Opportunities and challenges of using generative AI to personalize educational assessment.

IF 3 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Frontiers in Artificial Intelligence Pub Date : 2024-10-07 eCollection Date: 2024-01-01 DOI:10.3389/frai.2024.1460651
Burcu Arslan, Blair Lehman, Caitlin Tenison, Jesse R Sparks, Alexis A López, Lin Gu, Diego Zapata-Rivera
{"title":"Opportunities and challenges of using generative AI to personalize educational assessment.","authors":"Burcu Arslan, Blair Lehman, Caitlin Tenison, Jesse R Sparks, Alexis A López, Lin Gu, Diego Zapata-Rivera","doi":"10.3389/frai.2024.1460651","DOIUrl":null,"url":null,"abstract":"<p><p>In line with the positive effects of personalized learning, personalized assessments are expected to maximize learner motivation and engagement, allowing learners to show what they truly know and can do. Considering the advances in Generative Artificial Intelligence (GenAI), in this perspective article, we elaborate on the opportunities of integrating GenAI into personalized educational assessments to maximize learner engagement, performance, and access. We also draw attention to the challenges of integrating GenAI into personalized educational assessments regarding its potential risks to the assessment's core values of validity, reliability, and fairness. Finally, we discuss possible solutions and future directions.</p>","PeriodicalId":33315,"journal":{"name":"Frontiers in Artificial Intelligence","volume":"7 ","pages":"1460651"},"PeriodicalIF":3.0000,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11491426/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frai.2024.1460651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

In line with the positive effects of personalized learning, personalized assessments are expected to maximize learner motivation and engagement, allowing learners to show what they truly know and can do. Considering the advances in Generative Artificial Intelligence (GenAI), in this perspective article, we elaborate on the opportunities of integrating GenAI into personalized educational assessments to maximize learner engagement, performance, and access. We also draw attention to the challenges of integrating GenAI into personalized educational assessments regarding its potential risks to the assessment's core values of validity, reliability, and fairness. Finally, we discuss possible solutions and future directions.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用生成式人工智能进行个性化教育评估的机遇与挑战。
与个性化学习的积极效果相一致,个性化评估有望最大限度地激发学习者的学习动机和参与度,让学习者展示自己真正的知识和能力。考虑到生成式人工智能(GenAI)的进步,在这篇视角文章中,我们阐述了将GenAI整合到个性化教育评估中的机遇,以最大限度地提高学习者的参与度、成绩和获取能力。我们还提请注意将 GenAI 整合到个性化教育评估中的挑战,即其对评估的核心价值--有效性、可靠性和公平性--的潜在风险。最后,我们讨论了可能的解决方案和未来方向。
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 去求助
来源期刊
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
期刊最新文献
Advancing smart city factories: enhancing industrial mechanical operations via deep learning techniques. Inpainting of damaged temple murals using edge- and line-guided diffusion patch GAN. Catalyzing IVF outcome prediction: exploring advanced machine learning paradigms for enhanced success rate prognostication. Predicting patient reported outcome measures: a scoping review for the artificial intelligence-guided patient preference predictor. A generative AI-driven interactive listening assessment task.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1