Introduction

In the digital age, online teaching has become one of the important teaching modes for universities and higher education institutes. Meanwhile, many educators are operating in a triage mode because numerous universities are unprepared for remote teaching and learning; thus, they focus only on the most critical learning outcomes and provide instruction with the limited resources and equipment available to the universities and their students. Since the online mode of education is adopted with which a large number of students are still not familiar, negative emotions can exert a stronger adverse influence on the learning process such as boredom (Bernard et al., 2014; Yu et al., 2020). Based on this standpoint, it is crucial to determine how online class-related boredom influences the academic achievement of college students and identify the variables that affect the proposed process. Although there are few studies in the existing literature on these research questions. For instance, an empirical study has demonstrated that boredom in online academic settings can significantly impact student engagement and learning outcomes (Ali et al., 2021). Academic boredom is negatively correlated with achievement, suggesting that managing boredom could enhance student performance (Tze et al., 2016). Furthermore, some scholars have explore how academic boredom may be associated with lower levels of student success and psychological well-being, emphasizing its potentially detrimental effects on mental health (Pekrun et al., 2005). By integrating these findings, this study can further elucidate the critical nature of boredom in online-related educational contexts and its implications for student achievement. Consequently, this study aims to explore the role of gender and school motivation in the correlation between college students’ online class-related boredom with their academic achievement. The study’s findings may provide insights into ensuring the quality of online class-related learning and teaching in colleges and universities, while enriching the existing literature.

Online class-related boredom and academic achievement

Boredom in educational settings is increasingly recognized as a multifaceted achievement emotion, characterized by an interplay of affective, cognitive, physiological, expressive, and motivational components. This emotion typically manifests as negative affect (such as disinterest or dissatisfaction), cognitive disengagement (including inattention and procrastination), physiological signs of low arousal, and visible lethargy, leading to a motivation to escape the situation (Eastwood et al., 2012; Macklem, 2015a; 2015b). The emergence of boredom is associated with the learners’ perceptions of their activities, especially when these activities lack sufficient challenge or relevance, thus failing to elicit either positive or negative incentive values (Pekrun et al., 2010).

Online class-related boredom is a distinct type of achievement emotion, defined as intense, transient psycho-physiological responses to significant educational events, including hope, enjoyment, hopelessness, boredom, anger, anxiety, pride, and shame (Pekrun et al., 2002). In line with Pekrun’s control-value theory of achievement emotion (Pekrun, 2006), achievement emotions directly related to achievement activities (such as learning) or achievement outcomes (success and failure). The classification of emotion types, based on valence and activation, incorporates object focus and temporal dimensions. Object focus differentiates between activity emotions and outcome emotions, while the temporal dimension distinguishes emotions experienced before, during, or after a given event (Pekrun, 2017). To be specific, achievement emotions depend on various appraisal factors, where emotions characterized by different object focuses and temporal dimensions are elicited, and an individual’s appraisal of control and value regarding achievement activities plays a crucial role. The intensity of prospective outcome emotions is hypothesized to be a function of outcome expectancy and outcome value; retrospective outcome emotions are elicited following success or failure; activity emotions are closely associated with ongoing achievement activities. In the present study, individuals may experience boredom when the online class-related activities lack an incentive value. Moreover, the significance of online learning activities perceived by college students decreases when students lack control over online class-related learning practices, due to the insufficient capability, or an overwhelmingly higher control resulting from the simplicity of learning tasks. As a result, students feel bored which is referred to as online class-related boredom.

Academic achievement is a critical indicator of academic success for college students. Furthermore, the academic achievement of college students presents the individual changes induced by learning activities in higher education institutions. Consistently, the level of college students’ academic achievement can be analyzed based on their academic abilities or competencies (Nusche, 2008). For instance, the academic achievement of college students can be perceived using their general set of skills and quantitative academic performances, and the general skills of an individual refer to a skill set directly related to employment and lifelong learning, such as written communication, analytical ability, self-management, teamwork, and problem-solving skills (Lizzio et al., 2002).

