Leveraging In-Context Online Discussion of Course Materials to Enhance Student Engagement and Learning
Leveraging In-Context Online Discussion of Course Materials to Enhance Student Engagement and Learning
批准号:
1915724
负责人:
Marc Facciotti
金额:
$127.12万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-10-01 至 2024-09-30
中文摘要
在NSF改善本科生STEM教育:教育和人力资源(IUSE:EHR)计划的支持下,该项目旨在通过提高在线学习环境的价值来服务于国家利益。教与学越来越多地发生在网上。通过互联网提供的互动文本和视频有可能降低内容交付的成本,促进比传统内容交付方法更多的学习,并提供更个性化和更公平的教育机会。然而,要想获得成功并被广泛采用,任何新的在线教育平台都必须为学生和教师提供比它所取代的技术更大的价值。提高在线学习环境价值的一个有希望的想法是,利用在线学习环境的能力,通过使用可以向学生和教师提供定制反馈的“智能”互动技术,实现学生和教师之间的互动。在这个项目中,加州大学戴维斯分校和麻省理工学院的研究人员将对如何塑造学生参与在线内容以促进学习达成新的理解。学生的参与度将体现在简短的书面笔记、评论和问题中,学生可以将它们放在文档、网页和视频的页边空白处。通过收集学生对在线资源的感受和参与程度的反馈,教师将能够修改数字资源并重新安排课堂时间,使其更加有效。学生将有机会参与并更深入地思考课程内容,与其他学生联系讨论课程内容,并以新的方式与教师互动。该项目将改善学生和教师对在线内容的体验,增加在线内容交付的价值,并有助于在线资源的个性化。调查人员将建立在NotaBene的基础上,这是一个允许学生在这些内容来源的边缘讨论在线课程内容(PDF、网站和YouTube视频)的系统。调查人员将通过挖掘页边空白处的讨论内容来收集关于学生参与的信息,并将关于学生参与的信息呈现给教师,帮助教师利用这些信息进行课堂设计和与学生互动,并检验增加参与会导致更好的学习结果的假设。研究中的分析模型将考虑三种不同类型的投入:情感投入(衡量学生对他们在网上互动的感受;例如,兴趣;好奇心;困惑;无聊);认知投入(衡量学生思考他们与之互动的深度);以及时间投入(衡量学生花在与在线内容的不同部分互动的时间)。收集这三种敬业度将使调查人员不仅能够独立地观察每种类型的敬业度,而且还可以发现它们是如何相互关联的。了解这些参与类型之间的相互作用应该使教师能够通过更精细和有效的干预来应对。NotaBene的增强、随附的可视化工具以及该项目产生的分析将使学生和教师更深入地了解学生是如何从在线内容中学习的,这种洞察将使教学和内容更正能够克服学习障碍,并促进更多的学生在线参与。NSF的IUSE:EHR计划支持研究和开发项目,以提高所有学生的STEM教育的有效性。通过参与的学生学习路径,该计划支持有前景的实践和工具的创建、探索和实施。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
With support from NSF's Improving Undergraduate STEM Education: Education and Human Resources (IUSE: EHR) program, this project aims to serve the national interest by enhancing the value of online learning environments. Teaching and learning are increasingly happening online. Interactive texts and videos delivered through the Internet have the potential to lower the cost of content delivery, promote greater learning than traditional methods of content delivery, and provide more personalized and equitable access to education. To be successful and broadly adopted, however, any new online educational platform must provide greater value for the students and instructors than the technologies that it replaces. One promising idea to enhance the value of online learning environments is to leverage their ability to enable interactivity between students and instructors by using "smart" interactive technologies that can provide customized feedback to both groups. In this project, researchers at the University of California, Davis and Massachusetts Institute of Technology will build new understandings of how student engagement with online content can be shaped to enhance learning. Student engagement will be captured in short written notes, comments, and questions that students place in the margins of documents, web pages, and videos. By capturing feedback about how students feel about and engage with online resources, instructors will be able to modify digital resources and restructure classroom time to be more effective. Students will get an opportunity to engage with and reflect more deeply on the course content, connect with other students to discuss course content, and engage the instructor in new ways. The project will improve students' and instructors' experiences with online content, increase the value of online content delivery, and contribute to the personalization of online resources.The investigators will build upon NotaBene, a system that allows students to discuss online course content (PDFs, websites, and YouTube videos) in the margins of those content sources. The investigators will gather information about student engagement by mining the discussion content in the margins and will present information about student engagement to instructors, help the instructors make use of this information for class design and for interacting with students, and test the hypothesis that increasing engagement leads to better learning outcomes. The analytical models in the research will consider three distinct types of engagement: emotional engagement (a measure of how students feel about what they are interacting with online; e.g., interest;curiosity; confusion; boredom); cognitive engagement (a measure of how deeply students are thinking about what they are interacting with); and temporal engagement (a measure of how much time students are spending interacting