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Linking digital competence, self-efficacy, and digital stress to perceived interactivity in AI-supported learning
Jiaxin Ren1, Juncheng Guo2, Huanxi Li3
1Faculty of Social Sciences and Liberal Arts, UCSI University, Kuala Lumpur, Malaysia. jiaxin0776@gmail.com.
Scientific Reports
|September 27, 2025
Summary
Learners with higher digital competence interact better with artificial intelligence (AI). Digital stress can weaken this connection by impacting self-efficacy in AI learning environments.
Area of Science:
- Educational Technology
- Human-Computer Interaction
- Artificial Intelligence in Education
Background:
- Artificial intelligence (AI) integration in education necessitates understanding learner perceptions.
- Learner interaction with AI systems is influenced by digital competence and self-efficacy.
- Digital stress may impact the effectiveness of AI in learning environments.
Purpose of the Study:
- To investigate the relationship between digital competence and perceived AI interactivity.
- To examine the mediating roles of information retrieval self-efficacy and human-robot interaction self-efficacy.
- To explore the moderating effect of digital stress on AI-learner interactions.
Main Methods:
- A moderated serial mediation model was employed.
- Data were collected from 921 Chinese university students.
- Theoretical frameworks included constructivist learning theory, technology acceptance model, cognitive load theory, identical elements theory, and control-value theory.
Main Results:
- Digital competence positively correlated with perceived AI interactivity, both directly and indirectly.
- Self-efficacy in information retrieval and human-robot interaction sequentially mediated this relationship.
- Increased digital stress weakened the indirect effect of digital competence on perceived interactivity.
Conclusions:
- Learner-AI interaction is influenced by a combination of cognitive (competence, self-efficacy) and emotional (stress) factors.
- Digital competence is crucial for effective AI-enhanced learning.
- Educational AI designs should consider individual differences in digital competence and stress levels for optimal learning outcomes.
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