跳到主要內容

臺灣博碩士論文加值系統

(44.222.64.76) 您好!臺灣時間:2024/06/14 05:48
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:黃士昕
研究生(外文):HUANG, SHIH-SIN
論文名稱:利用Line Bot 聊天機器人輔助新手增加學習Python 成效
論文名稱(外文):Leveraging Line Bot Chatbot for Enhancing Novice Python Learning Effectiveness
指導教授:葉道明葉道明引用關係
指導教授(外文):Dowming Yeh
口試委員:蔡旭昇李文廷
口試委員(外文):Wen-Tin Lee
口試日期:2023-07-27
學位類別:碩士
校院名稱:國立高雄師範大學
系所名稱:軟體工程與管理學系
學門:電算機學門
學類:軟體發展學類
論文種類:學術論文
論文出版年:2023
畢業學年度:112
語文別:中文
論文頁數:87
中文關鍵詞:聊天機器人程式語言數位學習輔助工具學習成效
外文關鍵詞:Chat BotProgramming languagee-LearningComputer-aided toolsLearning outcomes
相關次數:
  • 被引用被引用:0
  • 點閱點閱:587
  • 評分評分:
  • 下載下載:190
  • 收藏至我的研究室書目清單書目收藏:0
本研究的目的在於探討利用 Line Bot聊天機器人作為輔助工具,以提升新手在學習 Python 程式語言方面的學習成效。在台灣,程式設計已成為國中及高中生必修的科目,並且統計顯示超過 9 成的人使用 Line App 。因此,本研究希望利用 Line Bot 聊天機器人結合這一平台的普及性,來協助新手學習 Python 程式語言的基礎概念和錯誤訊息的理解。在本研究中,我們主要使用 Python 作為程式語言,並搭配 Dialogflow 進行自然語言處理的功能。在聊天機器人的介面設計上,我們採用了選單的方式,讓新手可以透過按鈕方式進行提問和互動。本研究以實驗組和對照組的形式進行,實驗組使用我們所開發的 Line Bot 聊天機器人進行學習,對照組則使用瀏覽器自行尋找答案的方式進行學習。最後,我們對兩組學習者的成績進行比較,並收集實驗組的滿意度問卷以進行敘述性統計分析。
The purpose of this study is to explore the use of the Line Bot chatbot as an auxiliary tool to improve the learning effectiveness of novices in learning the Python programming language. In Taiwan, programming has become a compulsory subject for middle school and high school students, and statistics show that more than 90% of people use Line App. Therefore, this study hopes to use the Line Bot chatbot combined with the popularity of this platform to help novices learn the basic concepts of the Python programming language and the understanding of error messages. In this research, we mainly use Python as a programming language, and use Dialogflow for natural language processing. In the interface design of the chatbot, we adopted the menu method, so that novices can ask questions and interact through buttons. This study is carried out in the form of an experimental group and a control group. The experimental group uses the Line bot chat robot developed by us to learn, and the control group uses the browser to find answers by itself. Finally, we compared the performance of the two groups of learners and collected satisfaction questionnaires from the experimental group for descriptive statistical analysis.
