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Article

Breaking the Cycle: How Fatigue, Cyberloafing, and Self-Regulation Influence Learning Satisfaction in Online Learning

by
Somya Agrawal
1 and
Shwetha M. Krishna
1,2,*
1
Department of Information Management, Chaoyang University of Technology, Taichung 41349, Taiwan
2
Department of HR, Organizational Behaviour and Communications, T A Pai Management Institute, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India
*
Author to whom correspondence should be addressed.
Educ. Sci. 2025, 15(3), 373; https://doi.org/10.3390/educsci15030373
Submission received: 22 January 2025 / Revised: 6 March 2025 / Accepted: 12 March 2025 / Published: 18 March 2025
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Abstract

:
The transition to online learning has revolutionized educational experiences while introducing new challenges, such as managing fatigue and staying focused in digital environments. This study examines the relationship between fatigue, social cyberloafing, relaxation, self-regulation, and learning satisfaction in online learning environments. Using an online questionnaire, data were collected from 146 undergraduate students studying at a private university in India. The results show that fatigue is positively related to social cyberloafing, and its impact became negative when relaxation moderated their interrelationship. Further, it was found that social cyberloafing negatively impacted learning satisfaction in students, and when self-regulation moderated this interrelationship, the negative impact of social cyberloafing on learning satisfaction was reduced. Through the lens of self-determination theory (SDT), the current paper highlights that while fatigue and cyberloafing have a negative impact on learning satisfaction, self-regulation acts as an important buffer. This study emphasizes the need to create supportive digital learning environments that address fatigue and promote self-regulation, resulting in higher learning satisfaction. This research contributes to the existing literature on digital well-being and provides actionable insights for educators and learners.

1. Introduction

For over a decade, the topic of online learning has been the central focus of higher education research. The shift to online learning has transformed higher education, offering flexibility and opportunities for engagement. While these platforms offer flexibility and convenience, they also introduce challenges such as fatigue and disengagement, which threaten students’ academic success and well-being (Rudroff, 2024). Compared to face-to-face interactive classes, students might become fatigued from constant engagement in online learning environments as it limits their physical movement and interaction, which can cause eye strain and back strain (Nesher Shoshan & Wehrt, 2022). Moreover, students often experience mental and physical fatigue from balancing academic responsibilities and constant internet use. Therefore, fatigue is the stress response from insufficient resources, resulting in tiredness and low energy (Hockey, 2013).
Studies show that fatigue can also reduce learners’ motivation and concentration, leading to counterproductive relaxation activities (Gillett-Swan, 2017). Counterproductive relaxation activities can have a complex impact on fatigue, either reducing or aggravating its effects depending on their nature and degree. For instance, habits such as excessive social media browsing or engaging in non-academic duties function as coping methods but may unintentionally impede academic performance (Akbulut et al., 2016). This fatigue, resulting from a lack of rest and excessive screen time, leads to social cyberloafing for temporary stress relief (Chen & Qin, 2024; Nweke et al., 2024). Therefore, social cyberloafing, defined as the use of online platforms for non-academic objectives while learning, is a common example of such counterproductive conduct. Some scholars consider social cyberloafing counterproductive (Lim & Teo, 2024), whereas others treat it as a restorative and pleasurable consequence. Social cyberloafing drives them to seek immediate, low-effort rewards (Andreassen et al., 2016) and is considered a way to recover from resource depletion.
While social cyberloafing can disrupt focus and group collaboration, its influence varies based on an individual’s ability to regulate themselves. Self-regulation, or the ability to monitor and manage one’s behavior, functions as a moderator in determining how much social cyberloafing influences learning satisfaction. Learning satisfaction is a significant predictor of academic success and overall well-being. It indicates whether educational activities have met students’ needs and expectations (Poedjiastutie & Oliver, 2017). Previous research shows that students who engage in social cyberloafing have lower learning satisfaction (Lim & Teo, 2024). Moreover, increased fatigue may indirectly further diminish their level of engagement in class, adversely affecting their learning satisfaction. Fatigue can influence learning satisfaction differently, depending on how students manage it. To date, only a limited number of studies have explored the indirect impact of fatigue on online learning outcomes. In this study, we aim to understand the mechanism that connects fatigue to learning satisfaction, using social cyberloafing as a mediator and relaxation and self-regulation as boundary conditions.
Self-determination theory (SDT) (Deci & Ryan, 1985) suggests that physical or mental fatigue hampers individuals’ ability to engage in self-regulated activities. This can hamper students’ competence as fatigue depletes the energy needed to focus on academic tasks (Baumeister et al., 2018). SDT emphasizes the importance of fulfilling psychological needs such as autonomy, competence, and relatedness. In online learning, fatigue depletes energy and reduces students’ capacity to meet these needs, highlighting the importance of mediating mechanisms like social cyberloafing and moderating mechanisms of relaxation and self-regulation. We focus on social cyberloafing as a mediator as it will help students deal with fatigue due to online learning. We propose relaxation as a moderating variable in the relationship between fatigue and social cyberloafing. Relaxation activities can help students recover from fatigue and help them restore their cognitive and emotional resources, whereas counterproductive relaxation activities such as binge-watching and excessive social media usage may fail to reduce the negative impact of fatigue (Mihelič et al., 2023; Nweke et al., 2024). We used self-regulation as a moderating variable in the relationship between social cyberloafing and learning satisfaction, as keeping social media usage in check requires self-regulation (Windeler et al., 2017). Although fatigue is extensively studied in organizational and student contexts, few studies examine how fatigue affects learning satisfaction in the online learning environment. This paper seeks to fill this important gap and contribute to the literature on online learning environments by examining:
  • How does fatigue influence social cyberloafing in online learning environments?
  • How does social cyberloafing mediate the relationship between fatigue and learning satisfaction?
  • What roles do relaxation and self-regulation play in moderating these relationships?
We use self-determination theory as a theoretical framework for this study as it emphasizes the factors that build or restore energy resources, focusing on activities that fulfil the needs for relatedness, competence, and autonomy. Findings from this study can guide educators in designing online courses that minimize fatigue, leverage social cyberloafing constructively, and encourage self-regulation to enhance learning satisfaction.

