Trait Emotional intelligence, a construct rooted in the psychological understanding of emotions and their impact on behavior, has increasingly been recognized as a pivotal element in the realm of art education. Originating from Salovey and Mayer’s (1990) seminal work, Trait Emotional Intelligence encompasses a personality trait, also referred to as emotional self-efficacy, and assessed via self-report instruments (Petrides and Furnham, 2000). This multidimensional understanding of emotional processes has significant implications for the field of art education, a domain where emotional expression and comprehension are central.

In the context of art education, Emotional intelligence is not merely an adjunct feature but a core component of artistic development and pedagogy. Gardner’s (2015) theory of multiple intelligences, which includes interpersonal and intrapersonal intelligences (components of Emotional intelligence), underscores the relevance of emotional faculties in artistic pursuits. Students with high Emotional intelligence are often more adept at expressing complex emotional landscapes through their art, a claim supported by contemporary research in arts education (Farrington et al., 2019).

Furthermore, the role of Emotional intelligence in art education extends to the pedagogical approaches employed by educators. Teaching methodologies that integrate Emotional intelligence principles foster an environment where students are encouraged to explore and express their emotions, thereby enhancing their creative capacities. This approach aligns with recent pedagogical trends emphasizing the importance of socio-emotional learning in the classroom (Durlak et al., 2011). Instructors skilled in Emotional intelligence can create a learning atmosphere that values empathy, self-reflection, and emotional expression, crucial for nurturing artistic talent (Valente and Lourenço, 2022).

The implications of Emotional intelligence in art education are also evident in the development of critical thinking and problem-solving skills. As students engage with art, they learn to interpret and analyze emotional content, a process that enhances their ability to understand perspectives different from their own. This aspect of Emotional intelligence, often termed ‘emotional literacy,’ is essential in developing a nuanced appreciation of art, fostering tolerance and empathy (Alemdar and Anilan, 2020).

Integrating emotional intelligence (EI) into art education offers significant benefits for student well-being and mental health. The therapeutic nature of art, coupled with an emphasis on understanding and managing emotions, equips students with coping mechanisms for stress and anxiety (Hoffmann et al., 2021). Art educators, by incorporating EI principles, can contribute to the holistic development of students, addressing both emotional and artistic growth (Kim and Kim, 2018). Beyond bolstering artistic expression and fostering creativity, EI plays a crucial role in socio-emotional learning and student well-being. This integration is fundamental in shaping individuals who are not only adept in artistic skills but also emotionally aware and capable (Huerta et al., 2017).

Based on the above revised literature, the following hypothesis is proposed:

Insight orientation, an empirically grounded concept within the field of psychology, has garnered significant attention for its applications in diverse contexts, including educational settings. Originating from the broader constructs of self-awareness and reflective thinking, insight orientation refers to an individual’s capacity to attain a deep, intuitive understanding of personal experiences, emotions, and thoughts. This self-reflective process plays a relevant role in personal development and decision-making, a notion supported by a great amount of psychological research (Martinsen et al., 2016).

In educational contexts, the application of insight orientation significantly influences learning processes and outcomes. Insight, recognized as a critical component in achieving critical thinking, is increasingly valued in the contemporary educational paradigm (Wagner, 2010). Empirical evidence suggests that students with higher levels of insight orientation demonstrate enhanced problem-solving skills and are more adept at processing complex information (Parker et al., 2004; Robinson and Aronica, 2016). Moreover, the scope of insight orientation extends beyond cognitive abilities to include emotional and social competencies. The development of emotional intelligence, intrinsically linked with insight, positively influences academic performance and interpersonal dynamics within educational environments (Salovey et al., 2002). However, despite various proposed mechanisms explaining the impact of Emotional Intelligence on educational outcomes, there is a notable absence of recent studies exploring the mediating role of Insight Orientation in the relationship between Emotional Intelligence and desired student outcomes. This research extends the application of Insight Orientation, traditionally examined in work-related contexts (Gori et al., 2022), to the educational domain. Supporting this perspective, recent studies indicate that students with greater insight into their emotional states are more adept at managing the challenges and stressors inherent in academic settings (Molero-Jurado et al., 2021; Sha et al., 2022).

