언어학습에서 긍정심리를 위한 생성형 인공지능과 에듀테크 활용.

This research examined the confluence of generative AI and educational technology (EdTech) within the realm of positive psychology for language learning tasks. Focused on the five key positive psychology factors—grit, academic engagement, enjoyment, resilience, and well-being—students engaged in a task of rewriting the lyrics of Anne Marie’s song “2002” to express their future goals and career aspirations. This task leveraged a range of EdTech tools to offer personalized support in the lyric adaptation process, simultaneously enriching the overall learning experience with positive psychological aspects. The study identified significant positive correlations between task completion and accuracy with three of the positive psychology factors: grit (r = .35, p < .01 for task completion; r = .36, p < .01 for task accuracy), enjoyment (r = .27, p < .01; r = .28, p < .01), and academic engagement (r = .45, p < .01; r = .46, p < .01), indicating that higher levels of these factors are associated with improved task performance and accuracy. In contrast, well-being and resilience did not exhibit significant correlations with either task completion or accuracy. The findings further highlighted that academic engagement significantly predicts both task completion and accuracy, with a beta value of 1.55 for task completion (p < .001) and 1.798 for task accuracy (p < .001). grit, with a beta value of 0.59 for task completion (p = .06) and 0.938 for task accuracy (p = .06), marginally influences task outcomes, implying that students with higher grit are 1.8 times more likely to perform tasks accurately. Notably, the outcomes also revealed varied reasons for student reluctance to use AI, underscoring the complexities of integrating AI into language learning settings. This reluctance among students was attributed to factors such as perceived complexity, preference for personal effort, and uncertainties in how to effectively utilize AI for language tasks. These insights shed light on the importance of aligning technological tools with learner needs and preferences, paving the path toward more effective and personalized language learning environments. [ABSTRACT FROM AUTHOR]