Artificial Intelligence and Learning Efficiency: The Mediating Role of Time Management (A Case Study of Korean Language Learners at the International University of Ulaanbaatar)
DOI:
https://doi.org/10.65168/Keywords:
Generative AI, AI Literacy, Self-Directed Learning, Self-Regulated Learning, Learning StrategiesAbstract
This study examines the relationship between the proficiency of Korean as a Foreign Language (KFL) learners in utilizing Artificial Intelligence (AI)-based technologies and their perceived learning efficiency, specifically identifying the mediating role of time management. The research involved 100 university students, and the collected data was analyzed using descriptive statistics, correlation analysis, regression analysis, and mediation effect analysis.
The results indicate that AI technology proficiency has a positive and statistically significant impact on both time management (β=.387, p< .001) and perceived learning efficiency (β= .342, p< .001). Furthermore, it was discovered that time management serves a statistically significant mediating role between AI technology proficiency and perceived learning efficiency. This suggests that the ability to effectively utilize AI technology supports behavioral regulation related to a learner's use of time, thereby influencing a more efficient evaluation of the learning process.
However, regarding the frequency of AI technology use, the results showed that unorganized and aimless usage could potentially have a negative impact on the learning process. Nevertheless, as this study relies on self-reported and cross-sectional data, it is not possible to fully establish a causal relationship. Future research should utilize longitudinal research designs and objectisve measures such as actual AI usage logs and academic performance indicators.
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This work was supported by the Core University Program for Korean Studies of the Ministry of Education of the Republic of Korea and Korean Studies Promotion Service at the Academy of Korean Studies (AKS-2022-OLU-2250006).