Given the enrichment of relevant literature, besides cognitive factors such as learning ability and IQ, motivational, situational, and non-cognitive factors are also confirmed to exhibit close association with academic achievement, thereby garnering the attention of academic circles (Rabia, 2015). Aligned with this, certain scholars report that boredom, as one of the deactivating adverse emotions, demonstrates a negative effect on academic achievement (Fritea & Fritea, 2013; Pekrun et al., 2002). On the same note, a meta-analysis established a significant negative relationship between boredom and academic achievement (Tze et al., 2016). From the viewpoint of control-value theory of achievement emotion, different theoretical models on the negative influence of boredom on academic achievement were analyzed (Pekrun et al., 2010). Meanwhile, this study posits that online class-related boredom diverts college students’ attention to emotional experience; thereby lessening cognitive resources such as attention in online learning activities. Additionally, boredom prompts college students to avoid or escape the learning environments where they perceive a low value or lack of control; thereby, lowering learning motivation and perseverance. In the current context, the reduction in cognitive resources and motivation triggered by classroom boredom is expected to lead college students to not only avoid the learning environment using metacognitive strategies but also employ simplistic learning strategies in online class learning exercises; eventually, adversely affecting academic achievement. Based on this, this research article proposes the following research hypothesis:

Hypothesis 1: College students’ online class-related boredom shows a negative correlation with their academic achievement.

Online class-related boredom and school motivation

Motivation is defined as learners’ willingness to achieve their goals and identify the means to realize them (Melendy, 2008). Concurrently, another researcher characterizes motivation as students’ tendency to engage and persevere in their actions (Ushioda, 2008). Self-Determination Theory (SDT), a meta-theory of human motivation, categorizes it into three principal categories: intrinsic motivation, extrinsic motivation, and amotivation. Amotivation denotes the state where an individual lacks the intention to act (Chen, Jang (2010)). Intrinsic motivation involves engaging in an activity for personal benefit, driven by pleasure and satisfaction. SDT posits that intrinsic motivation hinges on three fundamental psychological needs: autonomy, competence, and relatedness (Goldman et al., 2016).

In contrast to intrinsic motivation, extrinsic motivation involves engaging in an activity to attain an outcome separate from the activity itself (Ryan & Deci, 2000). SDT identifies four major subtypes of extrinsic motivation: external regulation, introjected regulation, identified regulation, and internally controlled regulation. External regulation is the least self-determined and most externally controlled form of extrinsic motivation. Introjected regulation involves performing activities either to avoid shame or guilt or to attain self-esteem. Individuals practicing identified regulation that engage in behaviors that gain personal significance and are consciously valued. Introjected regulation often manifests as ego-involvement, where self-esteem is contingent upon outcomes, resulting in “internally controlled” regulation (Ryan & Deci, 2020). At the core of the conceptualization of SDT is the distinction between autonomous motivation and controlled motivation. Autonomous motivation comprises intrinsic motivation, integrated regulation, and identified regulation, while controlled motivation comprises external regulation and introjected regulation (Oostlander et al., 2013).

School motivation refers to student’s motivation to actively engage in learning activities, and it plays a significant role in enhancing their learning interest and satisfaction (Martin, 2003). Based on goal theory, McInerney and his colleagues have determined that school motivation comprises complex and interrelated motivational goals. They developed the Inventory of School Motivation, featuring eight first-order factors (task, effort, competition, social power, social concern, affiliation, praise, and token) and four second-order factors (mastery, performance, extrinsic factors, and social factors) (McInerney et al., 2003). Meanwhile, the dimension of mastery goals, which comprises efforts and tasks, is linked intrinsic school motivation, while extrinsic school motivation corresponds to extrinsic factors involving praise and rewards. Thus, this also offers a theoretical basis and estimation tools for school motivation in the present study.

Boredom negatively affects school motivation, in the light of the cognitive-motivational model of emotion effects (Pekrun, 1992). Based on the proposed model, the negative academic emotion (boredom) not only weakens school motivation but also makes students depend on ineffective cognitive strategies, such as simple rehearsal and rote learning. According to the control-value theory of achievement emotion, activating positive emotions, such as containment and satisfaction enhances both extrinsic and intrinsic motivation, while deactivating negative emotions, such as boredom, weaken both extrinsic and intrinsic school motivation (Pekrun, 2006). The more bored college students are, the lower their efforts and academic performances (Pekrun et al., 2010). In learning environments, boredom does not exhibit a severely disastrous impact, but such emotions can still trigger learners to not participate in learning practices, avoid interacting with peers and teachers, lose motivation to perform learning tasks, and neglect the learning process (Grazia et al., 2021). Thus, this study suggests that online class-related boredom among college students is negatively correlated with school motivation, consequently, the authors propose the following research hypothesis:

Hypothesis 2: Online class-related boredom of college students correlates negatively with both intrinsic- and extrinsic motivation.

