China's expansion of higher education has highlighted concerns about educational quality. This study addresses this by investigating the factors influencing student learning outcomes. A key focus is on learning motivation, the internal drive that propels students' learning behaviors and academic goals. Previous research indicates a positive correlation between learning motivation and academic performance, but the complexities of this relationship are not fully understood. This is especially true in the context of Chinese universities where the transition to a more independent learning environment after high school can lead to reduced learning motivation. The study also incorporates learning engagement, encompassing behavioral, emotional, and cognitive aspects that directly influence the learning process. Finally, the study considers personality traits, acknowledging their role in shaping students' learning behaviors and outcomes. Prior research suggests personality traits influence self-efficacy and academic performance, highlighting the need to incorporate this factor in understanding the overall learning dynamic. This research aims to integrate learning motivation, learning engagement, and personality traits within a single framework to better understand their interrelationships and influence on learning effectiveness. By bridging the gap in existing research, this study will offer valuable insights to improve teaching practices and student learning outcomes in Chinese higher education.

The literature review examines existing research on learning motivation, learning engagement, personality traits, and learning effectiveness. Learning motivation is explored as a multi-faceted construct, encompassing both intrinsic (internal) and extrinsic (external) factors. Studies consistently show a positive link between learning motivation and academic performance. Learning engagement is discussed as a crucial aspect of the learning process, encompassing behavioral, cognitive, and emotional dimensions. Research indicates that higher levels of engagement are associated with better academic outcomes. The Big Five personality traits (agreeableness, conscientiousness, extraversion, neuroticism, and openness to experience) are considered, based on their established influence on various aspects of human behavior, including academic performance. Studies have shown that individuals with different personality traits exhibit varying levels of self-efficacy and reliance on social expectations, impacting learning outcomes. The study acknowledges that prior research has examined these variables individually or in pairs, but a comprehensive model integrating all four variables within the university student context is lacking. Therefore, the study aims to test hypotheses that posit significant relationships among these four variables, emphasizing the mediating role of learning engagement and the moderating influence of personality traits.

This quantitative study employs a survey design using a questionnaire to collect data from undergraduate students across multiple Chinese universities. The questionnaire assesses learning motivation (internal and external), learning engagement (behavioral and emotional), personality traits (using a short form of the Big Five inventory), and learning effectiveness. A total of 251 valid responses were obtained and analyzed using SPSS 21 and Amos 24. Pearson product-moment correlation analysis was conducted to explore relationships between the variables. Multiple regression analyses (stepwise and hierarchical) were used to test the hypotheses regarding direct and indirect effects. The Baron and Kenny (1986), Mackinnon et al. (1995), and Mackinnon (2008) methods were used to analyze mediation effects. The moderation effect of personality traits was examined using a centralization variable approach developed by Fang et al. (2022). The reliability of the questionnaire was evaluated using Cronbach's alpha, yielding values above 0.7 for all constructs, indicating high reliability. Validity was assessed through factor analysis, including the Kaiser-Meyer-Olkin (KMO) test and Bartlett's test of sphericity, ensuring the suitability of the data for factor analysis. The principal component analysis confirmed the factor structure of the questionnaire, demonstrating its construct validity. The research framework is depicted in Figure 1, outlining the relationships between learning motivation (independent variable), learning engagement (mediating variable), personality traits (moderating variable), and learning effectiveness (dependent variable).

The study's key findings are: 1) Learning motivation (both internal and external) significantly and positively predicted learning effectiveness (H1 supported). 2) Learning motivation (both internal and external) significantly and positively predicted learning engagement (H2 supported). 3) Learning engagement (both behavioral and emotional) significantly and positively predicted learning effectiveness (H3 supported). 4) Learning engagement partially mediated the relationship between learning motivation and learning effectiveness (H5 partially supported). Specifically, learning engagement explained some, but not all, of the variance in the relationship between learning motivation and learning effectiveness, suggesting the existence of other mediating variables. 5) Personality traits significantly moderated the relationship between learning motivation (both internal and external) and learning effectiveness (H4 supported). This indicates that the strength of the relationship between learning motivation and learning effectiveness varied depending on student personality traits. The average learning motivation was 3.802 (internal 3.868, external 3.736), and the average learning effectiveness was 3.740, indicating that the average motivation and effectiveness were relatively high but also revealing a room for improvement. Correlation analysis confirmed the significant relationships predicted by the hypotheses, providing supporting evidence for the model's construct validity. The regression analysis further solidified the findings, demonstrating the statistical significance of the relationships between variables.

The findings demonstrate a strong positive relationship between learning motivation, learning engagement, and learning effectiveness. The partial mediation effect of learning engagement highlights the importance of translating motivational drive into active engagement in learning activities. The significant moderating role of personality traits indicates that interventions should be tailored to the specific personality profiles of students to maximize their learning effectiveness. The results align with previous research, while also extending understanding of the complex interplay of these variables in the Chinese university context. The partial mediation effect of learning engagement suggests that while motivation is a crucial factor, the actual engagement in the learning process is equally important for achieving high learning effectiveness. The moderating role of personality traits underscores the need for individualized approaches to learning interventions, targeting the specific needs and characteristics of students with different personality types. This is particularly relevant for China's higher education system, where an increasing focus on quality necessitates a thorough understanding of individual student dynamics and effective strategies for promoting learning outcomes. This study is not without limitations; the results only capture a snapshot of these relationships at one point in time, neglecting longitudinal analysis. Future studies could explore these relationships across different time points. This would provide a more comprehensive understanding of their dynamic nature.

This study provides valuable insights into the factors influencing learning effectiveness among Chinese undergraduate students. The integrated model reveals the significant contributions of learning motivation, learning engagement, and personality traits to learning outcomes. The partial mediation effect of learning engagement and the moderating influence of personality traits emphasize the importance of multifaceted approaches to improving student learning. Future research should investigate the specific personality traits that most strongly moderate the learning process, and explore other potential mediating factors that could help to further explain the relationship between learning motivation and learning effectiveness. Longitudinal studies tracking students across their university years could shed more light on the dynamic interplay of these variables.

The study's cross-sectional design limits the ability to establish causal relationships between variables. The reliance on self-reported data may introduce response biases. The use of a relatively short form of the Big Five personality inventory may have limited the depth of analysis on personality traits. Finally, the sample was restricted to undergraduate students in China, limiting the generalizability of the findings to other populations and educational contexts.