MODELING THE STRUCTURAL IMPACT OF ARTIFICIAL INTELLIGENCE LITERACY ON VOCABULARY KNOWLEDGE THROUGH LANGUAGE LEARNING MOTIVATION AMONG IRAQI EFL LEARNERS
Keywords:
Artificial Intelligence Literacy; Language Learning Motivation; AI-Based Educational Tools; Vocabulary Knowledge.Abstract
The present study aimed to "model the structural effect of AI literacy on vocabulary knowledge through language learning motivation among Iraqi learners of English as a foreign language". This study is descriptive-survey and applied and is of correlational type in terms of the relationship between the components under study. The research population is all undergraduate students in the field of English in Iraqi higher education institutions in the academic year 2024-2025, from which a sample of 300 people was selected using the stratified sampling method and based on the proportion of the field and level of education, and the research questionnaire was distributed among them. Data collection was carried out using standard questionnaires. SmartPLS3 statistical software was used to analyze the data and test the hypotheses. According to the results of the model, AI literacy had an effect on the motivation to learn and vocabulary knowledge of the learners. The results also showed that learning motivation could act as a mediator and reflect the effect of AI literacy on learners' vocabulary knowledge. However, the moderating role of AI tools was not significant. This means that AI tools do not moderate the relationship between AI literacy and vocabulary knowledge.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