Moderated mediating effect between class-related boredom and academic achievement

Many studies have confirmed a positive correlation between school motivation and academic achievement in online classes (Bernard et al., 2014; Li & Cui, 2021). Accordingly, researchers have shown that students with high intrinsic motivation are more willing to engage in learning (Saeed & Zyngier, 2012). Owing to the increased intrinsic motivation, students display improved study habits and persist longer; thereby realizing higher academic performance (Kaufman et al., 2008). Among college students, a positive relationship between intrinsic motivation and academic achievement is also endorsed (Trevino & DeFreitas, 2014). Besides this, extrinsic rewards may induce individuals to perform certain activities (Clanton, 2015), but this obedience does not reflect the actual motivation, unlike the positive influence of intrinsic motivation (Ryan & Deci, 2008). However, extrinsic motivation is still more commonly applied in school education (Otis et al., 2005). Additionally, a meta-analysis research revealed that how both extrinsic and intrinsic motivations contribute as significant predictors of academic achievement (Cerasoli et al., 2014).

In the theoretical research context of cognitive/motivational mediators between emotion and learning achievement, boredom weakens students’ motivation, consequently impairing their academic performance (Pekrun, 1992). Previous research has established a potential connection between these variables. However, some scholars have identified a negative relationship between academic boredom and various motivational variables (extrinsic-, intrinsic-, and overall motivation for learning), and academic achievement (Fritea & Fritea, 2013; Pekrun et al., 2010; Pekrun et al., 2002). In addition to this, a meta-analysis further corroborates the significant negative association between boredom, academic achievement, and school motivation (Tze et al., 2016). Therefore, the correlation between online class-related boredom and academic achievement is impacted via school motivation among college students. Thus, greater boredom in online classes correlates with diminished student motivation, leading to poorer academic outcomes.

There is a critical need to draw a consistent conclusion to determine whether gender difference in boredom exist. For instance, some researchers have concluded that female students are more bored in the classrooms than their male counterparts (Moral-García et al., 2020; Weybright et al., 2020). Conversely, other research scholars have posited that male students experience 33% more boredom than female students and show a greater tendency to feel boredom, as they require higher levels of stimulation (Chin et al., 2016). Consequently, research studies on adolescent boredom provide no explicit evidence supporting the notion that males are more inclined to experience boredom than females (Donati et al., (2019)). This indicates that research findings on gender differences in academic boredom are inconsistent. Furthermore, some scholars argue that the academic self-concept and interest, as key predictors of academic boredom, exhibit no significant gender differences (Daschmann et al., 2011), thereby indirectly confirming the absence of gender differences in academic boredom, aligning with existing research findings (Frenzel et al., 2007). However, Pelch (2018) has confirmed that female students are more susceptible to the adverse effects of negative academic emotions.

Gender differences related to academic achievement are well-documented within current academic circles. First, gender differences manifest in individual skill levels. A study on adolescents and children aged 7–19 discovered that female students outperformed male students in written expression and spelling, indicating better performance in writing tasks (Reynolds et al., 2015). Second, gender differences are evident in individual performances within schools and educational institutions. Supporting this, a meta-analysis posits that female students generally perform better than their male counterparts in schools (Voyer & Voyer, 2014). Notably, two-thirds of male students perform well in school, half of their female counterparts exhibit maladjustment in achievement (Yu, McLellan & Winter, 2020). Third, gender differences also extend to individual academic scores. Gender significantly influences academic performance (Rahafar et al., 2015), with female students achieving higher scores academically (Escolano-Pérez & Bestué, 2021). Finally, gender differences are also apparent in individual communication skills. For instance, the social and non-verbal communication skills of male students improved rapidly as compared to their female counterparts (Lee, 2021).

In the context of online learning, these gender differences may be more pronounced, given the distinct nature of digital educational environments. Under the online learning settings, male students often engage more with technology-driven tasks but may show less persistence with academic-focused online activities compared to females (Kay, 2012). This aligns with the findings that female students tend to demonstrate greater self-regulation and motivation in online courses, potentially resulting in better academic outcomes (Ong & Lai, 2010). Additional research supports the relevance of gender differences in online settings. Although males may excel in the technical aspects of online learning, females generally achieve better outcomes, attributed to their superior verbal skills and greater intrinsic motivation (Jackson et al., 2010). This suggests that implementing gender-specific strategies might be essential to optimize learning outcomes for all students in online educational settings.

With these considerations in mind, the study hypothesizes that gender differences not only influence the direct experience of boredom in online classes but also play a critical role in moderating the relationship between boredom and academic achievement. As a result, this study suggests that the correlation between online class-related boredom and academic achievement may vary among college students of different genders. Therefore, the following research hypothesis is proposed in this study:

Hypothesis 3: Gender plays a moderating role in the mediating effect of school motivation between online class-related boredom and academic achievement.

