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題名 整合生成式與知識型人工智慧聊天機器人於影片自主學習之成效影響研究
The Effects of a Video Learning System with the Support of Integrating Generative and Knowledge-based AI Chatbots on Self-Directed Learning Performance
作者 陳奕慈
Chen, Yi-Cih
貢獻者 陳志銘
Chen, Chih-Ming
陳奕慈
Chen, Yi-Cih
關鍵詞 影片學習
自主學習
聊天機器人
Rasa
ChatGPT
Video-based learning
Self-directed learning
Chatbot
Rasa
ChatGPT
日期 2024
上傳時間 5-Aug-2024 14:51:55 (UTC+8)
摘要 影片為自主學習常用的一種教學媒體，經常被應用於線上學習與翻轉教學。然而，學習者在使用影片進行自主學習時，常常會因為缺乏觀看影片的動機、缺少學習同伴，抑或教師解答學習問題等因素而影響其學習表現。因此，如何有效提升學習者使用影片進行自主學習時的學習成效與學習動機，一直是重要的研究議題。過去已有少數研究嘗試將聊天機器人技術融入於影片自主學習，然而，這些研究所發展的聊天機器人，其對話資訊通常係由人工制定，並受限於資料庫建立的語料範圍，因此無法完整且精準地回覆學習者在學習過程中的提問，致使無法有效輔助學習者進行自主學習。隨著生成式人工智慧聊天機器人技術的迅速發展，OpenAI於2022年推出之聊天生成預訓練轉換器（ChatGPT），讓輔助學習之聊天機器人發展產生突破性的發展。許多研究指出，ChatGPT能夠提供多樣的功能來輔助教師與學習者進行教與學。然而，雖然ChatGPT基於大型語言模型具有廣博之可對話語料，但與使用者進行對話時，可能會生成錯誤的應答資訊，也無法回答跟特定情境具有關聯的問題。相較之下，Rasa為一種可以利用其所提供的自然語言理解與回應框架，來建置適合應用於特定情境之聊天機器人。因此，本研究使用Rasa來建置由專家知識組成的小型語料庫，並結合ChatGPT來補足Rasa缺少廣博知識的問題，開發出一種更具實用性之整合生成式與知識型之AI聊天機器人，來更有效的輔以學習者進行影片自主學習。 本研究採用單一實驗組前後測設計，以桃園市某高中一年級共36名學生為研究對象，探討使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以學習者進行影片自主學習，是否有助於提升學習者的學習成效與學習動機，並且能否帶來良好的科技接受度與聊天機器人優使性感受。此外，亦探討學習者對於聊天機器人的優使性感受是否與學習成效、學習動機，以及科技接受度具有顯著的相關性。另外，也進一步探討使用此一系統輔以自主學習之高低不同自律能力、不同認知風格，以及高低不同先備知識的學習者，在學習成效、學習動機、科技接受度，以及聊天機器人優使性感受上是否具有顯著的差異。最後，本研究亦採用半結構深度訪談法，了解學習者使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以進行影片自主學習的學習歷程、感受與建議。 研究結果發現，無論是全體、高低不同自律能力、不同認知風格，還是高低不同先備知識的學習者使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以進行影片自主學習皆能夠帶來顯著的學習成效提升。再者，學習者在使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以進行影片自主學習時，對於與AI聊天機器人的互動像真人對話一般的感受程度，跟學習成效具有顯著關聯。在學習動機上，「具整合生成式與知識型AI聊天機器人支援之影片學習系統」能有效地提升全體、低自律能力、場地獨立型，以及高低不同先備知識的學習者使用影片進行自主學習的學習動機。此外，學習者對於使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以進行影片自主學習的科技接受度高於中位數，且除了對於學習者的隱私保護之外，學習者對於整合生成式與知識型AI聊天機器人的優使性感受亦均高於中位數。最後，根據訪談結果顯示，學習者普遍認為相較於單獨使用ChatGPT輔助進行自主學習，採用本研究所開發的整合生成式與知識型AI聊天機器人輔以進行影片自主學習會更加理想。 綜合以上所述，本研究成功結合Rasa與ChatGPT工具，發展出一個「整合生成式與知識型AI聊天機器人之影片自主學習系統」，改善過去聊天機器人無法有效輔助學習者進行自主學習的問題，並且顯著提升了學習者的學習成效與學習動機。此外，本研究為聊天機器人在教育領域的應用，開展了新的發展方向。
Video is commonly used for self-directed learning, especially in online courses and flipped classrooms. However, learners who engage in self-directed learning through videos often face challenges such as lack of learning motivation, absence of peer support or teachers to respond their learning questions, all of which can impact their learning effectiveness. Therefore, effectively improving learners’ learning motivation and learning effectiveness when using videos for self-directed learning is an essential research issue in educational settings. Previous studies have explored the integration of chatbot technology into video-based self-directed learning. However, these chatbots developed typically rely on manually-crafted dialogues constrained by the corpus established in the database, resulting in limitations in their ability to accurately respond to learner queries and provide effective support. The advent of generative artificial intelligence chatbot technology, exemplified by OpenAI’s ChatGPT launched in 2022, represents a significant advancement in chatbot development for educational purposes. Despite ChatGPT’s broad conversational capabilities based on Large Language Models (LLM), like other generative AI chatbots, it occasionally generates incorrect