From anxiety to action: exploring the impact of artificial intelligence anxiety and artificial intelligence self-efficacy on motivated learning of undergraduate students

ABSTRACT The rapid development of artificial intelligence (AI) technology, while empowering higher education, has also introduced anxiety and stress among university students. This study examines the impact of AI anxiety on motivated learning and the moderating role of AI self-efficacy. Data were collected from 387 valid questionnaires at a university in China, and the hypotheses were analyzed using SPSS 25.0 and PROCESS plug-in. The results indicate that AI anxiety, encompassing the dimensions of learning, AI configuration, job replacement, and sociotechnical blindness, has a positive impact on motivated learning, and AI self-efficacy positively moderates the relationship between AI learning anxiety and motivated learning. Specifically, AI self-efficacy enhances the positive effect of AI learning anxiety on motivated learning. This study contributes to the existing literature and offers insights for the application of AI in higher education practice.

• Publication year

  2024

• Venue

  Interactive Learning Environments

• Publication date

  2024-12-17

• Fields of study

  Computer Science, Education, Psychology

• Identifiers
  DOI 10.1080/10494820.2024.2440877
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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