探究生成式AI在不同年级学生中的教育影响,发现其对规范使用影响最大。
Unlocking Learning Potentials: The Transformative Effect of Generative AI in Education Across Grade Levels
- 通过问卷与访谈结合,分析四类学生在六方面学习表现
- 大学生成绩优于高中生,但学习兴趣与自信水平最低
- 学生普遍积极使用AI,未来潜力大但需应对挑战
生成式人工智能(GAI)在教育领域迅速普及,但其在学生中的使用方式和感知仍缺乏系统研究。本研究采用混合调研方法,考察了四个年级学生在六个关键维度(LIPSAL:学习兴趣、自主学习、问题解决、自信心、规范使用、学习乐趣)中受GAI影响的情况。结果显示,GAI对“规范使用”的影响最大,而学习兴趣和自信心水平最低。不同年级间存在显著差异,大学生在整体LIPSAL上表现优于高中生。访谈表明,学生对GAI有较全面理解,态度积极,愿意广泛使用。随着技术成熟,GAI将在教育中发挥更大作用。研究结果有助于理解学生使用差异,为数字教育研究提供依据。
原文摘要 · Abstract (English)
The advent of generative artificial intelligence (GAI) has brought about a notable surge in the field of education. The use of GAI to support learning is becoming increasingly prevalent among students. However, the manner and extent of its utilisation vary considerably from one individual to another. And researches about student's utilisation and perceptions of GAI remains relatively scarce. To gain insight into the issue, this paper proposed a hybrid-survey method to examine the impact of GAI on students across four different grades in six key areas (LIPSAL): learning interest, independent learning, problem solving, self-confidence, appropriate use, and learning enjoyment. Firstly, through questionnaire, we found that among LIPSAL, GAI has the greatest impact on the concept of appropriate use, the lowest level of learning interest and self-confidence. Secondly, a comparison of four grades revealed that the high and low factors of LIPSAL exhibited grade-related variation, and college students exhibited a higher level than high school students across LIPSAL. Thirdly, through interview, the students demonstrated a comprehensive understanding of the application of GAI. We found that students have a positive attitude towards GAI and are very willing to use it, which is why GAI has grown so rapidly in popularity. They also told us prospects and challenges in using GAI. In the future, as GAI matures technologically, it will have an greater impact on students. These findings may help better understand usage by different students and inform future research in digital education.
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