information or fails to respond questions within specific contexts. In contrast, Rasa provides a natural language understanding and response framework that allows for the creation of chatbots tailored to specific contexts using small, custom-built corpora. Therefore, this study utilized Rasa to build an expert knowledge-based chatbot trained by a human expert based on a small corpus and integrated it with ChatGPT to complement the lack of extensive knowledge in Rasa. This combined approach aims to create a more practical AI chatbot capable of effectively assisting learners in video-based self-directed learning. The study adopts a one-group pretest-posttest design involving 36 Grade 10 learners as the research subjects from a senior high school in Taoyuan City, Taiwan to participant in an instruction experiment. The aim of this study was to investigate whether the “Video Learning System with the Support of Integrating Generative and Knowledge-based AI Chatbots (VLS-SIGKAIC)” can significantly improve learners’ learning effectiveness and motivation in video-based self-directed learning. Additionally, the study evaluates the system’s technology acceptance and the learners’ satisfaction with the chatbot experience. In addition, the study explores the correlation between learners’ satisfaction with the chatbot experience and their learning effectiveness, motivation, and technology acceptance. Furthermore, this study investigates potential differences in learning effectiveness, motivation, technology acceptance, and satisfaction with chatbot usage among learners with different levels of self-regulated learning ability, cognitive styles, and prior knowledge while utilizing this system for self-directed learning. Lastly, semi-structured in-depth interviews are employed to understand learners’ perceptions, feelings, and suggestions towards using VLS-SIGKAIC. Experimental results showed that VLS-SIGKAIC significantly improved learning effectiveness for all learners, regardless of their levels of self-regulated learning ability, cognitive styles, or prior knowledge levels. Furthermore, a significant correlation was observed between learners’ perceptions of interacting with the AI chatbot as if it were a human and their learning effectiveness. In terms of learning motivation, the system effectively improved the learning motivation of all learners, particularly those with lower self-regulated learning abilities, field-independent cognitive style, and different levels of prior knowledge. Additionally, learners’ technology acceptance of the system exceeded the median, and their satisfaction with utilizing the integrated AI chatbot, except for concerns related to personal privacy protection, also surpassed the median. Interview results suggested that learners generally perceived the integrated generative and knowledge-based AI chatbot for video-based self-directed learning as more ideal compared to solely relying on ChatGPT. In conclusion, this study successfully integrated Rasa and ChatGPT to develop a VLS-SIGKAIC to support video-based self-directed learning. This system addressed the limitations of previous chatbots in effectively assisting learners in self-directed learning and significantly improving learners’ learning effectiveness and motivation. Furthermore, this study charts new directions for the application of chatbots within the educational field.
