透明度和同意:学生对教育数据分析场景的看法

IF 0.8 4区管理学 Q3 INFORMATION SCIENCE & LIBRARY SCIENCE

Portal-Libraries and the Academy Pub Date : 2023-07-01 DOI:10.1353/pla.2023.a901565

Kyle M. L. Jones, Abigail H. Goben, Michael R. Perry, Mariana Regalado, D. Salo, Andrew D. Asher, M. Smale, Kristin A. Briney

{"title":"透明度和同意:学生对教育数据分析场景的看法","authors":"Kyle M. L. Jones, Abigail H. Goben, Michael R. Perry, Mariana Regalado, D. Salo, Andrew D. Asher, M. Smale, Kristin A. Briney","doi":"10.1353/pla.2023.a901565","DOIUrl":null,"url":null,"abstract":"abstract:Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts the student perspective by researching three unique futurized scenarios rooted in real-life systems and practices. Findings highlight student acceptance of data mining and analytics with particular limitations, namely transparency about analytics and consent mechanisms. Without such limitations, institutions risk losing their students’ trust.","PeriodicalId":51670,"journal":{"name":"Portal-Libraries and the Academy","volume":"1 1","pages":"485 - 515"},"PeriodicalIF":0.8000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Transparency and Consent: Student Perspectives on Educational Data Analytics Scenarios\",\"authors\":\"Kyle M. L. Jones, Abigail H. Goben, Michael R. Perry, Mariana Regalado, D. Salo, Andrew D. Asher, M. Smale, Kristin A. Briney\",\"doi\":\"10.1353/pla.2023.a901565\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"abstract:Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts the student perspective by researching three unique futurized scenarios rooted in real-life systems and practices. Findings highlight student acceptance of data mining and analytics with particular limitations, namely transparency about analytics and consent mechanisms. Without such limitations, institutions risk losing their students’ trust.\",\"PeriodicalId\":51670,\"journal\":{\"name\":\"Portal-Libraries and the Academy\",\"volume\":\"1 1\",\"pages\":\"485 - 515\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Portal-Libraries and the Academy\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1353/pla.2023.a901565\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Portal-Libraries and the Academy","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1353/pla.2023.a901565","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}

引用次数: 0

摘要

高等教育数据挖掘和分析，如学习分析，可以改善学习体验和成果。然而，这种做法充斥着学生的隐私问题和其他道德问题。在教育数据分析的设计中考虑学生的隐私期望和偏好是至关重要的。本研究通过研究根植于现实生活系统和实践的三种独特的未来情景，为学生的观点提供了前沿。研究结果强调了学生对数据挖掘和分析的接受程度，但存在特定的局限性，即分析和同意机制的透明度。没有这样的限制，院校就有可能失去学生的信任。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Transparency and Consent: Student Perspectives on Educational Data Analytics Scenarios

abstract:Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts the student perspective by researching three unique futurized scenarios rooted in real-life systems and practices. Findings highlight student acceptance of data mining and analytics with particular limitations, namely transparency about analytics and consent mechanisms. Without such limitations, institutions risk losing their students’ trust.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Portal-Libraries and the Academy INFORMATION SCIENCE & LIBRARY SCIENCE-

CiteScore

1.80

自引率

8.30%

发文量