本研究目的在於探討「導入探究與實作精神的人工智慧及其應用通識課程」對諮商領域學生人工 智慧素養之影響。本研究參與者為諮商相關學系大學部一年級學生，在導入探究與實作教學過程 中，讓非科技相關科系學生有機會透過人工智慧概念的學習與實作課程的體驗，學習人工智慧的 內涵，以提升其人工智慧的素養、好奇，並探究人工智慧如何運用在諮商及輔導領域。本研究採 行動研究法，在課程前與課程學習後，以陳璽宇（2020）所編製的「AI 素養測驗」為研究評量工 具、「課程後書寫的課程學習心得與省思札記」作為評量與資料分析工具，了解課程的訓練效果， 並於學習成績送出後，邀請其同意進行焦點團體訪談，作為本研究質性分析資料的依據。研究發 現探究與實作之教學方法有助於非科技領域學生學習人工智慧與應用，而大一學生在修習一學期 之「人工智慧及其運用」通識課程後，在人工智慧素養之「認知」與「技能」方面，於量化、質 性資料皆呈現明顯之進步與學習，「態度」層面於前後測雖無顯著差異，在質性資料則呈現正向、 從抗拒到感興趣、覺察人工智慧素養學習上的困難之處。最後本研究亦呈現此次研究結果反思與 建議，作為調整與修正人工智慧及其應用課程之依據。

This study investigated the effects of the general education curriculum of the course “Artificial Intelligence and its Application” on the artificial intelligence (AI) literacy of students in the field of counseling. Participants in this study were firstyear undergraduate students from the relevant counseling departments. We incorporated inquiry and hands-on experiences into the curriculum of “Artificial Intelligence and its Application” to provide an opportunity for students not majoring in information technology to learn the concepts of AI and to gain hands-on experience for improving their AI literacy. Our strategy involved promoting students’ interest for exploring how AI can be used in the field of counseling and guidance. This study adopted the action research method. The teaching effects of the course were evaluated, and the data were analyzed using the AI Attitudes, Knowledge, and Skills Scale compiled by Chen (2020) and the Course Learning Experience and Thinking Note Written after the Course tool. Moreover, students were invited for a focus group interview, and their final grades served as qualitative data that were analyzed in this study. The quantitative analysis results revealed that the students’ AI literacy increased after they were taught using the general education curriculum of the course. Moreover, their pretest scores were significantly higher than  the post-test scores for the AI knowledge and ability subscale. The above results reached a significant level (p < .001), indicating that the students’ AI knowledge and skills were markedly enhanced after one semester of the course. Most of the subscales and total scores related to AI attitude were higher in the post-test than in the pretest, but the difference was nonsignificant. To verify the reliability of the pretest and post-test quantitative results, this study conducted a correlation analysis between AI literacy subscale and students’ final grades. The correlation coefficient was between .059 and .515. Moreover, the scores of the decision-making component in the AI attitude scale and AI knowledge and skills subscale were significantly positively correlated with the students’ final grades (p < .01 and p < .05, respectively). The qualitative analysis results were divided into three major themes and eight categories. The first theme pertained to the influence of the AI course design, which incorporated inquiry and practice, on students’ learning; the learning outcomes included increasing their awareness and reflection on AI through theoretical courses. First, the theoretical courses in this study employed diverse instructional modes, including film appreciation, listening to lectures, and teaching by professors. Second, through practical courses, students gained experience in the use of AI, including machine learning, deep learning, algorithms, and programming, and they learned through practice. During the course, students believed interacting with AI to be a novel and interesting experience. However, few students reported negative experiences because they found the programming aspect to be challenging. Finally, by exploring the theme and creating a report on the theme, students learned to integrate multifaceted abilities, such as positive feelings about classmates’ reports, students’ abilities to prepare and complete the report, and students’

人工智慧及其應用；通識課程；人工智慧素養；探究與實作教學； 行動研究

artificial intelligence and its application；general education curriculum； artificial intelligence literacy； inquiry teaching and hands-on experience； action research