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描述 碩士
國立政治大學
圖書資訊與檔案學研究所
110155007
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0110155007
資料類型 thesis
dc.contributor.advisor 陳志銘zh_TW
dc.contributor.advisor Chen, Chih-Mingen_US
dc.contributor.author (Authors) 陳奕慈zh_TW
dc.contributor.author (Authors) Chen, Yi-Cihen_US
dc.creator (作者) 陳奕慈zh_TW
dc.creator (作者) Chen, Yi-Cihen_US
dc.date (日期) 2024en_US
dc.date.accessioned 5-Aug-2024 14:51:55 (UTC+8)-
dc.date.available 5-Aug-2024 14:51:55 (UTC+8)-
dc.date.issued (上傳時間) 5-Aug-2024 14:51:55 (UTC+8)-
dc.identifier (Other Identifiers) G0110155007en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/152928-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 圖書資訊與檔案學研究所zh_TW
dc.description (描述) 110155007zh_TW
dc.description.abstract (摘要) 影片為自主學習常用的一種教學媒體，經常被應用於線上學習與翻轉教學。然而，學習者在使用影片進行自主學習時，常常會因為缺乏觀看影片的動機、缺少學習同伴，抑或教師解答學習問題等因素而影響其學習表現。因此，如何有效提升學習者使用影片進行自主學習時的學習成效與學習動機，一直是重要的研究議題。過去已有少數研究嘗試將聊天機器人技術融入於影片自主學習，然而，這些研究所發展的聊天機器人，其對話資訊通常係由人工制定，並受限於資料庫建立的語料範圍，因此無法完整且精準地回覆學習者在學習過程中的提問，致使無法有效輔助學習者進行自主學習。隨著生成式人工智慧聊天機器人技術的迅速發展，OpenAI於2022年推出之聊天生成預訓練轉換器（ChatGPT），讓輔助學習之聊天機器人發展產生突破性的發展。許多研究指出，ChatGPT能夠提供多樣的功能來輔助教師與學習者進行教與學。然而，雖然ChatGPT基於大型語言模型具有廣博之可對話語料，但與使用者進行對話時，可能會生成錯誤的應答資訊，也無法回答跟特定情境具有關聯的問題。相較之下，Rasa為一種可以利用其所提供的自然語言理解與回應框架，來建置適合應用於特定情境之聊天機器人。因此，本研究使用Rasa來建置由專家知識組成的小型語料庫，並結合ChatGPT來補足Rasa缺少廣博知識的問題，開發出一種更具實用性之整合生成式與知識型之AI聊天機器人，來更有效的輔以學習者進行影片自主學習。 本研究採用單一實驗組前後測設計，以桃園市某高中一年級共36名學生為研究對象，探討使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以學習者進行影片自主學習，是否有助於提升學習者的學習成效與學習動機，並且能否帶來良好的科技接受度與聊天機器人優使性感受。此外，亦探討學習者對於聊天機器人的優使性感受是否與學習成效、學習動機，以及科技接受度具有顯著的相關性。另外，也進一步探討使用此一系統輔以自主學習之高低不同自律能力、不同認知風格，以及高低不同先備知識的學習者，在學習成效、學習動機、科技接受度，以及聊天機器人優使性感受上是否具有顯著的差異。最後，本研究亦採用半結構深度訪談法，了解學習者使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以進行影片自主學習的學習歷程、感受與建議。 研究結果發現，無論是全體、高低不同自律能力、不同認知風格，還是高低不同先備知識的學習者使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以進行影片自主學習皆能夠帶來顯著的學習成效提升。再者，學習者在使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以進行影片自主學習時，對於與AI聊天機器人的互動像真人對話一般的感受程度，跟學習成效具有顯著關聯。在學習動機上，「具整合生成式與知識型AI聊天機器人支援之影片學習系統」能有效地提升全體、低自律能力、場地獨立型，以及高低不同先備知識的學習者使用影片進行自主學習的學習動機。此外，學習者對於使用「具整合生成式與知識型AI聊天機器人支援之影片學習系統」輔以進行影片自主學習的科技接受度高於中位數，且除了對於學習者的隱私保護之外，學習者對於整合生成式與知識型AI聊天機器人的優使性感受亦均高於中位數。最後，根據訪談結果顯示，學習者普遍認為相較於單獨使用ChatGPT輔助進行自主學習，採用本研究所開發的整合生成式與知識型AI聊天機器人輔以進行影片自主學習會更加理想。 綜合以上所述，本研究成功結合Rasa與ChatGPT工具，發展出一個「整合生成式與知識型AI聊天機器人之影片自主學習系統」，改善過去聊天機器人無法有效輔助學習者進行自主學習的問題，並且顯著提升了學習者的學習成效與學習動機。此外，本研究為聊天機器人在教育領域的應用，開展了新的發展方向。zh_TW
dc.description.abstract (摘要) Video is commonly used for self-directed learning, especially in online courses and flipped classrooms. However, learners who engage in self-directed learning through videos often face challenges such as lack of learning motivation, absence of peer support or teachers to respond their learning questions, all of which can impact their learning effectiveness. Therefore, effectively improving learners’ learning motivation and learning effectiveness when using videos for self-directed learning