Measuring the Familiarity, Usability, and Concern towards AI-Integrated Education of College Teachers at the Undergraduate Level

Dr. Sahin Sahari
{"title":"Measuring the Familiarity, Usability, and Concern towards AI-Integrated Education of College Teachers at the Undergraduate Level","authors":"Dr. Sahin Sahari","doi":"10.36347/sjahss.2024.v12i05.002","DOIUrl":null,"url":null,"abstract":"Artificial Intelligence (AI) holds immense potential to revolutionize education globally. This research paper investigates how undergraduate college teachers in India perceive AI’s role in education and examines the key dimensions such as familiarity, usability, concerns, and challenges. To address this complex issue, researcher adopted a mixed-methods research design, combining both quantitative and qualitative research approaches. Data was collected through a structured online google form survey questionnaire that was administered to the randomly selected 441 sample of undergraduate college teachers in India by stratified random sampling technique from the five different states of the country (West Bengal, Bihar, Jharkhand, Gujrat, & Tripura). Here researcher used the basic descriptive statistics such as mean, median and standard deviations to summarize survey responses. On the other side, inferential statistics, such as ‘Confirmatory Factor Analysis’ and chi-square were used. This mixed approach-based investigation revealed distinct patterns in familiarity, usability, concerns, and challenges among the undergraduate college teachers. Notably, male teachers from private institutions exhibited higher familiarity with AI. On the other side, female teachers and private undergraduate college teachers demonstrated more favourable perceptions of AI’s usability in education. But concerns, especially regarding privacy and security, were more pronounced among female teachers. Challenges were also highlighted, with a shared dissatisfaction among undergraduate college teachers concerning institutional support, while technical support and infrastructure issues loomed large. Confirmatory Factor Analysis (CFA) validated positive relationships between familiarity and both usability and concerns, emphasizing the vital role of enhancing AI knowledge to shape perceptions positively and reduce concerns.","PeriodicalId":446153,"journal":{"name":"Scholars Journal of Arts, Humanities and Social Sciences","volume":" 15","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scholars Journal of Arts, Humanities and Social Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36347/sjahss.2024.v12i05.002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Artificial Intelligence (AI) holds immense potential to revolutionize education globally. This research paper investigates how undergraduate college teachers in India perceive AI’s role in education and examines the key dimensions such as familiarity, usability, concerns, and challenges. To address this complex issue, researcher adopted a mixed-methods research design, combining both quantitative and qualitative research approaches. Data was collected through a structured online google form survey questionnaire that was administered to the randomly selected 441 sample of undergraduate college teachers in India by stratified random sampling technique from the five different states of the country (West Bengal, Bihar, Jharkhand, Gujrat, & Tripura). Here researcher used the basic descriptive statistics such as mean, median and standard deviations to summarize survey responses. On the other side, inferential statistics, such as ‘Confirmatory Factor Analysis’ and chi-square were used. This mixed approach-based investigation revealed distinct patterns in familiarity, usability, concerns, and challenges among the undergraduate college teachers. Notably, male teachers from private institutions exhibited higher familiarity with AI. On the other side, female teachers and private undergraduate college teachers demonstrated more favourable perceptions of AI’s usability in education. But concerns, especially regarding privacy and security, were more pronounced among female teachers. Challenges were also highlighted, with a shared dissatisfaction among undergraduate college teachers concerning institutional support, while technical support and infrastructure issues loomed large. Confirmatory Factor Analysis (CFA) validated positive relationships between familiarity and both usability and concerns, emphasizing the vital role of enhancing AI knowledge to shape perceptions positively and reduce concerns.
衡量大学本科教师对人工智能融合教育的熟悉程度、可用性和关注度
人工智能(AI)蕴含着彻底改变全球教育的巨大潜力。本研究论文调查了印度大学本科教师如何看待人工智能在教育中的作用,并研究了熟悉程度、可用性、担忧和挑战等关键维度。为解决这一复杂问题,研究人员采用了混合方法研究设计,结合了定量和定性研究方法。研究人员采用分层随机抽样技术,从印度五个不同的邦(西孟加拉邦、比哈尔邦、恰尔康得邦、古吉拉特邦和特里普拉邦)随机抽取了 441 名本科院校教师,通过结构化在线谷歌调查问卷收集数据。在此,研究人员使用了基本的描述性统计,如平均值、中位数和标准偏差来总结调查反馈。另一方面,研究人员还使用了 "确认因素分析 "和卡方等推理统计方法。这项基于混合方法的调查揭示了本科院校教师在熟悉程度、可用性、关注点和挑战方面的独特模式。值得注意的是,来自民办院校的男教师对人工智能的熟悉程度较高。另一方面,女教师和民办本科院校教师对人工智能在教育中的可用性表现出更多的好感。但女教师的担忧,尤其是对隐私和安全的担忧更为明显。挑战也很突出,本科院校教师对机构支持普遍不满,而技术支持和基础设施问题也很突出。确认性因子分析(CFA)验证了熟悉程度与可用性和顾虑之间的正相关关系,强调了加强人工智能知识对形成积极看法和减少顾虑的重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信