2. Literature Review and Hypotheses Development

This section presents the literature on all the variables. The hypothesized research model is depicted in Figure 1.

2.1. Fatigue and Social Cyberloafing

Fatigue is defined as “the physical and mental exhaustion experienced by students due to prolonged academic engagement, inadequate rest, or overwhelming tasks” (McNair et al., 1992). According to self-determination theory (SDT) (Deci & Ryan, 1985), physical or mental weariness (often termed fatigue) impairs people’s ability to engage in self-regulated, purposeful activity. This state hinders students’ ability to meet their competence needs by making them struggle to perform effectively. Fatigue depletes the energy needed to achieve competence requirements, decreasing the ability to focus on academic tasks (Baumeister et al., 2018). Ego-depletion theory (Baumeister et al., 1998) also supports this and posits that weariness depletes cognitive resources required for self-regulation, making it difficult for individuals to concentrate on academic tasks. Studies show that fatigue is a common occurrence among Indian students who are subjected to intense academic pressure and long study hours (Gull et al., 2025). Fatigue, both mental and physical, is a common problem for students combining academic duties with the continual demands of internet connectedness. It is frequently caused by a lack of rest, prolonged cognitive strain, or excessive screen time, resulting in decreased energy and less cognitive engagement (Chen & Qin, 2024). These consequences foster behaviors such as social cyberloafing, which provides temporary relief from academic stress (Nweke et al., 2024). This tiredness limits their ability to exert prolonged effort, pushing them to seek immediate pleasure, which involves little work and gives instantaneous emotional rewards (Andreassen et al., 2016). They seek rest to regain autonomy and competence, which frequently take the form of low-effort, pleasurable activities such as social media use or online chatting behaviors associated with social cyberloafing.
Social cyberloafing occurs when students use online platforms for non-educational activities during collaborative learning tasks, e.g., browsing social media or unrelated websites (Andreassen et al., 2014). SDT contends that unmet psychological demands might result in compensatory responses (Ryan & Deci, 2020). Fatigued students who are unable to satisfy their competence demands through academic accomplishment may turn to social cyberloafing as a substitute for meeting their relatedness demands. Online social connections create a sense of connection and belonging, albeit superficially, which fatigued students may find more accessible than in-person engagement or academic collaboration (Vella et al., 2019). More specifically, Indian students are raised in a collectivist culture that values interpersonal connections (A. Kaur & Noman, 2015). This phenomenon may draw them especially to social cyberloafing as a means of maintaining social bonds and reducing stress. Social media platforms, which are designed to exploit the brain’s reward systems, deliver an instant sensation of fulfilment, promoting the practice of social cyberloafing in tired students (Shuter et al., 2018). Moreover, in India, the ubiquitous availability of cell phones and internet connectivity (Doron & Jeffrey, 2013) has made cyberloafing a popular coping method. Fatigue exacerbates this habit by encouraging students to engage in low-effort online activities. This is consistent with SDT’s theory that when resources are reduced, people strive to minimize effort by prioritizing current needs over long-term aspirations (Ryan & Deci, 2020). Therefore, through the lens of SDT, the positive relationship between fatigue and social cyberloafing among Indian undergraduate students can be understood as a maladaptive response to unmet psychological needs. Therefore, we propose Hypothesis 1 (H1):
H1. 
Fatigue is positively related to social cyberloafing in students.

2.2. Social Cyberloafing and Learning Satisfaction

Social cyberloafing is a reaction to fatigue since tired students may seek short-term distractions to cope with feelings of exhaustion and stress (Wu et al., 2020). The increased availability of low-cost cell phones and data connections in India (Doron & Jeffrey, 2013) has made it all the more simple for students to view non-academic content during class. Devoting time and energy to non-academic activities can also exacerbate fatigue and interfere with the fulfillment of academic responsibilities (Pindek et al., 2018). This vicious cycle lowers the quality of academic engagement and may have a negative impact on learning satisfaction by reducing focus, productivity, and sense of accomplishment (Zhang et al., 2022). Studies have also indicated that multitasking, which is commonly triggered by technology overuse, lowers academic performance and learning satisfaction (May & Elder, 2018). Therefore, fatigue triggers social cyberloafing, which, in turn, impacts learning satisfaction by disrupting goal-oriented academic behaviors.
Learning satisfaction refers to “the extent to which students feel fulfilled, content, and positive about their educational experience” (Chou & Liu, 2005). It is influenced by multiple factors, such as cognitive, emotional, and social dynamics. Learning satisfaction is a significant predictor of academic success and well-being (Steinmayr et al., 2018). It includes students’ emotional and cognitive evaluations of their learning experiences, as well as the degree to which educational activities meet their needs, goals, and expectations. Cyberloafing reduces learning satisfaction by resulting in a fragmented learning experience (Lim & Tee, 2021). For example, students distracted by social media during lectures may miss crucial content, resulting in decreased understanding and unhappiness with their learning outcomes. The negative impact of social cyberloafing on learning satisfaction is due to a lack of meaningful engagement in academic assignments, missed learning objectives, and irritation caused by squandered time. Fatigue disrupts the demands posited in SDT (autonomy, competencies, and relatedness) by diminishing energy and focus, causing students to engage in shallow, unsatisfactory activities such as social cyberloafing (Deci & Ryan, 2016). As a result, failure to address these basic psychological demands reduces intrinsic motivation and learning satisfaction. Therefore, social cyberloafing serves as a mediation behavior, exacerbating the negative impacts of fatigue on learning outcomes. Therefore, we propose Hypothesis 2 (H2):
H2. 
Social cyberloafing is negatively related to learning satisfaction in students.

