effects of initial social support and subjective sense of fit on these transitions.

LPA identified four distinct and reproducible profiles of study crafting at both time points: a low profile (below average on all dimensions), a moderate profile (near average on all dimensions), a high cognitive-moderate task-low relational profile (high cognitive, average task, and low relational crafting), and a high profile (above average on all dimensions). LTA indicated that the moderate and high profiles were highly stable, with 66% and 50% of students remaining in their respective groups over the one-year period. In contrast, the low and high cognitive-moderate task-low relational groups exhibited marked instability, with bidirectional transitions: 55% of the low-profile students transitioned to the high cognitive-moderate task-low relational profile, while 45% of that group reverted to the low profile. Notably, both perceived social support and subjective sense of fit significantly predicted positive transitions and buffered against downward transitions into the low profile.

These findings offer novel insights into the complex, multidimensional nature of study crafting. The identification of the high cognitive-moderate task-low relational group suggests that reliance on cognitive adjustments alone—without commensurate behavioral engagement in relational or task domains—may create a precarious state of cognitive dissonance. This mismatch ultimately drives students back into maladaptive, low-crafting patterns. The results also support and extend SD-R theory by demonstrating that holistic crafting behaviors depend heavily on a synergistic combination of resources. Specifically, external resources, such as perceived social support, provide the necessary emotional security to undertake the interpersonal risks associated with relational crafting, while internal resources, such as a strong subjective sense of fit, provide the intrinsic psychological comfort and efficacy required to sustain optimal autonomous learning over time.

The dynamic trajectories identified in this study offer targeted practical implications for higher education institutions. Rather than implementing generic educational programs, educators should adopt differentiated intervention strategies tailored to high-risk subgroups. For low-profile students, interventions should first stimulate cognitive crafting by helping them reflect on the meaning of their studies, followed by peer mentoring to scaffold relational and task crafting. For the high cognitive-moderate task-low relational group, institutions should reduce the behavioral costs of relational engagement by integrating structured, low-risk collaborative tasks into the curriculum. Ultimately, universities should build multilevel support networks and foster an inclusive campus climate to enhance both perceived social support and subjective sense of fit. By doing so, educators can effectively activate students' internal and external resources, facilitating sustainable transitions toward balanced, high-level study crafting and thereby improving overall academic well-being.