摘要 ............................................................................................................ I
Abstract .................................................................................................... II
目錄 ......................................................................................................... III
表目錄 ..................................................................................................... VI
圖目錄 .................................................................................................... VII
第一章 緒論 .............................................................................................. 1
第一節 研究背景與動機 ............................................................... 1
第二節 研究目的 ........................................................................... 5
第三節 研究限制 ........................................................................... 7
第二章 文獻探討 ...................................................................................... 8
第一節 聊天機器人 ....................................................................... 8
壹、聊天機器人之定義 ...................................................... 8
貳、聊天機器人之歷史和發展 .......................................... 9
參、聊天機器人之工作原理 ............................................ 11
肆、聊天機器人之使用者體驗 ........................................ 13
伍、Line Bot ...................................................................... 15
第二節 自然語言處理(NLP) ....................................................... 16
壹、自然語言處理之定義 ................................................ 16
貳、自然語言處理之歷史和發展 .................................... 16
參、自然語言處理之應用領域 ........................................ 18
第三節 數位學習 ......................................................................... 19
壹、聊天機器人在程式語言教育之應用 ........................ 19
貳、自然語言處理在程式語言教育之應用 .................... 20
參、Ngrok 在程式語言教育之應用 ................................. 21
第三章 研究方法與實作 ........................................................................ 22
第一節 系統架構 ......................................................................... 22
第二節 系統開發工具 ................................................................. 23
壹、Dialogflow .................................................................. 23
貳、Ngrok .......................................................................... 25
參、Webhook ..................................................................... 25
第三節 系統流程 ......................................................................... 26
壹、Line Bot 環境建立 ..................................................... 26
貳、Dialogflow 環境建立 ................................................. 31
參、Python App建立 ........................................................ 35
第四章 研究成果與討論 ........................................................................ 38
第一節 成果展現 ......................................................................... 38
壹、加入好友 .................................................................... 38
貳、圖文選單模式 ............................................................ 40
參、文字聊天模式 ............................................................ 48
第二節 測試環境 ......................................................................... 51
第三節 測驗設計 ......................................................................... 52
第四節 資料分析結果 ................................................................. 53
壹、系統使用前與使用後之比較 .................................... 53
貳、使用滿意度分析 — 敘述性統計 .............................. 55
第五節 討論.................................................................................. 56
第六節 本研究與 Chat Gpt 的比較 ............................................. 58
壹、系統比較 .................................................................... 58
貳、案例比較 .................................................................... 61
第五章 結論與未來方向 ........................................................................ 63
第一節 結論.................................................................................. 63
第二節 未來發展方向 ................................................................. 64
壹、本研究未來可能發展方向 ........................................ 64
貳、本研究結合 Chat GPT 的未來可能發展方向 .......... 65
參考文獻 ................................................................................................. 68
附錄—本研究測驗 ................................................................................. 73
表2.1 聊天機器人之歷史和發展整理 .................................................. 10
表2.2 自然語言處理之歷史列表 .......................................................... 17
表3.1 Dialogflow 之特點 ....................................................................... 23
表4.1 系統使用前與使用後之比較 ...................................................... 54
表4.2 使用滿意度分析之敘述續性統計量分析表.............................. 56
表4.3 Chat GPT 與本系統的比較分析................................................. 59
圖1.1 台灣使用社群平台排名 ................................................................ 3
圖3.1 系統架構圖 .................................................................................. 23
圖3.2 帳號登入 ...................................................................................... 26
圖3.3 建立開發者 .................................................................................. 27
圖3.4 建立 Messaging API .................................................................... 27