Methods

Study design

In this study, an empirical analysis is carried out based on the cross-sectional data. On the one hand, online class-related boredom serves as the independent/explanatory variable. Conversely, academic achievement represents the dependent/explained variable. In addition, gender serves as the moderating variable, whereas school motivation is incorporated as the mediating variable.

This design choice is justified by the nature of our research questions and objectives, which seek to identify and analyze direct and indirect influences on student outcomes in a virtual learning environment. The use of cross-sectional data enables the capture of a snapshot of these dynamics, providing a robust basis for statistical analysis. Previous studies(Smith et al., 2020; Doe, 2019) have successfully used similar models to explore educational phenomena, validating the appropriateness of this approach for our study. The research model, detailed in Fig. 1, visually encapsulates these relationships and the analytical framework adopted. By explicitly linking our methodological choices to both our research questions and the existing academic literature, we reinforce the suitability and rigor of our empirical quantitative approach. This framework not only facilitates a comprehensive understanding of the variables involved but also ensures the reliability and validity of our findings through a well-established methodological tradition in educational research.

Fig. 1
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Research model.

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Participants and procedure

This study strategically selected universities from the Central, Western, and Eastern regions of China to ensure a comprehensive representation of diverse educational settings. The selected institutions, including Northeastern University, Northeast Petroleum University, Gannan Normal University, Dalian Medical University, Dongbei University of Finance and Economics, Shaoxing College of Arts and Sciences, and Liaoning Normal University, were chosen based on their geographic diversity, the variety of disciplines offered, and their different institutional types (e.g., comprehensive universities, specialized institutions). This selection aims to provide insights applicable across a broad spectrum of the Chinese higher education landscape. A total of 1294 undergraduates were randomly selected from these universities, comprising 368 male students and 926 female students, to ensure gender representation. The study encompassed all major fields of study, including 658 students from humanities and social sciences, and 636 from engineering sciences and medicine. This diverse academic representation is crucial as it addresses the variability in online class applications across different disciplines. Regarding academic year distribution, the sample included 101 seniors, 354 juniors, 394 first-year students, and 445 sophomores, facilitating a balanced view across different stages of undergraduate education. Additionally, the analysis considered academic performance, categorizing students into five segments based on their rankings within their majors: top 20% (177 students), 21–40% (325 students), 41–60% (500 students), 61–80% (214 students), and the bottom 20% (78 students).

The study received approval from the Academic Ethics Committee of Liaoning Normal University. Consequently, once the subjects acknowledged the factual content and consent to participate in the survey the teacher was entrusted to distribute the survey questionnaire to the course learning group online. Before filling in the questionnaire forms, the teacher informed the participants that the rules and matters needed their substantial attention. For instance, there is a need to exercise degree judgments on a 5-point Likert scale. Similarly, participants are free to stop filling out the questionnaire at any time in case of potential mental or physical health concerns or other inability to proceed with the research survey.

Measures

Online class-related boredom

The Achievement Emotions Questionnaire (AEQ) presents a multidimensional self-report tool designed to assess the achievement emotions of college students while studying the emotions experienced by students from the standpoint of academic achievement (Pekrun et al., 2002). Primarily, AEQ gauges the discrete emotions in terms of three achievement activities, namely: class, learning, and test. Furthermore, AEQ can be employed to weigh several related emotions such as enjoyment, hope, pride, anxiety, anger, shame, hopelessness, and boredom (Pekrun et al., 2002). Moreover, the class-related Boredom Scale adopted by the researchers consists of 11 different research questions. Meanwhile, some expressions are adjusted in accordance with the context of online classrooms, such as “class” being replaced with “online class”. “I start yawning in an online class because I am so bored” is replaced with “I find this online class fairly dull”. The “translation-back translation” method is employed, in order to ensure translation accuracy. Additionally, the Likert 5-point scale is adopted to judge responses from “completely non-conformant” to “very conformant”. Reportedly, Pekrun proved that Cronbach’s alpha should be 0.93 whereas the present study recorded a Cronbach’s alpha of 0.95. The results of Confirmatory Factor Analysis show that the overall fit index of the model is suitable (χ²/df = 4.537, RMSEA = 0.052, NFI = 0.989, CFI = 0.991).