Insight orientation is gaining traction in educational circles, recognized by instructors and psychologists for its value in developing well-rounded individuals. Reflective journaling, mindfulness practices, and collaborative learning are increasingly employed to cultivate student insightfulness (Schön, 2017). The impact of insight orientation extends beyond individual students, influencing educational policy and practice. Recent reform discussions advocate for integrating insight-oriented learning objectives into standard curricula, emphasizing a more comprehensive approach that balances cognitive, emotional, and social learning (Wagner, 2010; Robinson and Aronica, 2016).

Based on the above revised literature, the following hypothesis is proposed:

Chinese art students’ engagement has received considerable interest (Halimi et al., 2021). Engagement, defined as the degree of attention, curiosity, interest, optimism, and passion students exhibit in their learning process (Fredricks et al., 2004), is particularly interesting in the field of art education, where creativity and personal investment are keys of academic success.

Recent studies have shown several factors influencing the engagement of Chinese art students. Cultural aspects, deeply ingrained in the Chinese education system, play a significant role. The Confucian heritage, emphasizing respect for authority and rote learning, contrasts with the more explorative and expressive nature of art education (Zhao et al., 2020). This dichotomy often challenges students to reconcile traditional educational values with the creative demands of their artistic pursuits.

Another critical factor is the influence of globalization and exposure to diverse artistic traditions. Chinese art students today have unprecedented access to global art forms, thanks to technological advancements and international collaboration in education (Zhao et al., 2022). This exposure not only broadens their artistic horizons but also presents challenges in integrating these influences within the context of their native artistic traditions.

The pedagogical approaches adopted by art educators in China also significantly impact student engagement. There has been a gradual shift from teacher-centered methods to more student-centered approaches, which encourage personal expression and individual creativity (Huang and Zhu, 2020). This shift aligns with contemporary educational theories emphasizing student agency and active learning, which are crucial in art education for fostering engagement and motivation (Deci and Ryan, 2013). Additionally, technological integration in art education has emerged as a notable factor. The use of digital tools and online platforms has transformed traditional art practices, offering new mediums and methods for artistic expression (Ma, 2021). This digital transformation, while offering new opportunities, also poses challenges in terms of skill adaptation and the potential impact on traditional art forms.

Chinese art students’ engagement hinges on a complex interplay of cultural heritage, educational approaches, global trends, and technology. Established cultural norms collide with contemporary art practices, creating a dynamic tension within evolving art education. Analyzing these diverse elements is essential to cultivate well-rounded artists who excel in both traditional and modern forms, adapting to shifting artistic landscapes. This not only enriches their learning but also contributes to the progressive development of art education in China and internationally.

The full research model has been depicted in Figure 1.

The sample for the present study was recruited among students aged above 18 years enrolled in art study programs, as Bachelor degrees, Master degrees and Ph.D. in private and public institutions. Inclusion criteria were being an Art student in a Higher Education institution in China and being aged 18 years or more. Students taking art courses as complementary to their principal education program were excluded, as summer and winter schools, workshops, online courses or MOOCs (Massive Open Online Courses). Participants who entered the survey have been 986, but only 884 completed the questionnaire (response rate 89.6%). Three questionnaires have been eliminated due that failed to fill the 100% of the survey, giving a final sample of 881 participants. The gender distribution of the sample is a bit biased, 54.1% females, the majority of the participants were in a Bachelor’s Degree level (51.5%), while 40% were in Master’s studies and only 4.9% in Ph.D. programs. Regarding the distribution of the art specialties, 24.4% were enrolled in Calligraphy and traditional Chinese painting, 36.2% in Oil painting, Sculpture and Ceramics, 14.9% in Graphic and Fashion Design, 9.5% in animation and digital arts, and 7.7% in Photography and 7.2% in performance arts.

