A Study on the Relationship between AI Anxiety and AI Behavioral Intention of Secondary School Students Learning English as a Foreign Language
Artificial Intelligence (AI) provides new tools and approaches for English as a Foreign Language (EFL) learning, yet it also brings new risks and challenges, such as AI anxiety. With the gradual adoption of AI in EFL learning, AI anxiety has brought about a variety of issues. In order to help educat...
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| Published in: | Journal of educational technology development and exchange Vol. 17; no. 1; pp. 130 - 154 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
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| ISSN: | 1941-8035, 1941-8035 |
| Online Access: | Get full text |
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| Summary: | Artificial Intelligence (AI) provides new tools and approaches for English as a Foreign Language (EFL) learning, yet it also brings new risks and challenges, such as AI anxiety. With the gradual adoption of AI in EFL learning, AI anxiety has brought about a variety of issues. In order to help educators understand students’ concerns and promote the use of AI for secondary school students’ EFL learning, this study took the Unified Theory of Acceptance and Use of Technology (UTAUT) and relevant aspects of AI anxiety as the theoretical foundation. Subsequently, this study analyzed the situation of AI anxiety among secondary school students and its relationship with students’ Behavioral Intention to use AI EFL learning tools. Data were collected through an online platform, with 293 valid responses from secondary school students in Beijing, China. Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were used to analyze the data. The validity and reliability of the scale were satisfied with nine constructs: Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Behavioral Intention, AI Learning Anxiety, Job Replacement Anxiety, Sociotechnical Blindness Anxiety, and AI Configuration Anxiety. The results indicated: (1) Performance Expectancy, Effort Expectancy, Social Influence and Facilitating Conditions could all positively predict Behavioral Intention in different degrees, and Social Influence had the strongest effect; and (2) AI Learning Anxiety and Job Replacement Anxiety might indirectly and negatively predict Behavioral Intention through intermediate variables. Based on the analysis, the study suggests that educators should not only cultivate students’ AI literacy through comprehensive AI education, but also guide students to form correct emotions through scientific psychological interventions so that they can better use AI EFL learning tools. |
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| ISSN: | 1941-8035 1941-8035 |
| DOI: | 10.18785/jetde.1701.07 |