{"title":"人工智能强化教育:探索人工智能扫盲对印度北部 Z 世代学习成绩的影响","authors":"Ekamdeep Singh, Prihana Vasishta, Anju Singla","doi":"10.1108/qae-02-2024-0037","DOIUrl":null,"url":null,"abstract":"<h3>Purpose</h3>\n<p>Artificial intelligence (AI) has the potential to address significant challenges in education, innovate learning and teaching practices and achieve SDG 4. However, existing literature often overlooks the behavioural aspects of students regarding AI in education, focusing predominantly on technical and pedagogical dimensions. Hence, this study aims to explore the significant relationships among AI literacy, AI usage, learning outcomes and academic performance of generation Z students in the Indian educational context.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>The study used structural equation modelling (SEM) on Gen Z students born in the years 1997–2012 as a sample population for the research in the north Indian states like Punjab, Haryana, Himachal and regions like Chandigarh and N.C.R. Delhi.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The results established significant positive relationships between AI literacy, AI usage, AI learning outcomes and academic performance. Specifically, higher levels of AI literacy were associated with increased engagement with AI technologies and tools for learning purposes, leading to better learning outcomes and academic performance. 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引用次数: 0
摘要
目的 人工智能(AI)具有应对教育领域重大挑战、创新学习和教学实践以及实现可持续发展目标 4 的潜力。 然而,现有文献往往忽视了学生在教育中使用人工智能的行为方面,而主要关注技术和教学层面。因此,本研究旨在探讨印度教育背景下 Z 世代学生的人工智能素养、人工智能使用、学习成果和学业成绩之间的重要关系。研究采用结构方程建模法(SEM),以 1997-2012 年出生的 Z 世代学生为样本,在印度北部旁遮普邦、哈里亚纳邦、喜马偕尔邦以及昌迪加尔和新德里等地区进行研究。具体而言,较高的人工智能素养与更多地将人工智能技术和工具用于学习目的相关联,从而带来更好的学习成果和学业成绩。研究的局限性/意义研究的意义包括将人工智能教育计划纳入课程、优先考虑教育工作者的专业发展计划以及确保每个学生都能公平地获得人工智能技术的重要性。原创性/价值本研究通过研究人工智能素养、人工智能使用、人工智能学习成果和学业成绩等变量,并开发出一种以前从未研究过的模型,引入了一个新的视角。它提供了一个新的论述,并提出了一个独特的框架,将人工智能注入课程设计、教育者赋权、健全的评估机制和可持续实践结合在一起。
AI-enhanced education: exploring the impact of AI literacy on generation Z’s academic performance in Northern India
Purpose
Artificial intelligence (AI) has the potential to address significant challenges in education, innovate learning and teaching practices and achieve SDG 4. However, existing literature often overlooks the behavioural aspects of students regarding AI in education, focusing predominantly on technical and pedagogical dimensions. Hence, this study aims to explore the significant relationships among AI literacy, AI usage, learning outcomes and academic performance of generation Z students in the Indian educational context.
Design/methodology/approach
The study used structural equation modelling (SEM) on Gen Z students born in the years 1997–2012 as a sample population for the research in the north Indian states like Punjab, Haryana, Himachal and regions like Chandigarh and N.C.R. Delhi.
Findings
The results established significant positive relationships between AI literacy, AI usage, AI learning outcomes and academic performance. Specifically, higher levels of AI literacy were associated with increased engagement with AI technologies and tools for learning purposes, leading to better learning outcomes and academic performance. The findings demonstrated that AI literacy plays a crucial role in providing effective learning experiences and fostering skills such as problem-solving and critical thinking among Gen Z students.
Research limitations/implications
The implications of the study include the significance of integrating AI education initiatives into curricula, prioritising professional development programmes for educators and making sure that every student has equitable access to AI technologies.
Originality/value
The study introduces a novel perspective by examining variables such as AI literacy, AI usage, AI learning outcomes and academic performance and developing a model that has not been previously studied. It provides a new discourse and proposes a framework uniquely combining AI-infused curriculum design, educator empowerment, robust assessment mechanisms and sustainable practices.
期刊介绍:
QAE publishes original empirical or theoretical articles on Quality Assurance issues, including dimensions and indicators of Quality and Quality Improvement, as applicable to education at all levels, including pre-primary, primary, secondary, higher and professional education. Periodically, QAE also publishes systematic reviews, research syntheses and assessment policy articles on topics of current significance. As an international journal, QAE seeks submissions on topics that have global relevance. Article submissions could pertain to the following areas integral to QAE''s mission: -organizational or program development, change and improvement -educational testing or assessment programs -evaluation of educational innovations, programs and projects -school efficiency assessments -standards, reforms, accountability, accreditation, and audits in education -tools, criteria and methods for examining or assuring quality