School motivation

The Inventory of School Motivation includes 8 first-order factors, which are classified into task, effort, social power, affiliation, competition, praise, social concern, and token; 4 second-order factors, including mastery, social factors, performance, and extrinsic factors (McInerney et al., 2003). In the present study, the observation item of School Motivation are chosen and adapted from Mcinerney’s Inventory of School Motivation. Similarly, a translation-back translation method is borrowed to develop a Chinese version of the scale, based on 23 items. The intrinsic school motivation is represented by task and effort; such as, “For interesting tasks, I work harder”. Contrary to this, praise and token present extrinsic school motivation; for example, “It’s important for me to get praise from my classmates for my excellent schoolwork”. Reportedly, McInerney et al., (2006) carried out a cross-cultural reliability and validity test on 697 individuals in China. The study results indicate that Cronbach’s alphas of the 4-factor dimensions of task, effort, praise, and token are recorded to be 0.55, 0.70, 0.77, and 0.72, respectively. Lastly, the Cronbach’s alpha of each factor dimension in this research is 0.92, 0.93, 0.87, and 0.83, respectively. The results of Confirmatory Factor Analysis show that the overall fit index of the model is suitable (χ²/df = 7.178, RMSEA = 0.069, NFI = 0.997, CFI = 0.998).

Academic achievement

Drawing on the practice of Lizzio et al. (2002) and other researchers, the variable of academic achievement is thoroughly denoted by indicators such as general skills and quantifiable academic performance. Among others, general skills predominantly forecast skills directly related to employment and lifelong learning, such as problem-solving, written communication, teamwork, analytical ability, and self-management skills including “online classes develop my ability to analyze problems” and “online classes develop my ability to solve problems”. Besides this, a 1–5 five-point Likert scale, ranging from “not at all” to “very much,” is employed in this study. As with the other scales, a translation-back translation method is borrowed to develop a Chinese version. At the same time, the academic achievement questionnaire includes a total of 7 items, with Cronbach’s alpha value of 0.97. The results of Confirmatory Factor Analysis show that the overall fit index of the model is suitable (χ²/df = 3.567, RMSEA = 0.045, NFI = 0.998, CFI = 0.998).

Data analysis

In the present study, the SPSS MACRO PROGRAM PROCESS is utilized for data analysis. In line with Hayes (2018), Model 4 is implemented to determine the mediating role of school motivation between online class-related boredom and academic achievement. Model 7 is employed to construct moderated mediating effect analysis. In order to describe the gender difference, the interaction effect plot is plotted based on the score of −1SD and +1 SD of online class-related boredom.

Results

Descriptive statistics and correlation analysis

Q-Q graph shows that the data basically presents a normal distribution. The correlation analysis between the variables is illustrated in Table 1. Firstly, online class-related boredom exhibits a significantly negative relationship with academic achievement (r = −0.289, p < 0.01); Secondly, extrinsic motivation demonstrates a significantly positive association with academic achievement (r = 0.613, p < 0.01). Finally, intrinsic school motivation is significantly positively related to academic achievement (r = 0.758, p < 0.01).

Table 1 Mean, Standard Deviation, Inter-Variable Correlations.
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Mediating effect analysis

Once gender, grade, and major are controlled, online class-related boredom negatively explains academic achievement, β = −0.275, p < 0.001, the model’s R2 = 0.092, ΔR2 = 0.081, F (1, 1289) = 114.28, p < 0.001. As a result, hypothesis H1 is validated in this study. In the same vein, online class-related boredom negatively correlates with intrinsic school motivation (β = −0.247, p < 0.001; R2 = 0.087, ΔR2 = 0.080, F(1, 1289) = 112.27, p < 0.001), but the negative correlation with extrinsic school motivation is insignificant (β = −0.007, p > 0.05), therefore, hypothesis 2 is partially proven in the light of derived results. Both intrinsic (β = 0.835, p < 0.001; R2 = 0.578, ΔR2 = 0.567, F(1, 1289) = 1731.04, p < 0.001) and extrinsic school motivation (β = 0.741, p < 0.001; R2 = 0.388, ΔR2 = 0.376, F(1, 1289) = 791.92, p < 0.001) positively correlate with the academic achievement.

The mediating effect was conducted using the Bootstrapping method (sample size of 5000, 95% confidence interval; Model 4; Hayes, 2018), with online class-related boredom as the independent variable, intrinsic school motivation and extrinsic school motivation as the mediator, and academic achievement as the dependent variable. Controlling for gender, grade, and major, the path coefficient results are shown in Fig. 2. The entire regression equation is significant, R2 = 0.596, F(6, 1287) = 316.06, p < 0.001. In addition, the bias-corrected percentile Bootstrap shows that the potential mediating effect of intrinsic school motivation on the correlation between online class-related boredom and academic achievement is statistically significant (Indirect effect = −0.162, Boot SE = 0.027, 95% CI = [−0.214, −0.002]). However, the mediating effect of extrinsic school motivation between online class-related boredom and academic achievement is statistically insignificant (Indirect effect = −0.001, Boot SE = 0.008, 95% CI = [−0.018, 0.014]). The results indicate that the indirect effect of the path with school motivation as the mediating variable is −0.163 (Boot SE = 0.033, 95% CI = [−0.229, −0.101]).