with different parts of the online content). Collecting these three measures of engagement will allow the investigators not only to look at each type of engagement independently but also to uncover how they are interrelated. Understanding the interplay between these types of engagement should enable instructors to respond with more finely tuned and effective interventions. The enhancements to NotaBene, the accompanying visualization tools, and the analyses that result from this project will give students and instructors greater insight into how students are learning from online content, and this insight will enable instructional and content corrections to overcome barriers to learning and facilitate greater student engagement online. NSF's IUSE: EHR program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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New Methods for Confusion Detection in Course Forums: Student, Teacher, and Machine
课程论坛中混淆检测的新方法:学生、教师和机器
DOI:
10.1109/tlt.2021.3123266
发表时间:
2021
期刊:
IEEE Transactions on Learning Technologies
影响因子:
3.7
作者:
[Geller, Shay A., Gal, Kobi, Segal, Avi, Sripathi, Kamali, Kim, Hyunsoo G., Facciotti, Marc T., Igo, Michele, Hoernle, Nicholas, Karger, David]
通讯作者:
Karger, David
Confused and beyond: detecting confusion in course forums using students' hashtags
困惑与超越:使用学生的主题标签检测课程论坛中的困惑
DOI:
10.1145/3375462.3375485
发表时间:
2020
期刊:
LAK '20: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge
影响因子:
--
作者:
[Geller, Shay A., Hoernle, Nicholas, Gal, Kobi, Segal, Avi, Zhang, Amy X., Karger, David, Facciotti, Marc T., Igo, Michele]
通讯作者:
Igo, Michele
lets-discuss: Analyzing student affect in course forums using emoji.
让讨论:使用表情符号分析学生在课程论坛中的影响。
DOI:
--
发表时间:
2022
期刊:
Proceedings of the 15th International Conference on Educational Data Mining
影响因子:
--
作者:
[Blobstein, A., Gal, K., Karger, D., Facciotti, M., Kim, H., Almahmoud, J., Sripathi, K.]
通讯作者:
Sripathi, K.
Spotlights: Designs for Directing Learners' Attention in a Large-Scale Social Annotation Platform
焦点:在大型社交注释平台中引导学习者注意力的设计
DOI:
10.1145/3555598
发表时间:
2022
期刊:
Proceedings of the ACM on Human-Computer Interaction
影响因子:
--
作者:
[Almahmoud, Jumana, Jahanbakhsh, Farnaz, Facciotti, Marc, Igo, Michele, Sripathi, Kamali, Gal, Kobi, Karger, David]
通讯作者:
Karger, David
Seeding Course Forums using the Teacher-in-the-Loop
使用教师在环中播种课程论坛
DOI:
10.1145/3448139.3448142
发表时间:
2021
期刊:
LAK21: 11th International Learning Analytics and Knowledge Conference
影响因子:
--
作者:
[Shusterman, Einat, Kim, Hyunsoo Gloria, Facciotti, Marc, Igo, Michele, Sripathi, Kamali, Karger, David, Segal, Avi, Gal, Kobi]
通讯作者:
Gal, Kobi
Collaborative Research: Chromatin Modification in Archaea and its Role in Gene Expression
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批准号:1517797
-
项目类别:Standard Grant
-
资助金额:$14.52万
-
财政年份:2015
-
负责人:Marc Facciotti
-
依托单位:
Dissertation Research: Decoding the dynamics of cryptic microscale biogeochemical cycling in a phototropic consortium
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批准号:1310166
-
项目类别:Standard Grant
-
资助金额:$2.0万
-
财政年份:2013
-
负责人:Marc Facciotti
-
依托单位:
Microbial Genome Sequencing: High-Resolution Phylogenomics of Halophilic Archaea
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批准号:0949453
-
项目类别:Standard Grant
-
资助金额:$72.47万
-
财政年份:2009
-
负责人:Marc Facciotti
-
依托单位:
Postdoctoral Research Fellowship in Microbial Biology for FY 2004
-
批准号:0400598
-
项目类别:Fellowship Award
-
资助金额:$10.0万
-
财政年份:2004
-
负责人:Marc Facciotti
-
依托单位:
国内基金
海外基金
基于Context建模的基因组数据压缩研究
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批准号:61861045
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项目类别:地区科学基金项目
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资助金额:35.0万元
-
批准年份:2018
-
负责人:陈建华
-
依托单位:
Focus+Context支持的群集三维对象变形可视化
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批准号:41671381
-
项目类别:面上项目
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资助金额:65.0万元
-
批准年份:2016
-
负责人:应申
-
依托单位:
基于Context建模的熵编码及其应用研究
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批准号:61062005
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项目类别:地区科学基金项目
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资助金额:22.0万元
-
批准年份:2010
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负责人:陈建华
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依托单位: