The increasing prevalence of social media (SM) and its widespread use among students has prompted research into its impact on the educational environment. While educators are eager to understand SM's potential in education, definitive conclusions regarding its suitability remain elusive. Prior studies have primarily focused on the factors influencing SM adoption and use in educational contexts, examining motivations and the influence of various elements on educational SM usage. Educational SM use involves the deliberate integration of SM platforms and tools into teaching to enhance the learning experience, leveraging SM's communicative and collaborative potential to foster active learning and knowledge acquisition. This integration, however, requires careful consideration of factors like creating supportive learning environments and addressing privacy concerns. Previous research in Saudi Arabia has largely concentrated on the motivations and behaviors associated with SM use, with some studies exploring students' attitudes towards SM in blended learning and its acceptance for educational purposes. Inconsistencies exist in the literature regarding SM's effect on learning outcomes, with some studies suggesting positive impacts on academic achievement while others report negative effects or no impact at all. Many studies have overlooked the mediating role of variables such as affective learning engagement and the moderating roles of factors like cyberbullying and cyberstalking. This study aims to address these limitations by investigating the moderating effects of affective learning involvement and instructional SM use on students' satisfaction and learning performance, clarifying the complex relationship between SM use and its outcomes.

The literature review extensively covers existing research on social media use in education, highlighting inconsistencies in findings regarding its impact on student learning outcomes. Studies using various platforms like Facebook, Twitter, and WhatsApp have been examined, with some showing positive correlations between SM use and academic performance, while others show negative correlations or no effect. The role of cultural norms in shaping SM use and its potential negative impacts on mental health have also been considered. The importance of mediating variables, like affective learning engagement and educational SM use, in understanding the relationship between SM use and learning outcomes has been emphasized, as well as the need to consider moderating factors such as cyberbullying and cyberstalking. The review also introduces Self-Determination Theory (SDT), emphasizing its relevance to understanding student motivation, engagement, and well-being. SDT's focus on the basic psychological needs of autonomy, competence, and relatedness, and their impact on intrinsic motivation, is highlighted. The literature review shows that fulfilling these needs through effective learning and the appropriate use of social media platforms has the potential to enhance student motivation and learning outcomes. Additionally, the review highlights existing research on the role of trust and organizational factors in fostering knowledge sharing and collaborative learning through social media in education.

This quantitative study employed a questionnaire survey to gather data from 293 undergraduate students at King Saud University in Saudi Arabia during the summer semester of 2022. Convenience sampling was used. The questionnaire included measures of perceived competence, autonomy, and relatedness (adapted from Ryan & Deci, 2000; Sørebø et al., 2009; Sun et al., 2019; Zhao et al., 2011), affective learning involvement, information sharing, collaborative learning environment, and educational SM use. Each construct was measured using five items on a five-point Likert scale. Data analysis involved descriptive statistics using IBM SPSS 26, followed by partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.3.3. The PLS-SEM analysis assessed the measurement model's reliability and validity through convergent validity (average variance extracted, AVE), discriminant validity (Fornell-Larcker criterion, heterotrait-monotrait ratio of correlations, HTMT), and internal consistency reliability (Cronbach's alpha, composite reliability). The structural model was evaluated for multicollinearity (variance inflation factor, VIF) and model fit (SRMR, RMSEA, Chi-square, degrees of freedom, ChiSqr/dF, NFI, and CFI). Hypotheses were tested using a one-tailed t-test with bootstrapping.

The PLS-SEM analysis revealed strong convergent and discriminant validity for all constructs, with AVEs exceeding 0.5 and HTMT values below the recommended threshold. Reliability was also high, with Cronbach's alpha and composite reliability values exceeding 0.7. Multicollinearity was not a significant issue. Model fit indices indicated a good fit. All 16 hypotheses were supported. Specifically, perceived competence, autonomy, and relatedness positively influenced both affective learning involvement and educational SM use. Information sharing and a collaborative learning environment also positively impacted both variables. Affective learning involvement positively influenced student satisfaction and learning performance. Educational SM use positively influenced affective learning involvement, student satisfaction, and learning performance. Finally, student satisfaction positively influenced learning performance. The findings showed that perceived competence, autonomy, and relatedness significantly influence affective learning engagement and educational SM use. Information sharing and collaborative learning environments also significantly affect these variables. Affective learning engagement significantly impacts student satisfaction and learning performance, and educational social media use has a significant positive influence on student satisfaction and learning performance.

The findings highlight the crucial role of self-determination theory (SDT) in understanding students' engagement with social media in educational settings. The study demonstrates that fostering feelings of competence, autonomy, and relatedness is key to enhancing affective learning involvement and promoting the effective use of SM for educational purposes. The significant impact of information sharing and collaborative learning environments underscores the importance of creating supportive and interactive learning spaces. The positive relationship between affective learning engagement and learning performance reaffirms the importance of fostering positive emotions in learning. The strong positive correlation between educational SM use and student satisfaction suggests that when implemented effectively, SM can contribute significantly to students' overall learning experience. These results contribute to a more nuanced understanding of the complex interplay between SDT, affective engagement, and social media in education, offering valuable insights for educators and policymakers.

This study provides significant insights into the relationship between self-determination theory, affective learning engagement, educational social media use, student satisfaction, and learning performance. The findings emphasize the importance of fostering students' feelings of competence, autonomy, and relatedness to enhance their engagement and academic success. Effective integration of social media in education requires careful consideration of the factors that promote a supportive and collaborative learning environment. Future research could investigate the generalizability of these findings across diverse cultural contexts and educational settings and explore the long-term impact of SDT-based interventions on student learning outcomes.

The study's limitations include its reliance on self-reported data, which might be susceptible to bias. The sample was restricted to undergraduate students from one university in Saudi Arabia, limiting the generalizability of the findings to other contexts. Future research could address these limitations by using objective measures of learning performance and expanding the sample to include students from different universities and cultural backgrounds. The lack of data on actual SM usage patterns, beyond self-reported intention, is another limitation. Further research should investigate real-time usage behavior and its relationship to learning outcomes.