- 期刊
高中生人工智慧學習態度對學習成就影響之研究
A study on the impact of high school students' artificial Intelligence learning attitudes on learning achievement
摘要
研究背景：隨著科技不斷創新與突破，人工智慧應用範疇也日益廣泛，從醫療、交通、商業到教育等，正持續改變我們的生活。人工智慧的競爭力，來自於教育的扎根，因此在十二年國教課程綱要中的教學內容，已將資訊科技教育相關課程納入基礎教育的實踐範圍，同時亦從結合生活情境的應用來引發學生興趣。研究目的：有鑑於人工智慧課程落實於教育現場之重要性，本研究主要探討高中生人工智慧學習態度對於學習成就之影響與關係，透過分析不同變項，探討高中生在人工智慧學習態度與學習成就之差異。研究方法：本研究為相關性研究，主要的依變項為人工智慧的學習成就；自變項為人工智慧的學習態度。資料分析以量化統計為主，其中包含描述統計、Two-Way ANOVA、皮爾森積差相關與迴歸分析等。研究結果：研究結果發現，透過人工智慧課程，高中生對於人工智慧的內容能獲得一般程度以上的理解力，並且學習興趣和學習成就呈現正相關。此外，以人工智慧學習成就結果而言，自然組學生成績優於社會組；而學習態度量表的結果，則呈現男生的學習態度高於女生。研究結論：從研究結果得知，高中學生對於人工智慧的學習興趣，對於學習成就具有一定程度的預測力，因此，教師若能有效引發學生對於人工智慧的學習興趣，則能引發學習者更高的學習成就。
並列摘要
Background: The application of artificial intelligence is becoming more extensive with the rapid development of science and technology. It's made progress in many areas, like medical care, transportation, business, education, etc., that changes our lives. However, artificial intelligence education plays a vital role in preserving future competitiveness. Therefore, the courses in information technology have been included in the scope of 12-year national curriculum guidelines. Simultaneously, the curriculum aims to stimulate students' interest by integrating real-life contexts into the applications. Purpose: Considering the importance of AI curriculum implementation in the educational field, this study focused on the influence and relationship between AI learning attitudes and the learning achievement of high school students. By analyzing different variables, this study examines the differences in attitudes and learning achievements among high school students in the context of artificial intelligence learning. Methods: This study is correlational research. It focuses on the dependent variable of AI learning achievement and the independent variable of AI learning attitude. The analyzing result is based on quantitative statistics, including descriptive statistics, two-way ANOVA, Pearson correlation, and regression analysis. Results: The results reveal that high school students could reach an above-average comprehension of AI content through the AI curriculum and that interest in learning and academic achievement are correlated. Meanwhile, the science majors outperformed the non science majors in AI learning achievement, and male students exhibited higher learning attitudes than females. Conclusions: Based on the results, it can be inferred that learning interest has predictive abilities for learning achievement. Therefore, if teachers can effectively stimulate students' interest in AI learning, it can lead to higher levels of learning achievement.