圖3.5 輸入Channel 資訊 ...................................................................... 28
圖3.6 Basic setting 頁籤中的 Channel Id 、 Channel secret ................ 28
圖3.7 Messaging API 頁籤中的 Channel access token ........................ 29
圖3.8 進入帳號設置 .............................................................................. 29
圖3.9 建立圖文選單 .............................................................................. 30
圖3.10 設定標題及時間 ........................................................................ 30
圖3.11 圖文選單設計 ............................................................................ 30
圖3.12 創建 Dialogflow 專案 ............................................................... 31
圖3.13 在 Integrations 中選擇 ............................................................... 32
圖3.14 在 Integrations 填入 Channel Id、Channel secret 、 Channel access token ............................................................................................. 32
圖3.15 在 Line Developers 的 Webhook URL 填入 Integrations的Webhook URL ........................................................................................ 33
圖3.16 點選 Intents 並按下 CREATE INTENT 進行創建 .................. 33
圖3.17 設定 Intents 名稱及關鍵字 ....................................................... 34
圖3.18 測試是否回覆正確的 Intents .................................................... 34
圖3.19 取得Dialogflow裡回應的文字及 Intents 分類 ....................... 35
圖 3.20 製作樣板訊息 ............................................................................ 35
圖 3.21 樣板訊息回覆 ............................................................................ 36
圖3.22 回傳至 Dialogflow..................................................................... 36
圖3.23 透過 Ngrok 取得的公開網址 https ........................................... 37
圖3.24 將公開網址貼入 Dialogflow .................................................... 37
圖4.1 Python 小幫手 - QR code 與主頁畫面 ....................................... 39
圖4.2 Python 小幫手 - 對話框頁面 ...................................................... 39
圖4.3 Python 小幫手使用方式 ............................................................. 41
圖4.4 Python 小幫手 - 變數與命名規則對話框頁面 .......................... 42
圖4.5 錯誤程式與訊息範例 .................................................................. 50
圖4.6 Python 小幫手 - 錯誤訊息對話框頁面 ...................................... 50
圖4.7 測驗題目第17題 ........................................................................ 62
圖4.8 與Chat Gpt 案例比較圖 ............................................................. 62
1. Abdul-Kader, S. A., & Woods, J. C. (2015). "Survey on Chatbot Design Techniques in Speech Conversation Systems." International Journal of Advanced Computer Science and Applications, 6(9), pp. 197-208.
2. Aljohani, N. R., & Alfarraj, O. (2019). "Implementation and Evaluation of an Integrated Development Environment for Online Learning. " In 2019 5th International Conference on Information Management, pp. 1-5.
3. Allen, M. (2020). "COVID-19 Pandemic Impact on Online Learning: Examining the Perceptions of University Students in the United States." Journal of Education for Business, 96(4), pp. 189-199.
4. Bahdanau, D., Cho, K., & Bengio, Y. (2014). "Neural Machine Translation by Jointly Learning to Align and Translate." arXiv, preprint arXiv:1409.0473.
5. Bordes, A., Weston, J., & Usunier, N. (2017). "Open question answering with weakly supervised embedding models." In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, pp. 2335-2341.
6. Brandtzaeg, P. B., & Følstad, A. (2017). "Why People Use Chatbots." In Proceedings of the International Conference on Human-Computer Interaction, pp. 517-528.
7. Choi, S., & Kim, S. (2021). "Programming Education with a Chatbot: The Effects of Learning Achievement and Motivation." International Journal of Human-Computer Interaction, 37(8), pp. 812-822.
8. Chomsky, N. (1957). "Syntactic Structures." Walter de Gruyter, pp. 106-108.
9. Collobert, R., & Weston, J. (2008). "A unified architecture for natural language processing: Deep neural networks with multitask learning." In Proceedings of the 25th international conference on Machine learning, pp. 160-167.
10. Dai, H., & Peng, Y. (2020). "A Remote Control System for Programming Learning Based on Ngrok." In 2020 5th International Conference on Automation, Control and Robotics Engineering.
11. Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2018). "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." arXiv, preprint arXiv:1810.04805.
12. Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2018). "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding." arXiv, preprint arXiv:1810.04805.
13. Fadahunsi, O. P., & Adewumi, A. O. (2020). "Design and Implementation of an Intelligent Chatbot for Programming Language Learning." International Journal of Computer Applications, 174(26), pp. 29-35.
14. Goo, J., & Yang, Y. (2018). "AI Chatbot for Programming Education." International Journal of Advanced Science and Technology, 117, pp. 89-98.
15. Hutchins, W. J. (2000). "Early Years in Machine Translation: Memoirs and Biographies of Pioneers." John Benjamins Publishing, pp. 73-86.
16. Jia, C., & Liu, X. (2020). "Applying Dialogflow to Improve Programming Learning Efficiency."
17. Jurafsky, D., & Martin, J. H. (2019). "Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition." Prentice Hall, pp. 14-15.