is an essential research issue in educational settings. Previous studies have explored the integration of chatbot technology into video-based self-directed learning. However, these chatbots developed typically rely on manually-crafted dialogues constrained by the corpus established in the database, resulting in limitations in their ability to accurately respond to learner queries and provide effective support. The advent of generative artificial intelligence chatbot technology, exemplified by OpenAI’s ChatGPT launched in 2022, represents a significant advancement in chatbot development for educational purposes. Despite ChatGPT’s broad conversational capabilities based on Large Language Models (LLM), like other generative AI chatbots, it occasionally generates incorrect information or fails to respond questions within specific contexts. In contrast, Rasa provides a natural language understanding and response framework that allows for the creation of chatbots tailored to specific contexts using small, custom-built corpora. Therefore, this study utilized Rasa to build an expert knowledge-based chatbot trained by a human expert based on a small corpus and integrated it with ChatGPT to complement the lack of extensive knowledge in Rasa. This combined approach aims to create a more practical AI chatbot capable of effectively assisting learners in video-based self-directed learning. The study adopts a one-group pretest-posttest design involving 36 Grade 10 learners as the research subjects from a senior high school in Taoyuan City, Taiwan to participant in an instruction experiment. The aim of this study was to investigate whether the “Video Learning System with the Support of Integrating Generative and Knowledge-based AI Chatbots (VLS-SIGKAIC)” can significantly improve learners’ learning effectiveness and motivation in video-based self-directed learning. Additionally, the study evaluates the system’s technology acceptance and the learners’ satisfaction with the chatbot experience. In addition, the study explores the correlation between learners’ satisfaction with the chatbot experience and their learning effectiveness, motivation, and technology acceptance. Furthermore, this study investigates potential differences in learning effectiveness, motivation, technology acceptance, and satisfaction with chatbot usage among learners with different levels of self-regulated learning ability, cognitive styles, and prior knowledge while utilizing this system for self-directed learning. Lastly, semi-structured in-depth interviews are employed to understand learners’ perceptions, feelings, and suggestions towards using VLS-SIGKAIC. Experimental results showed that VLS-SIGKAIC significantly improved learning effectiveness for all learners, regardless of their levels of self-regulated learning ability, cognitive styles, or prior knowledge levels. Furthermore, a significant correlation was observed between learners’ perceptions of interacting with the