2.3. Moderating Effects of Relaxation on Fatigue and Social Cyberloafing

In the digital era, undergraduate students in India frequently experience substantial academic expectations (Muthuprasad et al., 2021), which are worsened by the widespread availability of smartphones and the Internet. Social cyberloafing becomes an easily available, if maladaptive, coping method to alleviate their tiredness (Chen et al., 2021). Fatigue, both physical and mental, has arisen as a major issue, influencing students’ behavior and coping techniques (Mehta & Parasuraman, 2014). While relaxation is a common method for alleviating fatigue, its counterproductive forms—such as excessive or poorly timed engagement with non-academic digital activities (e.g., social media browsing or gaming)—can adversely affect student outcomes (Meriac, 2012). Relaxation can be defined as “the intentional or unintentional engagement in activities that reduce stress and mental fatigue, providing a temporary break from academic or cognitive demands” (Mihelič et al., 2023; Wu et al., 2021).
Counterproductive relaxing refers to acts that are undertaken to relieve exhaustion but do not successfully replenish mental and physical energy, often resulting in a greater loss of cognitive resources (Fritz et al., 2010). Within the context of SDT, counterproductive relaxing reduces autonomy (because students feel imprisoned in repetitive, mindless habits), competence (due to missed academic chances), and relatedness (since these activities frequently foster superficial interactions) (White et al., 2021). This misalignment with intrinsic drive exacerbates the negative impacts of fatigue, increasing the need for social cyberloafing. Examples are prolonged scrolling on social media during study breaks and watching videos or playing video games during class or study time. Multitasking practices that give temporary distraction but reduce focus and long-term productivity (Lim & Teo, 2024). These activities frequently provide brief emotional relief while undermining the restorative goal of relaxation, resulting in increased fatigue and a greater proclivity for behaviors such as social cyberloafing. For instance, a study on Indian students found that excessive social media use during study breaks exacerbated fatigue and reduced academic performance. Therefore, fatigue more strongly predicts social cyberloafing because counterproductive relaxation activities fail to alleviate stress, leaving students more susceptible to distractions (Nweke et al., 2024). Therefore, we propose Hypothesis 3 (H3):
H3. 
Relaxation moderates the relationship between fatigue and social cyberloafing negatively in students.

2.4. Moderating Effects of Self-Regulation on Social Cyberloafing and Learning Satisfaction

Self-regulation, defined as the ability to manage and steer one’s behavior toward accomplishing goals, is an important skill for reducing the negative impacts of social cyberloafing (Gökçearslan et al., 2016). Self-regulated students may better control distractions, create priorities, and stay focused on academic assignments, especially when presented with the temptation of social cyberloafing (Upadhyay et al., 2024). In the context of SDT, self-regulation helps the fulfillment of psychological demands (Gupta, 2020). Self-regulation allows students to make conscious decisions about their behavior, giving them a sense of control over their academic experience (autonomy). Effective self-regulation enables students to handle academic challenges by increasing their confidence and mastery of the topic (competence) (Nilson & Zimmerman, 2013). By properly managing their time and energy, self-regulated students can participate in meaningful academic collaborations, increasing their bonds with peers and instructors (relatedness) (Wilson & Narayan, 2016). Therefore, self-regulation moderates the interrelationship between social cyberloafing and learning satisfaction by allowing students to reduce the disruptive effects of social cyberloafing. Students with strong self-regulation abilities are more likely to limit their time and frequency of social cyberloafing, using it strategically as a temporary respite rather than a long-term distraction (DiDonato, 2013). This limited use of social cyberloafing can help students recharge without negatively impacting their academic performance or satisfaction (Aagaard, 2015). Self-regulation is especially crucial for Indian undergraduate students as they try to balance the demands of a tough academic environment with the pervasive availability of digital distractions. These individuals’ strong self-regulation allows them to stay focused on intrinsic goals and link their behaviors with their long-term goals.
Previous research also shows that self-regulation improved academic achievement and satisfaction by allowing students to better manage their time and effort. Elizondo et al. (2024) also emphasized the significance of self-regulation in goal planning, progress tracking, and sustaining focus, all of which are essential for reducing the negative impacts of social cyberloafing. Within the Indian context, P. Kaur et al. (2018) found that students with stronger self-regulation skills had better academic performance and were more satisfied with their learning experience, even in circumstances with significant digital distractions. The Indian educational system places a high value on academic performance and societal approbation, putting enormous pressure on students. In such a high-pressure atmosphere, self-regulation is critical for sustaining learning satisfaction. Students who can control their cyberloafing behavior are better suited to deal with these challenges while remaining on track with their academic goals (Parikh et al., 2019). Furthermore, culturally established ideals of discipline and self-control are consistent with SDT’s concepts of autonomy and competence, highlighting the significance of self-regulation in academic success (Reeve et al., 2012). Thus, counterproductive relaxation significantly moderates the fatigue–social cyberloafing relationship among Indian undergraduate students. Failing to meet the psychological demands described in SDT increases reliance on social cyberloafing, lowering academic achievement and satisfaction. Therefore, we propose Hypothesis 4 (H4):
H4. 
Self-regulation moderates the relationship between social cyberloafing and learning satisfaction positively in students.