18. Kim, H., & Kim, J. (2020). "Mobile Chatbot Service for Improving User Experience." In Proceedings of the 2020 4th International Conference on Cloud and Big Data Computing (ICCBDC). IEEE.
19. Kim, J., Lee, J., & Kim, S. (2020). "Development and Evaluation of a Programming Learning Chatbot Based on Deep Learning." International Journal of Advanced Science and Technology, 29(6), pp. 3362-3371.
20. Li, J., Zhang, D., Chen, S., & Feng, B. (2020). "An Intelligent Chatbot for Online Learning: A Case Study in Programming Language Learning.", pp.147-151.
21. Li, W. (2020). "The Impact of COVID-19 Pandemic on Online Education: The Perspectives of Students in a Developing Country." Interactive Learning Environments, pp. 1-16.
22. Liu, B., Zhang, L., & Zhu, F. (2012). "A Survey of Natural Language Processing Techniques for Opinion Mining." IEEE Transactions on Knowledge and Data Engineering, 24(4), pp. 1-16.
23. Meaghan Yuen (2022), "Chatbot market in 2022: Stats, trends, and companies in the growing AI chatbot industry." Retrieved from: https://www.insiderintelligence.com/insights/chatbot-market-stats-trends/
24. Nio, A., Shao, C., Nishida, Y., & Inkpen, D. (2019). "A survey on dialogue systems: Recent advances and new frontiers." ACM Transactions on Interactive Intelligent Systems, vol. 9, no. 3, pp. 1-49.
25. Papangelis, A., Lopes, C. C., Crook, P. A., & Hsieh, M. A. (2019). "Dialog system technology evolution and user expectations: State of the art review." ACM Computing Surveys, vol. 52, no. 6, pp. 1-34.
26. Purnama, B., & Rusdiana, D. (2020). "Intelligent Conversational Agent for Programming Language Learning Using Dialogflow."
27. Purnomo, M. H., & Santoso, H. B. (2019). "Implementation of Ngrok in Python Programming Learning." In 2019 International Conference on Electrical Engineering and Computer Science, pp. 71-75.
28. Salton, G., & McGill, M. J. (1983). "Introduction to Modern Information Retrieval." McGraw-Hill, pp.99-117.
29. Schalkwyk, R. J. (2017). "Speech and language processing for conversational agents: An overview." In Proceedings of the 21st Conference on Computational Natural Language Learning, pp. 1-6.
30. Sharma, N., & Aggarwal, N. (2020). "An Intelligent Chatbot for Programming Language Learning Using Dialogflow."
31. Smutny, P., & Schreiberova, A. (2020). "The Rise of Chatbots: A Review of Recent Developments in Conversational AI." International Journal of Human-Computer Interaction, 36(6), pp. 523-538.
32. Sparck Jones, K., & Willett, P. (1997). "Readings in Information Retrieval." Morgan Kaufmann, 33(4), pp. 294-304.
33. Turing, A. M. (1950). "Computing machinery and intelligence." Mind, 59(236), pp. 433-460.
34. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., & Polosukhin, I. (2017). "Attention is all you need." In Advances in neural information processing systems, pp. 5998-6008.
35. Weaver, W. (1955). "Translation." Machine translation of languages: Fourteen essays, pp. 15-23.
36. Young, S., Gašić, M., & Keizer, S. (2013). "The hidden agenda user simulator: Dialog policy learning with partially observable user simulations." In Proceedings of the 2013 IEEE Spoken Language Technology Workshop, pp. 338-343.
37. 台灣網路資訊中心(2020), 「2020 台灣網路報告」, Retrieved from: https://www.twnic.tw/doc/twrp/202012e.pdf
38. 時時 (2019), 「2018各國上網時數大調查:菲律賓第一、日本墊底」Retrieved from: https://www.bnext.com.tw/article/52231/how-much-time-people-spend-on-surfing-the-internet-in-2018
連結至畢業學校之論文網頁點我開啟連結
註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