The global assessment of the model displayed a Chi-square value of 186 with 24 degrees of freedom (p < 0.001), indicating a significant difference from the null model. The baseline model exhibited a Chi-square of 2064 with 36 degrees of freedom (p < 0.001). The fit of the model was assessed using several indices. The Standardized Root Mean Square Residual (SRMR) was 0.049 and the Root Mean Square Error of Approximation (RMSEA) was 0.087, with 95% confidence intervals ranging from 0.076 to 0.099, suggesting a moderate fit. The Comparative Fit Index (CFI) was 0.920, and the Tucker-Lewis Index (TLI) was 0.880, both indicating a good model fit. Other indices such as Bentler-Bonett Non-Normed Fit Index (NNFI), Relative Noncentrality Index (RNI), Bentler-Bonett Normed Fit Index (NFI), Bollen’s Relative Fit Index (RFI), Bollen’s Incremental Fit Index (IFI), and Parsimony Normed Fit Index (PNFI) also supported the adequacy of the model.

In the structural model, the path from Trait Emotional Intelligence to Insight Orientation was significant (β = 0.297, z = 5.99, p < 0.001), indicating a positive relationship. Students’ Engagement was significantly predicted by Insight Orientation (β = 0.316, z = 6.74, p < 0.001) and Trait Emotional Intelligence (β = 0.140, z = 3.21, p = 0.001). The R² values for Insight Orientation and Students’ Engagement were 0.0881 and 0.1454, respectively, indicating the proportion of variance explained by the predictors in each case.

In the measurement model, all observed variables significantly loaded on their respective latent constructs. For Trait Emotional Intelligence, the loadings were significant for all the observed items. The loadings for Insight Orientation were significant for all of the items, and, similarly, for Students’ Engagement.

Variances and covariance among observed variables and latent constructs were significant, indicating distinctiveness and relationships among the constructs. The intercepts for all observed variables were significant (p < 0.001), affirming the model’s intercept structure.

The reliability of the constructs was assessed using Cronbach’s alpha (α), omega hierarchical (ω₁), omega total (ω₂), and omega asymptotic (ω₃). The values for Trait Emotional Intelligence were α = 0.650, ω₁ = 0.668, ω₂ = 0.668, and ω₃ = 0.669, suggesting moderate reliability. For Insight Orientation, the reliability indices were α = 0.730, ω₁ = 0.750, ω₂ = 0.750, and ω₃ = 0.753, indicating good reliability. Students’ Engagement exhibited α = 0.717, ω₁ = 0.724, ω₂ = 0.724, and ω₃ = 0.711, also reflecting good reliability. The Average Variance Extracted (AVE) values for Trait Emotional Intelligence, Insight Orientation, and Students’ Engagement were 0.414, 0.510, and 0.482, respectively, further substantiating the adequacy of the measurement model (see Table 2)

The Goodness of Fit Index (GFI) was exceptionally high at 0.998, and the Adjusted Goodness of Fit Index (AGFI) was 0.994, indicating an excellent fit. The Parsimony Goodness of Fit Index (PGFI) was 0.443, reflecting a moderate level of parsimony. The McDonald Fit Index (MFI) was 0.912, further supporting the model’s fit. The Expected Cross-Validation Index (ECVI) was 0.279, indicative of the model’s potential generalizability.

The path model effectively captured the hypothesized relationships among the constructs. Path diagram (Figure 2) visually represents these relationships.

Hence, the SEM analysis demonstrated a well-fitting model with significant relationships among the constructs. The measurement model confirmed the validity of the latent constructs, and the structural model revealed meaningful paths among the variables. The model’s reliability and validity were supported by various indices, confirming its appropriateness for interpreting the relationships within the data.

Further analysis with the Model 4 allows to compare the total effect of Trait Emotional Intelligence on Students’ Engagement, with the direct effect and the indirect effect, mediated by Insight Orientation. As Table 3 shows, all the effects were significant. Moreover, the indirect effect, through Insight orientation were stronger than the direct effects, providing full support for the hypothesis.

