The lack of face-to-face interaction in virtual learning environments can make it difficult

The gap

Evidence profile

Sourced from the stated challenges and recommendations and future work of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 3 journals. Those papers have been cited 1 times in total.

Supporting evidence — 3 representative gaps

• Effectiveness of virtual learning system in agricultural education in India (2025) · Frontiers in Education · cited 1× · doi

  The lack of face-to-face interaction in virtual learning environments can make it difficult for students to navigate the autonomy and demands of online education. The study notes that virtual learning environments require students to have high self-regulation skills to manage their learning behaviors, emotions, and motivations. The study highlights the importance of well-structured e-learning design in enhancing the effectiveness of virtual learning.

  generalstated challengesevidence 5/5
  Keywords: lack face-to-face interaction virtual learning environments make difficult
• The Mediating Effect of Academic Buoyancy on the Causal Chains of Online Learning Readiness, Academic Motivation, and Academic Performance (2026) · Online Learning · doi

  Basic education institutions should integrate OLR assessments as part of their standard practices to help predict academic risk and personalize instructional support for students. These screenings can inform targeted interventions that address both technical and emotional aspects of learning in digital environments. To further support student success, schools should implement buoyancy-enhancing programs that build students’ capacity to manage academic stress and recover from setbacks. Interventions such as workshops on emotional regulation and peer mentoring initiatives can promote resilience and improve students’ overall engagement. Teachers also play a critical role in strengthening students’ time management and communication skills. Practical exercises, including planning logs and asynchronous discussion prompts, can be incorporated into instruction to help students better manage deadlines and Online Learning Journal – Volume 30 Issue 2 – June 2026 530 express their ideas confidently in online settings. Motivation—both intrinsic and extrinsic— should be nurtured through goal-setting activities, timely and constructive feedback, and the celebration of academic progress. These strategies can sustain students’ engagement and commitment throughout the learning process. Finally, ongoing monitoring and feedback are essential. Regular assessment of students’ readiness, buoyancy, and motivation enables teachers to proactively adapt their strategies, ensuring continuous support for students’ well-being and academic performance.

  generalrecommendationsevidence 5/5
  Keywords: students academic support learning help interventions emotional buoyancy manage engagement teachers online motivation feedback strategies
• Explaining English learning motivation in digital EFL environments through emotional intelligence, academic well-being, and perceived digital learning support (2026) · Frontiers in Psychology · doi

  that explain how psychological and contextual factors shape learning behavior and motivation. SDT proposes that motivation is strengthened when learners experience autonomy, competence, and relatedness within learning environments (Englund et al., 2023). In digital EFL settings, where learners often regulate their own learning activities, psychological resources become particularly important for maintaining engagement and persistence. Learners who possess stronger emotional competencies may be better equipped to cope with learning challenges and sustain motivation environments. Control-Value Theory further explains how emotions influence academic engagement and achievement by emphasizing learners’ perceptions of control and the value they assign to learning activities (Pekrun, 2024). According to this perspective, positive emotional experiences contribute to greater academic engagement and ELM, whereas negative emotional experiences may undermine learning outcomes. Consequently, emotional factors represent an important mechanism through which learners’ internal resources affect theoretical framework, EI represents a key personal resource that enables learners to perceive, understand, regulate, and utilize emotions effectively (Antonopoulou, 2024). Learners with higher levels of their educational experiences. Within this in technology-mediated EI are generally better able to manage academic stress, maintain positive emotional states, and respond constructively to learning difficulties. These capacities are especially important in digital learning environments, where learners often face challenges that require self-regulation and emotional adaptation. in turn, AWB refers to learners’ positive psychological functioning in educational settings, including feelings of engagement, satisfaction, emotional balance, and reduced academic stress (Huo, 2022). Drawing on SDT and CVT, emotionally intelligent learners are expected to experience higher levels of AWB because they can better regulate emotional responses and maintain positive learning experiences. Higher AWB, is expected to support stronger ELM by promoting sustained engagement and commitment to learning goals. ELM refers to the willingness, effort, and persistence that learners invest in acquiring English language skills (Wang et al., 2025a). As one of the most important predictors of language learning success, ELM influences how much learners engage in learning activities, overcome challenges, and continue pursuing language learning objectives over time. In digital EFL environments, maintaining ELM becomes particularly important because learners often have greater responsibility for directing and regulating their own learning processes. The study also incorporates PDLS as a contextual factor. SDT suggests that supportive learning environments strengthen learners’ ELM by facilitating positive learning experiences and learners satisfying important psychological needs. Accordingly, who perceive greater levels of digital support may be more likely to translate positive psychological states into sustained ELM. PDLS, therefore, represents an important environmental condition that may strengthen the relationship between AWB and ELM. Drawing on SDT and CVT, the proposed framework suggests that EI contributes to ELM both directly and indirectly through AWB, while PDLS strengthens this relationship. Together, these theoretical perspectives provide a comprehensive foundation for understanding how emotional and contextual factors jointly influence ELM in digital EFL learning environments. 2.2 Global perspective on Emotional Intelligence (EI), Academic Well-being (AWB), and English Learning Motivation (ELM)

  generalfuture workevidence 5/5
  Keywords: learning learners emotional important environments positive psychological digital engagement academic experiences motivation contextual factors often

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