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| Title: | 基於 SFBT 架構探討 AI 協作中的行為建議對個體生涯自我效能的影響
The effect of SFBT-based behavioral advice on career self-efficacy: an AI-Human collaboration approach |
| Authors: | 紀玟伶
Chi, Wen-Ling |
| Contributors: | 陳宜秀
廖峻鋒
Chen, Yi-Hsiu
Liao, Chun-Feng
紀玟伶
Chi, Wen-Ling |
| Keywords: | 人工智慧
心理健康
生涯自我效能
人機互動
人智協作
對話型機器人
AI
Mental health
Career self-efficacy
HCI
Chatbot
Human-AI Collaboration |
| Date: | 2025 |
| Issue Date: | 2025-08-04 15:50:59 (UTC+8) |
| Abstract: | 當個體遇到求職的挑戰，伴隨而來的情緒困擾或是壓力，除了選擇自身勇敢面對之外，還能有其他支持性的資源可以使用。目前在社會或校園中有輔導和諮商的管道，都是個體可利用的資源。輔導與諮商能夠幫助個體處理內在認知，覺察感受，此過程中不僅能夠獲得同理與支持，還能促進自我理解，更有方法面對困擾自身的議題。
隨著科技的發展，運用人工智慧的輔助，能夠為諮商服務提供新的發展性。人工智慧應用於心理健康領域的協助應用，因其能夠突破時空限制，給予個體更即時的幫助與建議，也能為個體提供另一個求助資源。因此，希望透過本研究探索人工智慧使用焦點解決短期治療（solution-focused brief therapy, SFBT），將其應用於輔導個體探索生涯的過程，理解人工智慧如何與個體雙向互動和協作，在評估個體能力之後，給予聚焦問題的行動解方，並且觀察人工智慧在提供個體執行建議後，其是否能夠對個體的生涯自我效能產生正向影響，並協助減緩壓力。
本研究採用單因子組間設計實驗法，將30位參與受試者隨機分配至三個組別：「AI協作組」、「文字引導組」、「獨立完成組」。實驗操弄變項為不同「接收到行為建議的方式」，依變數為「生涯自我效能」和「壓力值」，每位受試者皆需完成前測和後測，用來觀察受試前後的變化，藉此理解人工智慧如何與個體協作產生行為建議，以及輔助過後造成的效果影響。
實驗結果顯示，在AI協作組提升生涯自我效能表現最為突出，平均提升 10.7 分、文字引導組平均提升4.9分、獨立完成組平均提升2.5分。AI協作組與獨立完成組間存在顯著差異（t（26）= 2.574， p = .041）。AI協作組中，對話型機器人擔任職涯輔導員的角色，協助受試者針對求職目標討論、探索過去的成功經驗以及拆解行動步驟。在過程中，受試者會收到對話型機器人的回饋，如同獲得同行夥伴陪伴其前行，協助其提升生涯自我效能。另外，雖然結果顯示人工智慧輔助行為建議對個體壓力具有緩解效果，然而，在實驗結果中發現組間之間並沒有顯著差異。未來研究應增加樣本數，在取樣上盡量減少個體間的差異，增加研究數據對於結果的支持。
本研究結果顯示，基於SFBT架構下所設計的人工智慧對話型機器人，能依照個體的狀態與能力，與其討論出合適的行為建議，幫助個體思索過往成功經驗或是可利用的資源，協助個體找回面對難題的掌控感，也提升其面對和解決求職問題的自我效能。本研究指出，人工智慧的數位工具可作為諮商輔導的輔助資源，也能成為個體自我幫助的方法之一，提供未來設計對話型機器人應用於心理健康領域的研究參考。
When people look for a job, they may feel stressed or emotionally overwhelmed; however, they can find support through helpful resources. People can access counseling services available in society and on campus. This process not only helps people process their thoughts and care for their emotions, but also enhances self-awareness and provides guidance on how to address the problems they are facing.
As technology advances, artificial intelligence presents new opportunities for the development of counseling services, overcoming time and location limitations to provide people with immediate help and advice. This study aims to explore the application of artificial intelligence in solution-focused brief therapy (SFBT) and utilize it to support individuals in focusing on resolving problems in their career planning. To understand how artificial intelligence collaborates with people and provides advice. It also examines whether artificial intelligence enhances people's career self-efficacy and helps them reduce stress.
This study adopts a single-factor experimental design. Randomly assigning 30 participants into three groups: "AI-guided group", "Text-guided group", "Self-Guided group". The experimental manipulation variable is the different methods of receiving behavioral advice. The dependent variables include career self-efficacy and stress scores. Each participant is required to complete both the pre-test and post-test to observe changes before and after the experiment, which helps to understand how artificial intelligence collaborates with people to provide behavioral advice and the effect of the advice provided.
Results showed that the AI-guided group had the most improvement in career self-efficacy, with an average increase of 10.7 points, followed by the text-guided group with 4.9 points and the self-guided group with 2.5 points. A significant difference was found between the AI-guided group and the self-guided group, t(26) = 2.574, p < .05 . In the experiment, the chatbot played the role of a career mentor. It supported people in sharing their goals, reflecting on their successful experiences, and breaking down the goal into small action steps. During the experiment, participants received feedback from the chatbot. This support is beneficial in enhancing their career self-efficacy.
Furthermore, the results showed that stress was reduced in the AI-guided group; however, there were no significant differences between the groups. In future studies, increasing the sample size and balancing the stress levels before the experiment may help reduce individual variability and enhance the reliability of the findings.
In summary, this demonstrates that an AI chatbot designed under the SFBT framework can provide suitable behavioral advice tailored to individuals' needs and abilities. Because of this help, it enhances people's career self-efficacy and confidence in facing job search challenges. AI-collaborative digital tools can serve as a supportive resource in counseling. It can also be a self-help resource. The results and insights from this study can offer a valuable reference for future research on the use of chatbots in the mental health field. |
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| Description: | 碩士
國立政治大學
數位內容碩士學位學程
112462003 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0112462003 |
| Data Type: | thesis |
| Appears in Collections: | [數位內容碩士學位學程] 學位論文
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