AI chatbot as if it were a human and their learning effectiveness. In terms of learning motivation, the system effectively improved the learning motivation of all learners, particularly those with lower self-regulated learning abilities, field-independent cognitive style, and different levels of prior knowledge. Additionally, learners’ technology acceptance of the system exceeded the median, and their satisfaction with utilizing the integrated AI chatbot, except for concerns related to personal privacy protection, also surpassed the median. Interview results suggested that learners generally perceived the integrated generative and knowledge-based AI chatbot for video-based self-directed learning as more ideal compared to solely relying on ChatGPT. In conclusion, this study successfully integrated Rasa and ChatGPT to develop a VLS-SIGKAIC to support video-based self-directed learning. This system addressed the limitations of previous chatbots in effectively assisting learners in self-directed learning and significantly improving learners’ learning effectiveness and motivation. Furthermore, this study charts new directions for the application of chatbots within the educational field.en_US
dc.description.tableofcontents 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 4 第三節 研究問題 4 第四節 研究範圍與限制 5 第五節 重要名詞解釋 6 第二章 文獻探討 8 第一節 影片支援自主學習 8 第二節 聊天機器人於教學應用 12 第三節 整合生成式與知識型人工智慧聊天機器人輔助學習 15 第四節 自律能力、認知風格，以及先備知識對於自主學習的成效影響 20 第三章 系統設計 24 第一節 系統架構介紹 24 第二節 系統開發環境與工具 27 第三節 系統介面與功能介紹 28 第四節 提示問題列表與聊天機器人設計 30 第四章 研究設計與實施 37 第一節 研究架構 37 第二節 研究方法 39 第三節 研究對象 40 第四節 研究工具 41 第五節 實驗設計與流程 46 第六節 資料處理與分析 50 第七節 研究實施步驟 53 第五章 實驗結果與分析 56 第一節 學習者向AI聊天機器人提出的問題類型，以及Rasa自然語言理解模型對於學習者提問意圖的判斷準確度 56 第二節 學習者完成之KWL學習單內容分析 57 第三節 採用VLS-SIGKAIC輔以影片自主學習之學習者，在學習成效、學習動機、科技接受度，以及聊天機器人之優使性差異分析 57 第四節 採用VLS-SIGKAIC輔以影片自主學習之不同自律能力學習者，在學習成效、學習動機、科技接受度，以及聊天機器人優使性之差異分析 66 第五節 採用VLS-SIGKAIC輔以影片自主學習之不同認知風格學習者，在學習成效、學習動機、科技接受度，以及聊天機器人優使性之差異分析 75 第六節 採用VLS-SIGKAIC輔以影片自主學習之高低不同先備知識學習者，在學習成效、學習動機、科技接受度，以及聊天機器人優使性之差異分析 84 第七節 訪談質性資料分析 93 第八節 綜合討論 101 第六章 結論與建議 114 第一節 結論 114 第二節 「具整合生成式與知識型AI聊天機器人支援之影片學習系統」之改善建議 120 第三節 未來研究方向 121 參考文獻 125 附錄一、參與研究同意書 138 附錄二、醣類知識測驗 139 附錄三、KWL學習單 140 附錄四、自律能力量表 141 附錄五、團體嵌圖測驗 143 附錄六、學習動機量表 150 附錄七、科技接受度量表 152 附錄八、聊天機器人優使性問卷 154 附錄九、半結構式訪談大綱 156zh_TW
dc.format.extent 6834015 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0110155007en_US
dc.subject (關鍵詞) 影片學習zh_TW
dc.subject (關鍵詞) 自主學習zh_TW
dc.subject (關鍵詞) 聊天機器人zh_TW
dc.subject (關鍵詞) Rasazh_TW
dc.subject (關鍵詞) ChatGPTzh_TW
dc.subject (關鍵詞) Video-based learningen_US
dc.subject (關鍵詞) Self-directed learningen_US
dc.subject (關鍵詞) Chatboten_US
dc.subject (關鍵詞) Rasaen_US
dc.subject (關鍵詞) ChatGPTen_US
dc.title (題名) 整合生成式與知識型人工智慧聊天機器人於影片自主學習之成效影響研究zh_TW
dc.title (題名) The Effects of a Video Learning System with the Support of Integrating Generative and Knowledge-based AI Chatbots on Self-Directed Learning Performanceen_US
dc.type (資料類型) thesisen_US
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