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| Title: | 具情緒識別與反應能力之AI虛擬導覽員於元宇宙數位策展成效的影響研究
A Study on the Effects of an AI Virtual Tour Guide with Emotion Recognition and Response Capabilities on Metaverse Digital Curation Performance |
| Authors: | 張添輔
Chang, Tien-Fu |
| Contributors: | 陳志銘
Chen, Chih-Ming
張添輔
Chang, Tien-Fu |
| Keywords: | 元宇宙數位策展
AI虛擬導覽員
情緒辨識
情緒智力
語音導覽
Metaverse Digital Curation
AI Virtual Tour Guide
Emotion Recognition
Emotional intelligence
Audio Guide |
| Date: | 2025 |
| Issue Date: | 2025-08-04 14:03:34 (UTC+8) |
| Abstract: | 隨著數位科技與元宇宙技術的快速發展，數位策展已成為圖書館、博物館，以及美術館等文化機構的重要文化傳播模式，元宇宙的擬真場域更進一步提供觀展者沉浸式的虛擬互動空間，使其能透過虛擬化身與展品、角色，抑或他人互動，可突破時間與空間的限制，進而提升觀展體驗。文化機構亦逐漸導入具互動性的數位導覽系統，尤其是結合自然語言處理與機器學習技術的AI虛擬導覽員，進而提升觀展者的學習體驗。此外，情緒亦在觀展過程中扮演關鍵角色，觀展者可能因展覽內容，抑或個人情感狀態產生情緒反應，而這些情緒將影響其對於展覽的感受、理解，以及記憶深度。因此，本研究旨在開發應用於元宇宙數位策展平台的「具情緒識別與反應能力之AI虛擬導覽員」，其可透過自然語言問答與語音回饋，提供具同理心的回覆內容，進而提升觀展學習者的情感共鳴與知識內化。
本研究採用真實驗研究法，選取高中在校以及應屆畢業生共計60名，並隨機分派各30名受試者，分別使用有/無「情緒辨識與反應能力之AI虛擬導覽員」搭配語音輔以進行「白色恐怖」的元宇宙數位策展，並據此探討此兩種不同觀展學習模式在學習成效感受、內在學習動機、沉浸經驗感受、科技接受度，以及情感投入上是否具有顯著的差異。此外，亦進一步探討高低不同情緒智力觀展學習者使用這兩種不同觀展學習模式，在學習成效感受、內在學習動機、沉浸經驗感受、科技接受度，以及情感投入上是否具有顯著的差異。最後，也透過與AI虛擬導覽員之問答互動內容與提問行為分析，以及半結構式訪談蒐集受試者在觀展過程中的學習互動歷程、想法、感受，以及建議。
研究結果發現，對於低情緒智力觀展學習者而言，使用「不具情緒辨識與反應能力」之「AI虛擬導覽員」輔以進行「白色恐怖」元宇宙數位策展之觀展學習模式，有顯著較佳的學習成效感受，但使用「具情緒辨識與反應能力」之「AI虛擬導覽員」觀展模式能顯著減緩觀展學習的焦慮與壓力。至於其他面向則兩種觀展學習模式均未達顯著的差異。
根據訪談結果，多數觀展學習者認為搭配「具情緒識別與反應能力之AI虛擬導覽員」輔以觀展學習，有助於加深對白色恐怖歷史事件的理解與記憶。這種具同理心的互動模式，有助於提升觀展者之參與意願與投入感，進一步強化其觀展的學習成效，特別是在情緒支持方面發揮了積極作用。此外，觀展學習者普遍肯定情緒識別功能所帶來的擬真感受與情緒支持，尤其當AI虛擬導覽員能配合觀展情境調整語氣與回應時，更能激發觀展學習者的情感覺察與主動學習意願，進而提升其知識吸收的深度。
本研究根據研究結果針對「具情緒辨識與反應能力之AI虛擬導覽員」輔以進行元宇宙數位策展之優化建議，也提供未來可繼續延伸及擴展的研究方向，以作為實質策展與學術研究之參考。
With the rapid advancement of digital technologies and metaverse-related innovations, digital curation has emerged as a vital mode of cultural dissemination for institutions such as libraries, museums, and art galleries. The immersive environments enabled by the metaverse offer visitors interactive virtual spaces that transcend the limitations of time and space, allowing them to engage with exhibits, characters, and other users through their virtual avatars. In response to these developments, cultural institutions have increasingly adopted interactive digital guide systems—most notably, AI-powered virtual tour guides that integrate natural language processing and machine learning technologies—to enhance the educational experiences of exhibition visitors. Moreover, emotion plays a critical role in the exhibition experience, as visitors may exhibit emotional responses triggered either by the exhibition content or by their own affective states. These emotional reactions significantly influence how they perceive, understand, and remember the exhibition. Accordingly, this study aims to develop an AI virtual tour guide with emotion recognition and response capabilities for application within a metaverse-based digital curation platform. Through natural language dialogue and voice-based feedback, the system provides empathetic responses, thereby fostering emotional resonance and supporting deeper knowledge internalization among exhibition learners.
This study employed a true experimental research design involving a total of 60 participants, comprising current and recently graduated high school students. Participants were randomly assigned into two groups of 30 individuals each. One group experienced a metaverse-based digital curation of the “White Terror” exhibition assisted by an AI virtual tour guide equipped with emotion recognition and response capabilities alongside voice interaction, while the other group engaged with the same exhibition without such AI emotional features. The study aimed to examine whether these two different exhibition-based learning models yielded significant differences in perceived learning effectiveness, intrinsic learning motivation, immersive experience, technology acceptance, and emotional engagement. Furthermore, the study investigated whether learners with varying levels of emotional intelligence demonstrated significant differences in these five dimensions when interacting with the two learning models. Finally, the research incorporated an analysis of user–AI interaction content and questioning behavior, as well as data collected through semi-structured interviews to explore participants’ learning processes, perceptions, emotional responses, and suggestions during the exhibition experience.
The results of the study revealed that, for exhibition learners with low emotional intelligence, engaging with the “White Terror” metaverse-based digital curation using an AI virtual tour guide without emotion recognition and response capabilities led to significantly higher perceived learning effectiveness. However, the use of an AI virtual tour guide with emotion recognition and response capabilities was found to significantly alleviate learners’ anxiety and stress during the exhibition experience. For other dimensions—namely intrinsic learning motivation, immersive experience, technology acceptance, and emotional engagement—no statistically significant differences were observed between the two learning models.
According to the interview findings, most exhibition learners perceived that engaging with the exhibition through an AI virtual tour guide equipped with emotion recognition and response capabilities enhanced their understanding and memory of the historical events related to the White Terror. This empathetic mode of interaction was found to increase participants' willingness to engage and their sense of involvement, thereby reinforcing the effectiveness of their learning experience—particularly in terms of emotional support. Moreover, participants generally affirmed the value of the emotion recognition function in enhancing the sense of realism and emotional resonance. Notably, when the AI virtual guide adapted its tone and responses to match the exhibition context, it further stimulated learners’ emotional awareness and motivation for active learning, contributing to a deeper absorption of knowledge.
Based on the research findings, this study offers recommendations for optimizing the use of AI virtual tour guides with emotion recognition and response capabilities in metaverse-based digital curation. Additionally, it proposes future research directions that can be further explored and expanded, serving as a valuable reference for both practical curation initiatives and academic inquiry. |
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| Description: | 碩士
國立政治大學
圖書資訊與檔案學研究所
112155018 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0112155018 |
| Data Type: | thesis |
| Appears in Collections: | [圖書資訊與檔案學研究所] 學位論文
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