3. Methodology

Data for this study were collected one time from undergraduate students through an online survey using a convenience sampling technique. The participants were enrolled in courses like corporate governance, entrepreneurship development, human resource management, and organizational behavior in the fall semester of 2021 at a large private university in India. The study was administered between October and November 2021. This survey is part of a broader research project, and not all survey variables are included in this study. Among 146 respondents, 50.7% were male, and 49.3% were female. The age of the participants varied between 17 to 23, with an average age of 19.1 years. The questionnaire consisted of two parts. The first part consisted of demographic variables such as age, gender, and department/program. The second part of the questionnaire consisted of 20 questions related to “Fatigue”, “Social cyberloafing”, “Learning satisfaction”, “Relaxation”, and “Self-regulation”.

3.1. Variables and Measures

All the variables except fatigue were measured on a five-point Likert scale ranging from 1 = Strongly disagree to 5 = Strongly agree. Fatigue was measured using another five-point Likert scale, where 1 = Never and 5 = Always.

3.1.1. Fatigue

A four-item scale (Cronbach’s α = 0.845) was adapted from Park and Sprung (2015) to measure this variable. The students were required to rate statements such as “Rate how often you feel exhausted after a day of online classes”.

3.1.2. Social Cyberloafing

The variable of social cyberloafing was measured using four items (Cronbach’s α = 0.85) adapted from Andreassen et al. (2014). The students were required to rate statements such as “I cannot resist using social media to follow current events during class hours”.

3.1.3. Learning Satisfaction

Learning satisfaction was measured on a four-item scale (Cronbach’s α = 0.893) adapted from Chou and Liu (2005). The students were required to rate statements such as “I am satisfied with the instruction model”.

3.1.4. Relaxation

Relaxation was measured using a four-item scale (Cronbach’s α = 0.909) adapted by Wu et al. (2021). The students were required to rate statements such as “I relax via the Internet”.

3.1.5. Self-Regulation

We used a scale adapted from Gökçearslan et al. (2016) to measure self-regulation, which consists of four items (Cronbach’s α = 0.738). The students were required to rate statements such as “I can concentrate on one activity for a long time, if necessary”.

3.2. Analytical Approach

This study used structural equation modeling to examine the hypothesized model. A two-step analytical strategy was adopted: first, the measurement model was confirmed using confirmatory factor analysis; then, the structural equation model was used to estimate the fit of the hypothesized model. Procedural remedies and statistical methods suggested by Podsakoff et al. (2024) were used to reduce and assess the level of common method variance in cross-sectional data. Survey participants were informed about the purpose of the survey and guaranteed anonymity and confidentiality of the data. Harman’s one-factor test was conducted, and the results show that five distinct factors emerged with a cumulative variance of 71%, with the first factor accounting for 15.9% of the variance, suggesting that no single factor dominates, nor does any single factor account for the majority of the variance, suggesting a low likelihood of common method variance.
SEM was used to examine the direct effect of fatigue on social cyberloafing (Hypothesis 1) and social cyberloafing on learning satisfaction (Hypothesis 2). The advantage of SEM lies in its ability to test an entire system of variables simultaneously within a hypothesized model, allowing for an assessment of model-data fit (Byrne, 1994). Researchers (e.g., MacKinnon et al., 2002) have suggested that a simultaneous test of the significance of both the path from an initial variable to a mediator and the path from the mediator to an outcome, as implied in SEM and consistent with our direct and indirect predictions, provides the best balance of Type I error rates and statistical power.
Hierarchical multiple regression was used to examine the role of relaxation as a moderator of the relationship between fatigue and social cyberloafing and role of self-regulation as a moderator of the relationship between social cyberloafing and learning satisfaction. Hierarchical regression is particularly useful for testing interaction effects as it enables researchers to determine the order of variable entry based on causal priority (Cohen et al., 2003). To mitigate multicollinearity, all interaction variables were mean-centered. By integrating SEM and hierarchical regression, we leverage the strengths of both methods, i.e., SEM’s capability to model complex relationships within a structured framework and hierarchical regression’s ability to assess interaction effects systematically.

3.3. Data Analysis and Results

To validate construct measures, we used Confirmatory Factor Analysis (CFA), which confirms whether the construct measures the load on the respective constructs (Hair et al., 2010). The results of the confirmatory factor analysis are presented in Table 1.
Table 2 provides details of descriptive statistics and correlation of the study variables. Results show that gender has significant negative correlations with fatigue (r = −0.281, p < 0.01) and social cyberloafing (r = −0.281, p < 0.01). Fatigue correlates positively with relaxation (r = 0.181, p < 0.05) but negatively with learning satisfaction (r = −0.293, p < 0.01). Social cyberloafing is positively correlated with fatigue (r = 0.181, p < 0.05) and relaxation (r = 0.391, p < 0.01), while negatively correlated with learning satisfaction (r = −0.313, p < 0.01). Self-regulation positively correlates with learning satisfaction (r = 0.218, p < 0.01). Relaxation is positively associated with fatigue (r = 0.181, p < 0.05), social cyberloafing (r = 0.391, p < 0.01), and self-regulation (r = 0.191, p < 0.05). Additionally, learning satisfaction has a significant positive correlation with self-regulation (r = 0.218, p < 0.01) and negative correlations with fatigue (r = −0.293, p < 0.01) and social cyber loafing (r = −0.313, p < 0.01).

3.4. Measurement Model

The measurement model’s fit indexes in Table 3 support examining the structural model (χ2/DF = 1.536, p ≤ 0.001; CFI 0.967, GFI = 0.22, SRMR = 0.0509, RMSEA = 0.068). The results indicate that the proposed model fits the data well (χ2/DF = 1.662, p ≤ 0.001; CFI = 0.959, GFI = 0.915, SRMR = 0.086, RMSEA = 0.068).

3.5. Structural Model

Table 3 provides all the model fit indexes. Figure 2 displays the overall structural model with path coefficients. H1 states that fatigue is positively related to social cyberloafing. Results support this hypothesis (β = 0.242, p ≤ 0.01). Similarly, H2, which states that social cyberloafing is negatively related to learning satisfaction, is also supported (β = −0.362, p ≤ 0.001).