The methodology of the present study presents certain limitations that must be acknowledged. Firstly, the recruitment of participants through social networks may have introduced a selection bias. This mode of recruitment potentially excludes art students who are less active or have no presence on these platforms. Expanding beyond social media platforms to include other forms of outreach might help in obtaining a more representative sample. Additionally, future studies could provide more solid evidence supporting our finding’s patterns, as the positive relationships between Trait Emotional Intelligence and Students’ engagement mediated by Insight Orientation. Another limitation arises from the brief and concise nature of the questionnaire. While advantageous for participant convenience and higher response rates, the limited number of items may have restricted the depth and breadth of the data collected. This brevity, especially in measuring complex constructs like Trait Emotional Intelligence and Insight Orientation, might not fully capture the nuanced aspects of these constructs. Future research could benefit from employing a more comprehensive set of items (Grant et al., 2002). This would be particularly beneficial for capturing the complexity of Trait Emotional Intelligence and Insight Orientation in the context of art education (Martinsen et al., 2016). Lastly, considering the unique context of art education, future studies might examine how these constructs play out in different scholar disciplines to understand better the specificity of these relationships across various education settings. This would significantly contribute to the literature on emotional intelligence and student engagement in the realm of higher education.

The following suggestions can be offered, grounded in the findings of the study. Art curricula can be enriched by integrating modules focused on developing emotional intelligence. These modules should be designed to enhance self-awareness, empathy, emotional regulation, and interpersonal skills (Jenney, 2012b). Practical activities like group discussions, role-plays, and reflective exercises can make these modules interactive and impactful (Huang and Zhu, 2020). In a related vein, teachers should be provided with professional development opportunities focused on emotional intelligence can equip them with the skills to better understand and support their students’ emotional needs. This could include training in identifying emotional cues in students, understanding the role of emotions in learning, and strategies for creating an emotionally supportive classroom environment (Jenney, 2012a). For instance, incorporating exercises that require students to express their emotions through art can bridge the gap between theoretical understanding and practical application. Similarly, conducting workshops that specifically target the development of insight orientation can be highly beneficial for art students (Omotoy, 2023). These workshops should focus on promoting self-reflection, cognitive complexity, and creative thinking. Activities could include guided meditation, analysis of artistic works from multiple perspectives, and exercises that challenge students to rethink and reinterpret their artistic creations (Zhou et al., 2023). Finally, mentorship programs where experienced artists or senior students mentor younger students can provide valuable support (Luo and Lau, 2020). These programs should focus not only on technical skills but also on the emotional and insightful aspects of art creation. Mentors can share their experiences, offer guidance on navigating emotional challenges in art, and provide feedback that fosters insight.

The findings of the present study extend beyond the field of Art education, allowing us to provide a broad spectrum of social implications for Higher Education institutions.

Firstly, the study’s emphasis on insight in the context of art education underscores the value of deep self-awareness and the ability to critically reflect on one’s thoughts, emotions, and behaviors. For Higher Education institutions, this means creating an environment where students are not only academically proficient but also emotionally intelligent and culturally aware individuals who can contribute positively to society (Xu et al., 2019).

Furthermore, the concept of Teaching Emotional Intelligence expands the focus beyond individual development. It encourages institutions to create an environment where emotional intelligence is embedded throughout the curriculum. This approach enhances student engagement, creativity, and resilience, particularly relevant in Chinese art education where emotions, culture, and artistic expression are deeply intertwined. By embracing these dimensions, institutions can cultivate the next generation of artists who are not only technically skilled but also emotionally and culturally competent (Jin and Ye, 2022).

Moreover, fostering insight and Teaching Emotional Intelligence can significantly impact students’ professional development (Pong and Leung, 2023). Art education programs that incorporate these elements equip students with the emotional and cognitive skills needed to navigate the complexities of the art world and succeed in their careers (Wang et al., 2022). This not only benefits individual students but also contributes to the art industry itself, which thrives on innovation, emotional depth, and cultural understanding.