Technology perceptions, emotions, and social support in technology-enhanced learning: Differential associations with learning outcomes in primary education

Background Technology-enhanced learning has become increasingly common in primary education, yet the collective roles of students’ technology-related perceptions, emotional experiences, and social support in shaping learning outcomes remain insufficiently understood. This study examined how perceived ease of use, perceived usefulness, pressure, interest, parental support, and teacher support are associated with change in two learning outcome domains: declarative musical knowledge and aural skills in digitally supported primary education. Methods Drawing on the technology acceptance model, achievement-emotion perspectives, and social support theory, we proposed the Techno‑Emo‑Socio framework, which contains six predictors and two distinct learning outcomes. We tested this framework using a pre–posttest design with data from 135 third‑grade students at a public primary school in China who used a tablet-based music learning application over 16 lessons. Objectively assessed learning outcomes were estimated using the Rasch model, and latent change score models were used to examine associations over time. Findings The results showed domain-specific patterns. Perceived ease of use was positively associated with gains in aural skills, whereas pressure was negatively associated with gains in declarative knowledge. Perceived usefulness, interest, parental support, and teacher support were not statistically significant predictors of either outcome. Conclusion These findings suggest that selected technological and emotional factors show domain-specific associations with objectively assessed learning gains in digitally supported primary classrooms. The Techno-Emo-Socio framework should therefore be interpreted as a heuristic for organizing potentially relevant factors rather than as a validated predictive model. The study underscores the importance of assessing distinct learning outcomes and interpreting predictor-outcome associations cautiously.