3.6. Hierarchical Multiple Regression Analysis

Table 4a,b provide the hierarchical multiple regression results. H3 argues that relaxation interacts significantly with fatigue to negatively influence social cyberloafing. The result supported this argument (β = −0.223, p ≤ 0.01). The plot in Figure 3a suggests that relaxation had a more negative relationship with social cyberloafing when the level of relaxation was higher compared to when the level of relaxation was lower.
Hypothesis 4 states that self-regulation interacts with social cyberloafing to influence learning satisfaction; in line with this, we found that self-regulation interacted with social cyberloafing to positively influence learning satisfaction (β = 0.240, p ≤ 0.01). The plot in Figure 3b suggests that self-regulation positively affects learning satisfaction when the level of self-regulation is higher compared to when the level of self-regulation is lower.

4. Discussion

Results show that fatigue is positively related to social cyberloafing in students, providing support for H1. Previous studies show that lack of leisure time, lack of sleep, and academic expectations can all contribute to students’ fatigue (Vansoeterstede et al., 2024). Fatigue has a major negative impact on cognitive and emotional self-regulation, which makes it harder to concentrate and more likely to become distracted. It reduces the cognitive resources needed for self-control, increasing the likelihood that people may give in to impulsive actions, according to the ego depletion theory (Baumeister et al., 1998). Long-term exhaustion lowers students’ self-control and motivation for meaningful activities, such as academic engagement during classes. Social media and other online platforms offer quick and low-effort ways to alleviate stress (Maciejewski & Smoktunowicz, 2023). As a result, they turn to less demanding online social activities for instant gratification (Lin et al., 2021). Academic stress among Indian students is well-documented (Deb et al., 2014). India has a high rate of student fatigue because academic success is frequently valued more highly than overall health (Malik et al., 2020). Students’ intrinsic drive for academic work is not just undermined by this fatigue, but it also makes social cyberloafing seem like a more appealing way to meet unfulfilled psychological demands.
Due to strict academic schedules, parental expectations, and cultural norms that place a strong emphasis on conformity, Indian undergraduate students frequently feel limited autonomy. This lack of autonomy is made worse by fatigue, which increases the likelihood that students would resort to social cyberloafing in an attempt to regain some control over their time and behavior (Wielenga-Meijer et al., 2012). Students may feel less competent and less able to function academically when they are exhausted. They turn to low-effort, socially engaged online activities that offer them immediate reinforcement and a false sense of competence through likes and comments as a result of this aggravation (Deci & Ryan, 2016). Social cyberloafing, in spite of its maladaptive nature, provides a virtual platform for peer connections, satisfying students’ demand for relatedness. Moreover, fatigued students may put relatedness above academic performance in a collectivist country like India, where interpersonal relationships are highly prized, which would further encourage the habit of cyberloafing (Pérez-Juárez et al., 2023).
Also, Indian society emphasizes collectivism, and coping strategies heavily rely on interpersonal interactions (Kanth et al., 2024). Students may use social contacts, such as group discussions or online chat, to feel emotionally supported when they’re tired. This is consistent with research showing that social media use for emotional regulation may be increased by exhaustion (Andreassen et al., 2014). As a result, social cyberloafing can be used to stay in touch with friends and escape from the demands of school. Therefore, a complex interaction between cognitive constraints, cultural influences, and technical factors accounts for the positive link between fatigue and social cyberloafing among Indian undergraduate students.
H2 examined the interrelationship between social cyberloafing and learning satisfaction. We found support for this hypothesis. According to SDT, learning satisfaction arises when students’ psychological needs are met (Deci & Ryan, 2016). Social cyberloafing disrupts these needs, reducing students’ intrinsic motivation and overall satisfaction with their learning experience (Karaoglan Yilmaz et al., 2024). At first, students might view social cyberloafing as an independent way to take back control of their time. Still, it frequently leads to shame and a loss of control over academic priorities when it becomes a habit. Students’ autonomy satisfaction declines with time as they feel less equipped to make significant academic decisions (Durak, 2020). This annoyance is made worse for Indian students, whose learning environments are frequently defined by structured and competitive frameworks. Social cyberloafing takes time and effort away from schoolwork, which results in subpar academic performance and a lessened sense of achievement.
Cognitive load theory (Sweller, 1994) states that learning necessitates certain cognitive resources. Due to their increased cognitive load from trying to multitask, students who engage in social cyberloafing have a harder time understanding and remembering academic material. Those who are less satisfied with their educational experiences also have lower levels of academic engagement (Junco, 2012). Undergraduate education in India frequently places a strong emphasis on demanding coursework and test-focused methods. According to Singh (2021), students who cyberloaf during lectures or group projects may find it difficult to keep up, which could lead to discontent with their academic performance and perceived learning results.
According to Deci and Ryan (2016), students frequently believe that they fall short of academic expectations, which undermines their sense of competence. This dissatisfaction is especially significant in India’s fiercely competitive academic environment, where achieving academic achievement is directly linked to one’s sense of value and social acceptance (Yadav & Mishra, 2017). Social cyberloafing may temporarily satisfy students’ demand for relatedness by giving them the chance to interact with classmates virtually, but these exchanges frequently fall short of the depth and caliber needed to create lasting bonds. Additionally, excessive participation in online social activities might cause kids to feel isolated in the classroom by alienating them from their teachers and friends (Khaskheli et al., 2024).
