When the Tutor Becomes the Student: Design and Evaluation of Efficient Scenario-based Lessons for Tutors

Danielle R. Thomas, Xinyu Yang, Shivang Gupta, A. Adeniran, Elizabeth Mclaughlin, K. Koedinger
{"title":"When the Tutor Becomes the Student: Design and Evaluation of Efficient Scenario-based Lessons for Tutors","authors":"Danielle R. Thomas, Xinyu Yang, Shivang Gupta, A. Adeniran, Elizabeth Mclaughlin, K. Koedinger","doi":"10.1145/3576050.3576089","DOIUrl":null,"url":null,"abstract":"Tutoring is among the most impactful educational influences on student achievement, with perhaps the greatest promise of combating student learning loss. Due to its high impact, organizations are rapidly developing tutoring programs and discovering a common problem- a shortage of qualified, experienced tutors. This mixed methods investigation focuses on the impact of short (∼15 min.), online lessons in which tutors participate in situational judgment tests based on everyday tutoring scenarios. We developed three lessons on strategies for supporting student self-efficacy and motivation and tested them with 80 tutors from a national, online tutoring organization. Using a mixed-effects logistic regression model, we found a statistically significant learning effect indicating tutors performed about 20% higher post-instruction than pre-instruction (β = 0.811, p < 0.01). Tutors scored ∼30% better on selected compared to constructed responses at posttest with evidence that tutors are learning from selected-response questions alone. Learning analytics and qualitative feedback suggest future design modifications for larger scale deployment, such as creating more authentically challenging selected-response options, capturing common misconceptions using learnersourced data, and varying modalities of scenario delivery with the aim of maintaining learning gains while reducing time and effort for tutor participants and trainers.","PeriodicalId":394433,"journal":{"name":"LAK23: 13th International Learning Analytics and Knowledge Conference","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"LAK23: 13th International Learning Analytics and Knowledge Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3576050.3576089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Tutoring is among the most impactful educational influences on student achievement, with perhaps the greatest promise of combating student learning loss. Due to its high impact, organizations are rapidly developing tutoring programs and discovering a common problem- a shortage of qualified, experienced tutors. This mixed methods investigation focuses on the impact of short (∼15 min.), online lessons in which tutors participate in situational judgment tests based on everyday tutoring scenarios. We developed three lessons on strategies for supporting student self-efficacy and motivation and tested them with 80 tutors from a national, online tutoring organization. Using a mixed-effects logistic regression model, we found a statistically significant learning effect indicating tutors performed about 20% higher post-instruction than pre-instruction (β = 0.811, p < 0.01). Tutors scored ∼30% better on selected compared to constructed responses at posttest with evidence that tutors are learning from selected-response questions alone. Learning analytics and qualitative feedback suggest future design modifications for larger scale deployment, such as creating more authentically challenging selected-response options, capturing common misconceptions using learnersourced data, and varying modalities of scenario delivery with the aim of maintaining learning gains while reducing time and effort for tutor participants and trainers.
当导师变成学生:高效情境化导师课程设计与评价
辅导是对学生成绩影响最大的教育方式之一,可能最有希望消除学生的学习损失。由于它的高影响力,组织正在迅速发展辅导项目,并发现了一个共同的问题——缺乏合格的、有经验的导师。这项混合方法调查的重点是短期(~ 15分钟)在线课程的影响,在这些课程中,教师参与基于日常辅导场景的情景判断测试。我们开发了三门课程,内容是关于支持学生自我效能感和动机的策略,并由一家全国性在线辅导机构的80名导师进行了测试。使用混合效应logistic回归模型,我们发现导师在教学后的学习效果比教学前高20%左右(β = 0.811, p < 0.01)。在后测中,导师在选择回答上的得分比构建回答高30%,有证据表明导师只从选择回答问题中学习。学习分析和定性反馈建议未来进行更大规模部署的设计修改,例如创建更具挑战性的选择响应选项,使用学习者来源的数据捕获常见的误解,以及以保持学习成果为目标的不同模式的场景交付,同时减少导师参与者和培训师的时间和精力。
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:481959085
Book学术官方微信