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From empathy to quality long-term care: a generative AI-based art therapy approach based on the self-directed learning model

移情 生成语法 心理学 劳动力 计算机科学 医学教育 护理部 医学 人工智能 社会心理学 经济增长 经济
作者
Ching‐Yi Chang,Pei‐Ling Wang,Chia‐Jung Li,Gwo‐Jen Hwang
出处
期刊:Interactive Learning Environments [Taylor & Francis]
卷期号:33 (5): 3333-3353 被引量:13
标识
DOI:10.1080/10494820.2024.2443072
摘要

The demand for a multi-disciplinary workforce in long-term care is paramount, particularly in the realm of life care services. Art therapy has been recognized as being a promising approach for promoting learners' empathy and competences for long-term care. However, in traditional art therapy courses, most students who are not interested in artworks or who do not have experience in artwork creation could lack confidence in their ability and motivation to engage in relevant activities, which could hence affect their learning performances. This study proposed a Generative Artificial Intelligence (Generative AI)-based art therapy approach to promote learners' empathy and art therapy performance in gerontological nursing training. A quasi-experimental design was adopted. The participants were two classes of students from a nursing college. The experimental group with 33 students learned with the Generative AI-based art therapy approach focused on gerontological healthcare activities, whereas the control group with 32 students was taught using the traditional art therapy instruction. Compared to the control group, the experimental group nursing students showed significant improvement in their empathy and art performance. The findings could be a reference to those who intend to use images or graphics generated by generative AI in educational technology research.
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