Undergraduate students in India frequently study under a system that prioritizes academic rigour and outside assessments above independent study. This setting makes learning satisfaction more dependent on intrinsic motivation. However, by substituting extrinsic and surface-level rewards, like likes and comments on social media, for intrinsic drive, social cyberloafing reduces it. As a result, students are less engaged, have less meaningful academic exchanges, and are generally less satisfied with their educational experience. (Shuter et al., 2018). Therefore, social cyberloafing negatively impacts learning satisfaction among Indian undergraduate students by frustrating their psychological needs for autonomy, competence, and relatedness.
Past studies show that fatigue, a state of mental and physical exhaustion, is a well-documented antecedent of social cyberloafing (Lim & Teo, 2024). However, relaxation—i.e., a state of rest and psychological recovery—acts as a moderator, weakening the positive relationship between fatigue and social cyberloafing. We found support for this hypothesis (H3). Although relaxation can lessen the consequences of exhaustion, not all types of relaxation are advantageous (Oravec, 2019). For instance, counterproductive relaxation, characterized by passive or escapist activities that fail to restore energy or psychological resources, weakens the interrelationship between fatigue and social cyberloafing. However, its negative impacts warrant examination through the lens of self-determination theory (SDT). Activities such as excessive binge-watching, mindless scrolling on social media, or other low-effort, nonrestorative behaviors (Chaudhary et al., 2022) provide temporary relief from fatigue but fail to fulfill the core psychological needs—autonomy, competence, and relatedness—central to SDT (Deci & Ryan, 1985). Therefore, instead of effectively mitigating fatigue, counterproductive relaxation often substitutes one maladaptive behavior (i.e., fatigue-driven cyberloafing) for another.
Students believe that they are choosing to participate in leisure activities; however, counterproductive relaxing may give them a false sense of autonomy. These behaviors’ escapist and passive nature erodes genuine volitional control and intensifies helplessness. Therefore, students’ capacity to fight fatigue is weakened by this unrealized autonomy, which makes it harder for them to avoid social cyberloafing (Sonnentag, 2012). In order to escape academic assignments that they feel are too difficult, exhausted students frequently resort to counterproductive relaxation techniques. These pursuits offer instantaneous but fleeting satisfaction, momentarily deflecting attention from exhaustion without tackling its underlying source. As a result, students continue to feel less competent, which keeps them using social cyberloafing as an additional avoidance strategy (Deci & Ryan, 2016). Counterproductive relaxation, especially on social media, frequently consists of shallow exchanges that do not offer genuine connection. Even while worn out, students might want to interact with others; the transient nature of these virtual interactions makes them feel alone and unfulfilled. The cycle of exhaustion and cyberloafing is sustained by this absence of true relatedness (Chen et al., 2021).
Moreover, students in India experience chronic fatigue as a result of the tremendous pressures placed on them by their families and society (Shuter et al., 2018). Also, digital distractions are so easily accessible that counterproductive relaxing is especially common. As a coping strategy, students could, for instance, watch brief films or browse social media. However, these activities are less successful in breaking the fatigue–cyberloafing loop since they frequently exacerbate exhaustion by decreasing sleep quality and increasing mental clutter (Durak, 2020).
Studies show that social cyberloafing, or engaging in non-academic online social activities during learning time, often has a negative impact on learning satisfaction (Zhang et al., 2022). Nonetheless, this association can be favorably moderated by self-regulation, which is the capacity to manage one’s thoughts, feelings, and actions in accordance with objectives. We also found support for this hypothesis (H4). Learning satisfaction happens when students’ psychological needs for autonomy, competence, and relatedness are fully met (Deci & Ryan, 1985). Social cyberloafing, however, tends to undermine these needs. For instance, frequent distractions from social media diminish the perception of being in control of one’s academic actions (autonomy). Second, the time spent on non-academic tasks detracts from opportunities to develop academic mastery, leading to feelings of inadequacy (competence). Third, social cyberloafing may provide superficial online connections but often hinders meaningful engagement in academic communities (relatedness). These factors collectively lower learning satisfaction (Karaoglan Yilmaz et al., 2024). However, the results show that self-regulation can counteract these negative outcomes by enabling students to engage in cyberloafing in a balanced and intentional manner.
Self-regulation enables students to manage their cyberloafing behaviors in a way that aligns with their academic goals. Instead of utilizing cyberloafing as an avoidance strategy, self-regulated individuals are better at establishing boundaries and purposefully using it as a brief respite to refuel (Kwala et al., 2024). They satisfy the autonomy requirement by maintaining a sense of control over their academic behaviors through intentional decision-making (Elizondo et al., 2024). This sense of independence is especially beneficial for Indian students, who frequently face academic pressures from outside sources. Students can prevent cyberloafing from interfering with their academic output by limiting the amount of time and frequency they spend doing it (Simanjuntak et al., 2022). They might even include cyberloafing activities into their scholastic pursuits, such as peer collaborations or online conversations. By using cyberloafing strategically, perceived competence is kept from declining and occasionally even increased (Shuter et al., 2018). Even when cyberloafing, self-regulated students are more likely to have meaningful social connections, which meets their relatedness demands without compromising their academic attention. To transform possible diversions into productive connections, individuals could, for example, use online platforms to communicate with peers regarding common academic interests (Ryan & Deci, 2020).
The capacity for self-control becomes essential in the academic setting of India, which is marked by strict curricula and fierce rivalry. Students frequently struggle to balance the demands of constant digital distractions with maintaining strong academic achievement (Tamilarasi, 2023). By striking a balance between their long-term academic objectives and their need for temporary solace (through cyberloafing), self-regulation can enable students to successfully negotiate this environment. Even in an atmosphere where technology is pervasive, Indian students who possess greater self-control are better equipped to use cyberloafing positively and maintain their learning satisfaction.