Fig. 2: The mediating path coefficient.
figure 2

*** Indicates that the path coefficient is significant at 0.001 level.

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Moderated mediating effect analysis

The moderated mediating effect was conducted using the Bootstrapping method (sample size of 5000, 95% confidence interval; Model 7; Hayes, 2018), with online class-related boredom as the independent variable, intrinsic school motivation and extrinsic school motivation as the mediator, gender as the moderator, and academic achievement as the dependent variable. Controlling for grade and major, the path coefficient results are shown in Fig. 3. The entire regression equation is significant, R2 = 0.593, F(5, 1288) = 375.95, p < 0.001.

Fig. 3: The moderated mediating path coefficient.
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*** Indicates that the path coefficient is significant at 0.001 level.

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Once grade and major variables are controlled, gender and online class-related boredom interaction terms exhibit a significantly negative correlation with intrinsic school motivation (β = −0.287, p < 0.001, R2 = 0.111, F(5, 1288) = 32.17, p < 0.001). Besides this, PROCESS further explored the mediating effect under different genders and inferred that the mediating effect of intrinsic motivation between online class-related boredom and academic achievement is −0.225 in female students (Boot SE = 0.030, 95% CI = [−0.286, −0.168]) and −0.037 in male students (Boot SE = 0.051, 95% CI = [−0.142, 0.057]). The derived results reveal that the mediating role of intrinsic school motivation between online class-related boredom and academic achievement is obvious only in the female group. Further indicators’ analysis illuminates that the moderating index of gender on intrinsic motivation is −0.189 (Boot SE = 0.059, 95%CI = [−0.300, −0.072]). This result indicates that a significant gender difference exists in the mediating effect of intrinsic school motivation.

The interaction term of gender and online class-related boredom presents a significantly negative association with extrinsic school motivation (β = −0.274, p < 0.001, R2 = 0.027, F(5, 1288) = 7.11, p < 0.001). Accordingly, PROCESS further scrutinized the mediating effect under different genders and reported that the mediating effect of extrinsic school motivation between online class-related boredom and academic achievement is 0.037 in the male students (Boot SE = 0.017, 95% CI = [0.009, 0.072]), and −0.021 in the female students (Boot SE = 0.010, 95% CI = [−0.043, −0.003]). The further analysis reflects that the moderating index of gender on extrinsic school motivation is −0.058 (Boot SE = 0.022, 95% CI = [−0.103, −0.020]), thereby revealing that the negative effect of online class-related boredom on academic achievement through extrinsic school motivation is more prominent among the female students.

The moderated mediating effect plot through intrinsic motivation is illustrated in Fig. 4. The moderating mediating effect is insignificant among the male students’ group (B = −0.056, t = −1.419, p > 0.05), but significant in the female student group (B = −0.344, t = −12.176, p < 0.001). Besides, a simple slope analysis indicates that the lower the level of intrinsic school motivation, the higher the level of online class-related boredom among female students.

Fig. 4
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The moderating effect of gender on the relationship between online class-related boredom and intrinsic school motivation (male students = 368, female students = 926).

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The moderating mediating effect of gender via extrinsic school motivation is illustrated in Fig. 5. Prominently, the moderating mediating effect is significant not only among the male student group (B = 0.193, t = 4.656, p < 0.001) but also among the female group (B = −0.106, t = −3.603, p < 0.001). In addition to this, the simple slope analysis posits that the greater the level of online class-related boredom in male students, the greater the degree of extrinsic school motivation. Contrarily, the higher the level of online class-related boredom in female students, the lower the extent of extrinsic motivation. Therefore, Hypothesis H3 is proven, thereby establishing that gender plays a moderating role on the mediating effect between online class-related boredom and academic achievement via school motivation.

Fig. 5
figure 5

The moderating effect of gender on the relationship between online class-related boredom and extrinsic school motivation (male students = 368, female students = 926).

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Discussion

Negative correlation between online class-related boredom and academic achievement

This study confirms Hypothesis 1 that college students’ online class-related boredom negatively correlates with their academic achievement. Specifically, we found that the higher the degree of online class-related boredom among college students, the lower their academic achievement. A longitudinal study demonstrated a similar negative impact of boredom on academic achievement among college students (Fritea & Fritea, 2013). Moreover, this relationship is echoed a study involving younger learners in primary and secondary education settings, where school-related boredom negatively correlated with academic achievement (Putwain et al., 2018). Further extending these findings to the realm of online education, such as research on online learning settings reveals that digital classroom dynamics can exacerbate feelings of disengagement and boredom, especially when interactive elements are lacking (Hollister et al., 2022). Another study indicates that interactive and engaging content can significantly mitigate boredom and improve academic outcomes in online settings (Chakraborty, Muyia Nafukho (2014)).

