The impact of self-determination theory: the moderating functions of social media (SM) use in education and affective learning engagement

With the widespread use of social media (SM) by students, educators are examining its educational value and effects on learning outcomes. Prior research has produced mixed findings on whether SM improves academic achievement, with some studies reporting benefits, others reporting negative effects, and some finding no effect. Most prior studies in Saudi Arabia focused on motivations and usage, often overlooking mediating mechanisms linking SM use to outcomes. Grounded in self-determination theory (SDT)—which emphasizes autonomy, competence, and relatedness—this study investigates how these psychological needs, along with information sharing and collaborative learning environments, relate to affective learning involvement and educational SM use, and how these in turn influence student satisfaction and learning performance. The study addresses two main research questions: (1) What effects on learning and usage of SM platforms for education do students’ needs (perceived competence, perceived autonomy, and perceived relatedness) have? (2) When educational SM use and affective learning engagement are employed as instructional strategies, do students’ satisfaction and academic achievement increase?

The literature indicates extensive student use of SM (e.g., Facebook, Twitter, WhatsApp) and its potential to support participation, peer learning, and collaborative projects. However, studies show inconsistent effects of SM on academic performance—ranging from positive to negative to negligible—often due to neglecting mediating variables. SDT has strong empirical support across contexts and posits that fulfilling autonomy, competence, and relatedness needs enhances motivation and well-being, with applications to online and mobile learning. Prior research links knowledge sharing and collaborative learning with improved educational outcomes but highlights the need for more work on how SM affects information sharing in education, especially in post-adoption phases. This study integrates SDT with constructs including information sharing and collaborative learning environments to explain affective learning engagement and educational SM use as mechanisms connecting SDT needs to satisfaction and learning performance, particularly within the Saudi higher education context.

Design: Quantitative, cross-sectional survey using validated and adapted instruments grounded in SDT and prior IS/education studies. Sample and setting: Convenience sample of 300 undergraduate students at King Saud University (Saudi Arabia) during the summer semester 2022 (July–August). After removing seven incomplete responses, 293 valid questionnaires (97.6% usable rate) were analyzed. Demographics included 66.6% female; age mostly 25–29 (35.5%); specializations in humanities (59.0%), scientific sciences (26.3%), and medical sciences (14.7%). Measures: 45 items across nine constructs (perceived competence, perceived autonomy, perceived relatedness, information sharing, collaborative learning environment, affective learning involvement, educational SM use, students’ satisfaction, learning performance), five items per construct. Items adapted from Ryan & Deci (2000), Sørebø et al. (2009), Sun et al. (2019), Zhao et al. (2011), and Alamri et al. (2020a), Hosen et al. (2021). Responses on a 5-point Likert scale (1=strongly disagree to 5=strongly agree). Basic demographics collected. Analysis: IBM SPSS for descriptive statistics; SmartPLS 3.3.x for PLS-SEM. Measurement model assessed via convergent validity (AVE ≥ 0.5), discriminant validity (Fornell–Larcker criterion, HTMT, cross-loadings), reliability (Cronbach’s alpha and composite reliability ≥ 0.7). Multicollinearity checked via VIF (< 5). Structural model evaluated with bootstrapping (500 resamples), one-tailed tests, reporting path coefficients (β), t-values, and p-values. Model fit indices: SRMR=0.056; RMSEA=0.068; NFI=0.913; CFI=0.918; ChiSqr/dF=2.927, indicating acceptable fit. Validity and reliability results: All AVEs exceeded 0.5 (0.648–0.775); Cronbach’s alpha and composite reliability for all constructs were ≥ 0.887 and ≥ 0.902, respectively. HTMT values supported discriminant validity. VIF values indicated no collinearity concerns.

All 16 hypothesized paths were supported (p < 0.05). Key results (β, t, p): - H1: Perceived competence → Affective learning involvement β=0.122, t=2.258, p=0.024. - H2: Perceived competence → Educational SM use β=0.147, t=2.339, p=0.020. - H3: Perceived autonomy → Affective learning involvement β=0.485, t=8.649, p<0.001. - H4: Perceived autonomy → Educational SM use β=0.137, t=2.150, p=0.032. - H5: Perceived relatedness → Affective learning involvement β=0.167, t=2.556, p=0.011. - H6: Perceived relatedness → Educational SM use β=0.168, t=2.310, p=0.021. - H7: Information sharing → Affective learning involvement β=0.179, t=3.854, p<0.001. - H8: Information sharing → Educational SM use β=0.208, t=3.628, p<0.001. - H9: Collaborative learning environment → Affective learning involvement β=0.183, t=2.512, p=0.012. - H10: Collaborative learning environment → Educational SM use β=0.253, t=3.475, p=0.001. - H11: Affective learning involvement → Students’ satisfaction β=0.326, t=6.367, p<0.001. - H12: Affective learning involvement → Learning performance β=0.262, t=4.076, p<0.001. - H13: Educational SM use → Affective learning involvement β=0.156, t=2.222, p=0.027. - H14: Educational SM use → Students’ satisfaction β=0.532, t=11.373, p<0.001. - H15: Educational SM use → Learning performance β=0.238, t=3.622, p<0.001. - H16: Students’ satisfaction → Learning performance β=0.191, t=2.560, p=0.011. Measurement quality: AVEs ranged 0.648–0.775; reliability indices (alpha and CR) all ≥ 0.887 and ≥ 0.902; model fit indices within recommended thresholds.

Findings confirm that fulfilling SDT needs (autonomy, competence, relatedness) predicts higher affective learning involvement and greater educational use of SM, which in turn enhance students’ satisfaction and learning performance. Information sharing and collaborative learning environments also positively influence both affective engagement and educational SM use, underscoring the social and collaborative affordances of SM for learning. Educational SM use showed a particularly strong effect on student satisfaction (β=0.532) and a meaningful effect on learning performance (β=0.238). Affective learning involvement contributes directly to both satisfaction and learning performance, indicating that students’ emotional/hedonic engagement during learning is a key mechanism linking SDT needs and SM use to outcomes. These results address the research questions by clarifying how and when SM use can improve outcomes in higher education: when integrated to support SDT needs, knowledge sharing, and collaboration, SM fosters affective engagement and consequently improves satisfaction and performance.

The study demonstrates that competence, autonomy, relatedness, information sharing, and collaborative learning environments foster affective learning engagement and educational SM use, which enhance students’ satisfaction and learning performance in higher education. Integrating SDT principles into SM-supported instruction can motivate students and improve outcomes by promoting autonomy, competence, and relatedness alongside collaborative knowledge sharing. The work contributes a validated model (with strong reliability, validity, and fit) linking SDT needs to affective engagement, educational SM use, satisfaction, and learning performance in a Saudi higher education context. Future research should incorporate objective performance measures, examine diverse cultural and institutional contexts, include actual-use behavioral data, and explore additional predictors and mediators of educational SM use and engagement.

- Behavioral measures: The model did not include observed actual-use behavior; only intentions/self-reports were used. - Cultural/contextual scope: Conducted at a single Saudi university (collectivist context); findings may differ in other cultural or institutional settings. - Sample generalizability: Participants were from one institution and selected disciplines; results may not generalize to other universities or fields. - Self-reported outcomes: Due to privacy constraints, objective GPA or similar performance data were not obtained; reliance on self-reports may introduce bias. - Future scope: Recommend inclusion of objective measures, replication across institutions and cultures, incorporation of additional determinants (e.g., ease of use, perceived enjoyment), and examination of further mediators/moderators.