4.1. Theoretical Implications

This study investigates the relationship between fatigue, relaxation, social cyberloafing, self-regulation, and learning satisfaction among Indian students using self-determination theory (SDT). This study contributes to the SDT literature by illustrating how external and internal factors (fatigue, relaxation, social cyberloafing, and self-regulation) interact to influence satisfaction with learning outcomes in students. It expands on SDT by investigating the dual moderating functions of relaxation and self-regulation, emphasizing how these dimensions modulate and buffer the effects of fatigue on learning satisfaction. Fatigue appears as a significant barrier to meeting the fundamental psychological demands of competence, autonomy, and relatedness. High fatigue reduces cognitive and emotional engagement, limiting students’ ability to find satisfaction in their learning activities (Ilies et al., 2015).
This study identifies relaxation as a new moderating factor that exacerbates the deleterious impact of fatigue on learning satisfaction. Counterproductive activities (for example, excessive reading of social media, or gaming) serve as maladaptive coping methods that, while temporarily easing stress, undermine students’ motivation and distract them from reaching significant academic goals (Elhai et al., 2019). The findings, which situate social cyberloafing within collaborative learning environments, reveal that social cyberloafing practices degrade a sense of relatedness and shared accountability, both of which are important components of SDT (Deci & Ryan, 2016). The study also confirms social cyberloafing as a fatigue-induced phenomenon and demonstrates its indirect impact on learning satisfaction via group dynamics. Lastly, self-regulation mitigates the negative impacts of fatigue and social cyberloafing on learning outcomes by allowing students to align their habits with long-term academic goals (Nweke et al., 2024). This emphasizes the importance of volitional control and persistence in maintaining motivation under pressure, providing a nuanced view of self-regulation’s role in SDT.

4.2. Practical Implications

SDT posits that students engage in maladaptive online social activities when their autonomy, competence, and relatedness demands are not met due to exhaustion (Ryan & Deci, 2020). Addressing these underlying needs through supportive academic methods may mitigate cyberloafing and improve overall student well-being. They should implement focused measures to combat fatigue, such as mindfulness workshops, flexible deadlines, and supportive academic practices (Palalas et al., 2020). The universities could promote flexible learning schedules to enhance autonomy (Huang et al., 2020). This could help monitor the fatigue–social cyberloafing relationship by creating a learning environment that meets students’ psychological demands. Moreover, recognizing and reducing fatigue might help students better align with their natural motivation. The teachers could encourage students to participate in class activities that build competence through incremental challenges (Neo, 2003). They could encourage collaborative projects and mentor-mentee partnerships to make meaningful connections between peers and instructors. This would create opportunities for healthy social interactions to meet relatedness needs in more constructive ways. By integrating these strategies into pedagogy, educators can reduce fatigue and mitigate the tendency of students to engage in social cyberloafing.
The educators could also consider designing organized collaborative assignments that promote accountability, which can help to reduce social cyberloafing. Platforms that promote transparent progress tracking in group initiatives can also reduce disengagement and restore a sense of shared purpose (Glassman et al., 2015). Including self-regulation training in the curriculum (for example, goal-setting workshops and reflective journaling) can help students stay motivated in the face of adversity. Technology-based tools, such as gamified apps for time management and focus that provide immediate feedback, could help create a sense of achievement, enhancing self-regulation performance (Li et al., 2022). Indian students frequently confront distinct sociocultural constraints (e.g., household expectations and society’s emphasis on academic achievement) (Cherian & Irudaya Rajan, 2024). Universities should adjust treatments to these realities, addressing emotional and psychological demands alongside intellectual objectives. The universities can leverage technology to build interesting and rewarding learning environments, such as adaptive learning platforms that are tailored to student’s specific needs and reduce fatigue by optimizing workload (Iqbal, 2023). Lastly, the universities should also create awareness programs about the effects of cyberloafing and implement strategies, such as structured online activities and digital well-being programs, to mitigate its impact (Khansa et al., 2018).

4.3. Limitations and Future Directions

This research has a few limitations, which should be noted. First, the data are cross-sectional, which makes it challenging to understand the effect of fatigue on student learning satisfaction. Future research could benefit from longitudinal, time-lagged, or experiential sampling, which would provide a better understanding of the interplay between variables. Participants of this study were students from a single private university in India. Even though students have diverse backgrounds, this limits the generalizability of the findings. Future studies with students from different university settings and other cultural backgrounds would increase the external validity of the results. Third, the study focuses on social cyberloafing as a recovery experience but does not differentiate between the various purposes for which cyberloafing may be used. Future research could explore different types of social cyberloafing behaviors as potential mediators in the relationship between fatigue and learning satisfaction. Lastly, while this study examines relaxation and self-regulation as moderators, it does not consider other potential moderators, such as guidance from peers or teachers. Future studies could investigate the role of peer or teacher support in reducing the effects of fatigue from online learning.

5. Conclusions

Through the lens of SDT, the current paper highlights the positive relationship between fatigue and social cyberloafing among Indian students, which can be seen as a maladaptive response to unfulfilled psychological demands. Fatigue undermines self-regulation and competency, prompting students to seek quick comfort through online social activities. These activities, while briefly satisfying the relatedness demand, do not address underlying requirements for autonomy and competence, sustaining a cycle of academic disengagement.
We found that relaxation (counterproductive) moderates the relationship between fatigue and social cyberloafing negatively by giving brief respite from exhaustion while failing to meet the basic psychological needs indicated in SDT. For Indian college students who frequently work in high-pressure academic contexts, counterproductive relaxing provides a simple but ultimately inadequate coping method. By raising awareness of and providing access to restorative forms of relaxation, universities can help students break the fatigue–cyberloafing cycle and improve their general well-being.
The findings show that social cyberloafing has a detrimental influence on learning satisfaction because it disrupts engagement, reduces collaborative learning experiences, and hinders academic success. To address this issue, institutions must raise awareness about the consequences of cyberloafing and establish ways to lessen its impact on learning outcomes.
The results also show that self-regulation moderates the interrelationship between social cyberloafing and learning satisfaction. This is especially relevant for Indian college students as they have to navigate a high-pressure academic atmosphere. Here, self-regulation can be used as an effective strategy to combine leisure and academic involvement. Teachers and educational institutions can assist students in turning the potential negatives of social cyberloafing into opportunities for long-term learning fulfilment by developing self-regulation abilities.

