人工智慧科技應用層面越來越深入我們的生活當中為人類帶來便利性，同時隨之而來因人工智慧科技產生新的社會性科學議題。經研究卻發現學生在處理社會性科學議題的非形式推理能力是不足的。我們應該重視「人工智慧」、「社會性科學議題」和「非形式推理能力」這三者交織而成會影響未來人類社會發展的重要研究問題。 本研究目的有四：一、試著初探人工智慧相關社會性科學議題基礎教學之研究；二、嘗試設計適合國內的人工智慧基礎課程並實際於國小現場實施教學；三、尋找能增進培養學生非形式推理能力之教學方式；四、了解國小高年級學生對人工智慧態度的影響。 本研究採用實驗研究法之準實驗設計，研究對象為兩班國小五年級學生，一班為實驗組共二十六人，一班為控制組共二十三人。本研究分別對兩班實施半學期共九週，進行一套「結合框架理論與拼圖法之合作學習」與「一般合作學習」學習活動，之後在對兩班學生的非形式推理能力與對人工智慧的態度進行評量。在非形式推理能力評量方面，研究者是研究處理前後分別以「國小高年級學生對人工智慧相關社會性科學議題非形式推理能力問卷」進行前、後測各一次，再利用Wu & Tsai (2007) 「社會性科學議題非形式推理綜合分析析架構」進行質性資料和量化資料的分析；在對人工智慧的態度評量方面，研究者在研究處理前後分別以「國小高年級學生對人工智慧的態度量表」進行前、後測各一次。 研究結果發現本研究此兩種的「合作學習」學習表現效果都好，而「基於框架理論及拼圖法之合作學習」在社會性科學議題非形式推理的「推理模式」、「論證品質」有顯著的提升及成長。本研究還發現實驗組和控制組的學生對人工智慧的相關態度意願有顯著差異存在，實驗組和控制組態度意願均為正向支持，但前測意願分數均大於後測，代表學生認知到人工智慧科技在未來的重要性，而他們選擇輕鬆的當人工智慧的「使用者」，而課程後對當人工智慧的「學習者」或「從業者」意願又下降，而這樣的態度令研究者擔憂。 本研究教學建議：一、非形式推理教學活動加入角色扮演讓學生突破自己立場的框架。二、論證活動應先「重質」再「重量」。未來研究建議：一、在尋找更佳的非形式推理能力的教學方式。二、對人工智慧科技相關態度的研究意願偏低之原因待後面研究者接續探究。 ;The application level of artificial intelligence technology is getting deeper and deeper into our lives to bring convenience to mankind, and at the same time, new Socio-scientific issues have arisen due to artificial intelligence technology. After research, it is found that students′ informal reasoning ability in dealing with Socio-scientific Issues is insufficient. We should attach importance to "artificial intelligence", " socio-scientific Issues " and "informal reasoning ability" intertwined with important research issues that will affect the future development of human society. The purpose of this research is four: Try to explore the basic teaching of artificial intelligence-related Socio-scientific Issues. Try to design a basic course of artificial intelligence suitable for Taiwan and implement teaching on the spot in elementary schools. Find ways to improve the training of students Teaching methods of informal reasoning ability. Understand the influence on senior elementary school students’ attitudes towards artificial intelligence. This research adopts the quasi-experimental design of experimental research. The research objects are two classes of fifth-grade students in elementary school. This study was implemented for two classes for a half-semester and a total of nine weeks. Conduct a set of "Cooperative Learning Combining Framework Theory and Jigsaw Method" and "General Cooperative Learning" learning activities. After that, the research will evaluate the informal reasoning ability of the two classes of students and their attitude towards artificial intelligence. Regarding the assessment of informal reasoning ability, the researcher will conduct a pre-test and post-test with the "Informal Reasoning Ability Questionnaire for Senior Elementary School Students on Socio-scientific Issues Related to Artificial Intelligence" before and after the research and processing. Then use Wu & Tsai (2007) "An integrated framework for analyzing learners’ informal reasoning′′ to analyze qualitative and quantitative data. Regarding the assessment of attitudes towards artificial intelligence, the researchers conducted pre-test and post-test using the "Elementary School Seniors′ Attitudes Towards Artificial Intelligence Scale" before and after the research and processing. The results of the study showing that the two types of "cooperative learning" in this study performed well. And "cooperative learning based on frame theory and jigsaw method" has significantly improved and grown in the "Reasoning modes" and " Reasoning quality" of informal reasoning on Socio-scientific issues. This study also found that the experimental group and the control group have significant differences in their attitudes and willingness to artificial intelligence. The attitude and willingness of the experimental group and the control group are both positive support. However, the scores of pre-test willingness are greater than those of post-test, indicating that students recognize the importance of artificial intelligence technology in the future. And they choose to be "users" of artificial intelligence easily, and their willingness to be "learners" or "practitioners" of artificial intelligence declines after the course and this attitude worries the researcher.
The teaching suggestions of this research are as follows: 1. Adding role-playing to the informal reasoning teaching activities allows students to break through the framework of their own position. 2. The argumentation activities should "focus on quality" and then " quantity".
Future research recommendations are as follows: 1. We are looking for better teaching methods for informal reasoning. 2. The reasons for the low willingness to study attitudes related to artificial intelligence technology will be explored by later researchers.