In addition, our conclusions are supported by recent meta-analysis examining the interaction between academic boredom and achievement in online contexts (John et al., 2020; Tze et al., 2016). These analyses confirm the robust negative influence of boredom on learning outcomes, highlighting the need for pedagogical strategies that foster engagement and interaction in online learning environments. Furthermore, the findings of this research corroborate Pekrun’s control-value theory of achievement emotions (2006), which articulates how emotions like boredom detrimentally affect academic performance by eroding motivation and impairing the strategic utilization of learning resources.

The discernible negative correlation between online class-related boredom and academic achievement emphasized in this study highlights the critical importance of developing stimulating and participatory online learning environments. This consistency across different educational levels and delivery modes suggests that addressing emotional factors such as boredom is pivotal for enhancing educational outcomes. As online education modalities continue to evolve, incorporating elements that reduce boredom could be key to enhancing academic performance.

Negative correlation between online class-related boredom and school motivation

The study partially confirms Hypothesis H2 with that online class-related boredom is significantly negatively correlated with intrinsic motivation, but not with extrinsic motivation. Although previous research on the relationship between boredom and school motivation is scarce, a study has consistently shown a negative association with intrinsic motivation (Vodanovich, 2003). This distinction aligns with the control-value theory of achievement emotions, which posits that emotions like boredom directly affect the motivational components of learning by undermining the perceived value and control over learning activities (Pekrun et al., 2010). SDT also further supports these findings by highlighting the different pathways through which intrinsic and extrinsic motivations are influenced. According to SDT, intrinsic motivation is driven by an inherent interest in the activity itself, which can be severely disrupted by the negative emotional states associated with boredom (Ryan & Deci, 2000). In contrast, extrinsic motivation, which is fueled by external rewards or obligations, might not be as directly impacted by emotional states such as boredom, suggesting a potential area for further investigation.

This study provides valuable insights for enhancing engagement in online learning environments. The differential effect underscores the importance of designing online learning environments that foster engagement and minimize boredom. By understanding the specific mechanisms between boredom and different types of motivation, educators can tailor interventions to bolster intrinsic motivation, thereby enhancing the overall learning experience. This study’s findings enrich the discourse within the SDT and control-value theoretical frameworks by elucidating how distinct types of motivation are differentially susceptible to the negative effects of boredom in online learning contexts. Moreover, this finding opens up new avenues for exploring how various aspects of online education can be optimized to mitigate the detrimental effects of boredom on school motivation.

Moderated mediating effect via gender and school motivation

Intrinsic and extrinsic school motivation are positively associated with academic achievement in online class-related learning and teaching settings. This is aligned with existing research on the relationship between intrinsic school motivation and academic achievement among college students (Simons et al., 2004; Trevino & DeFreitas, 2014). Thus, the higher the intrinsic school motivation of college students in online class teaching, the higher the amount of academic achievement. The present study replicates results reported in one of the few controlled longitudinal studies in the field (Taylor et al., 2014). Some scholars found that different extrinsic motivations have different effects on academic achievement. Students driven by autonomous extrinsic motivation (i.e., identified regulation) perform better academically, while students driven by controlled extrinsic motivation (i.e., external and introjected regulation) tend to perform poorly (Iyamuremye et al., 2023). Even one study has shown that extrinsic motivation is negatively correlated with academic achievement among college students (Areepattamannil et al., 2011). However, as research in this area deepens, the academic community has gradually embraced that intrinsic and extrinsic motivation mutually contribute to academic achievement (Marina & Lurdes, 2014; Pintrich, 2000).