Author Contributions

Conceptualization, S.M.K. and S.A. Methodology, S.M.K. Software, S.M.K. Validation, S.A. Formal analysis, S.M.K. Writing—original draft, S.A. Writing—review and editing, S.M.K. and S.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study because the collected data does not include any sensitive information about the participants. Moreover, the data collection procedure did not involve any risk of discomfort or inconvenience to participants, nor did it involve any risk of psychological distress to participants or their families. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Participation in this study was voluntary. Those who agreed to participate were ensured that their information and responses would be kept confidential and solely used for research purposes. As described in 45 CFR 46.101(b) Categories of Exempt Human Subjects Research, cross-sectional survey-based research, such as the current one, is usually exempt from the Institute Ethics Committee’s clearance. Similar exemptions are mentioned in one university document in India (Page number 23—in IEC). You can find the blank form here: https://forms.gle/tAft726NYW3SYAtn7.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Education 15 00373 g001
Figure 1. Hypothesized framework.
Figure 1. Hypothesized framework.
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Figure 2. SEM model with results of mediation analysis. Note: * p < 0.05; ** p < 0.01; *** p ≤ 0.001.
Figure 2. SEM model with results of mediation analysis. Note: * p < 0.05; ** p < 0.01; *** p ≤ 0.001.
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Education 15 00373 g003aEducation 15 00373 g003b
Figure 3. Moderating effects.
Figure 3. Moderating effects.
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Table 1. Results of Confirmatory Factor Analysis.
Table 1. Results of Confirmatory Factor Analysis.
ConstructItemFactor LoadingAVECR
Social Cyber loafingSCL10.8300.6910.9
SCL20.819
SCL30.809
SCL40.867
Learning satisfactionLS10.8140.7580.926
LS20.915
LS30.875
LS40.876
FatigueFTG10.8080.6570.884
FTG20.826
FTG30.846
FTG40.759
RelaxationREL10.8290.7860.939
REL20.892
REL30.917
REL40.905
Self-regulationSER10.7670.5650.839
SER20.700
SER30.753
SER40.785
Table 2. Means, standard deviations, and correlations.
Table 2. Means, standard deviations, and correlations.
VariableMeanSD1234567
Age19.181.021
Gender1.490.50−0.275 **1
Fatigue3.670.81−0.0690.0581
Social Cyber Loafing2.890.87−0.070−0.281 **0.181 *1
Self-regulation3.710.680.026−0.101−0.0960.0791
Relaxation3.290.87−0.154−0.1430.181 *0.391 **0.191 *
Learning satisfaction3.060.840.1490.071−0.293 **−0.313 **0.218 **−0.047
** Correlation is significant at the 0.01 level (two-tailed). * Correlation is significant at the 0.05 level (two-tailed).
Table 3. Summary of model fit indices.
Table 3. Summary of model fit indices.
Model Testχ2dfSRMRCFIGFIRMSEA
Independence model901.87466
Measurement model78.314510.05090.9670.9220.061
Hypothesized model86.437520.08650.9590.9150.068
Table 4. Results of multiple regression analysis.
Table 4. Results of multiple regression analysis.
Model 1Model 2Model 3
(a) Moderation effect of relaxation on the relationship between fatigue and social cyberloafing
Control variables
Age−0.136 *−0.073−0.100
Gender−0.562 ***−0.462 ***−0.475 ***
Independent variables
Fatigue 0.144+0.128
Relaxation0.314 ***0.343 ***
Interaction effects
Fatigue × Relaxation −0.223 **
R20.1020.2290.264
F8.136 ***10.453 ***10.023 ***
ΔR2 0.1270.035
(b) Moderation effect of self-regulation on the relationship between social cyberloafing and learning satisfaction
Control variables
Age0.150 *0.1100.132 *
Gender0.2020.0750.141
Independent variables
Social cyberloafing −0.299 ***−0.304 ***
Self-regulation0.298 **0.302 ***
Interaction effects
Social cyberloafing × self-regulation 0.240 **
R20.0360.1730.214
F2.6467.374 ***7.626 ***
ΔR2 0.1370.041
Notes: n = 146. Values are standardized coefficients, with standard errors in parentheses. (a) Social cyberloafing is the dependent variable; (b) learning satisfaction is the dependent variable; * p < 0.05; ** p < 0.01; *** p < 0.001.
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Agrawal, S.; Krishna, S.M. Breaking the Cycle: How Fatigue, Cyberloafing, and Self-Regulation Influence Learning Satisfaction in Online Learning. Educ. Sci. 2025, 15, 373. https://doi.org/10.3390/educsci15030373

AMA Style

Agrawal S, Krishna SM. Breaking the Cycle: How Fatigue, Cyberloafing, and Self-Regulation Influence Learning Satisfaction in Online Learning. Education Sciences. 2025; 15(3):373. https://doi.org/10.3390/educsci15030373

Chicago/Turabian Style

Agrawal, Somya, and Shwetha M. Krishna. 2025. "Breaking the Cycle: How Fatigue, Cyberloafing, and Self-Regulation Influence Learning Satisfaction in Online Learning" Education Sciences 15, no. 3: 373. https://doi.org/10.3390/educsci15030373

APA Style

Agrawal, S., & Krishna, S. M. (2025). Breaking the Cycle: How Fatigue, Cyberloafing, and Self-Regulation Influence Learning Satisfaction in Online Learning. Education Sciences, 15(3), 373. https://doi.org/10.3390/educsci15030373

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