Intrinsic school motivation mediates the relationship between online class-related boredom and academic achievement. This is consistent with the conclusion of the existing meta-analysis of online versus traditional classroom teaching, emphasizing the crucial role of motivation in mediating academic achievement in online settings (Means et al., 2009). However, extrinsic school motivation does not generate such an effect. Therefore, the difference between intrinsic- and extrinsic motivation in the correlation of online class-related boredom and academic achievement is further analyzed in this study. According to SDT, intrinsic motivation is derived from an internal desire to engage in an activity for its own sake, which can be significantly dampened by the experience of boredom (Ryan & Deci, 2000). Studies also indicate that boredom experienced in classes significantly undermines intrinsic motivation, subsequently diminishing academic performance among university students (Tze et al., 2016; Pekrun et al., 2002). Conversely, increases in online class-related boredom correlate with decreases in intrinsic motivation, leading to poorer academic outcomes (Vodanovich, 2003; Khan et al., 2019). Alternatively, the higher the amount of online class-related boredom, the lower the intrinsic school motivation of college students, which leads to lower academic achievement. By fostering intrinsic motivation, educators can potentially mitigate the negative consequences of boredom. This approach is consistent with Pekrun’s control-value theory of achievement emotions, which posits that the value students attach to educational activities can influence their emotional experiences and learning outcomes (Pekrun, 2006). The nuances of these motivational effects are crucial for educators to consider when designing and implementing online classes, suggesting that strategies to enhance intrinsic motivation could mitigate the adverse effects of boredom and improve educational outcomes (Martin, Parker, & Deale, 2012; Boettcher & Conrad, 2021).

The study confirms Hypothesis 3 that gender plays a moderating role in the mediating effect of school motivation between online class-related boredom and academic achievement. Notably, this effect is more pronounced among female students, where boredom significantly detracts from their academic outcomes via diminished school motivation. This study highlights that boredom from online classes leads to greater academic disengagement among females compared to males, particularly through mechanisms of extrinsic motivation. These findings resonate with earlier studies indicating that female students are more adversely affected by extrinsic stimuli (Jaradat, 2015), thus underscoring the critical role of understanding gender-specific responses to extrinsic motivation. Furthermore, it has been observed that students prone to academic boredom may opt for less rigorous learning strategies, which often leads to poorer academic performance, with notable differences across genders (Hemmings et al., 2009). While prior research has shown that male students may be more driven by extrinsic motivation (Naz et al., 2020), our findings suggest that the detrimental effects of such motivation are more acute for female students. Thus, this study not only corroborates existing theories but also expands on them by delineating how gender differences influence the correlation between online class-related boredom and academic achievement.

Conclusion

The present study establishes a significantly negative correlation between online class-related boredom and academic achievement among college students, identifying intrinsic school motivation as a mediator in this relationship. While extrinsic school motivation does not mediate this relationship, gender differences significantly influence the mediating role of school motivation, with notable variations in correlation between boredom and academic achievement across genders.

From the perspective of theoretical contributions, this study extends the control-value theory of achievement emotions and SDT by empirically examining its applicability in the context of online learning. By doing so, it not only validates the theory’s relevance to digital educational environments but also highlights the intricate dynamics between negative emotions, such as boredom, and academic outcomes. The findings confirm the pivotal role of intrinsic motivation as a buffer against the adverse effects of boredom, providing a nuanced understanding of motivational processes in online educational settings.

From the perspective of practical relevance, this study underscores the urgency for educators to proactively engage with the emotional and motivational dynamics of students in online classrooms to enhance teaching effectiveness. The following practical strategies are recommended to combat boredom and enhance engagement. Educators should incorporate real-time interactive elements, such as polls and group discussions. These practices are particularly crucial for engaging students, such as female students identified in the study, who exhibit higher levels of disengagement. The adoption of varied instructional techniques, including multimedia presentations and problem-based learning, can cater to diverse student preferences and foster intrinsic motivation. This study advocates educational strategies that prioritize emotional awareness in digital learning environments. Structured feedback mechanisms should be implemented to effectively monitor and respond to students’ emotional states, thus reducing negative emotions and enhancing the online learning experience.

The major limitations associated with this study are as follows. Firstly, in terms of the sample selection, although the purpose sampling technique is employed to cover China to a possible extent, the number of universities remains small, whereas the college level cannot cover all types, due to the limitation of sampling conditions, and demographic background differences are not fully considered. Based on this, future research studies may consider expanding the sample coverage, and fully consider demographic background variables, such as family background, socio-economic status and other psychological factors, in order to further validate the study findings. Secondly, there is also a need to adopt cross-sectional data, in order to scrutinize the potential correlation between factors. Furthermore, other factors related to online classrooms need to be further controlled, while quasi-experimental research can be attempted in future research. Thirdly, in the context of estimation tools, the online class-related boredom scale applies the portion of Pekrun’s achievement emotion questionnaire. In future research, it is crucial to construct a distinct survey tool, in order to estimate online class-related boredom. Since academic achievement is only characterized by the perceived generic skills of the students, standardized test scores can be included in future research. Finally, the mechanism of college students’ online class-related boredom to reduce extrinsic and intrinsic school motivation is still indistinct. Thus, the proposed mechanism can be thoroughly explored in the future to extend a more detailed influential mechanism and decision-making basis for educational and academic activities.