EAGER: Social Media Participation as Indicator of Actors, Awareness, Attitudes, and Activities Related to STEM Education

EAGER：社交媒体参与度作为与 STEM 教育相关的参与者、意识、态度和活动的指标

• 批准号: 1707837
• 负责人: Aditya Johri
• 金额: $ 29.93万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1707837&HistoricalAwards=false
• 关键词: EAGER; Social; Media; Participation; Indicator

A strong and productive STEM workforce is essential for the socio-economic well-being of the nation. Consequently, efforts to improve STEM education are undertaken each year across a range of federal and state agencies and they support thousands of STEM education events, activities, and initiatives. These efforts have been successful to some degree but participation by populations historically underrepresented in STEM continues to lag at a time when STEM workforce requirements are increasing. In order to improve future efforts, it is critical to build a nuanced and empirical understanding of the overall STEM space: What is the nature of issues related to STEM that garner interest? Who shows an interest and participates? What are the outcomes and impact of different STEM related initiatives? This proposed project will use social media data to study these issues and answer such questions. Social media data is an underutilized resource as almost 87% of the American population now participates in some form of social media activity. This project has the potential to improve and increase the impact of STEM education related efforts by illuminating ideas and activities of interest to people, current efforts in place, and what participants share and where. This information can be used for efforts such as broadening participation by better targeting campaigns intended to increase interest in STEM and by connecting individuals and organizations to create more momentum for an idea, event or topic.This study will use Twitter data and will focus on studying: (1) Actors - who participates in STEM education issues? (2) Awareness - what do participants know? (3) Attitudes - what attitude and beliefs do participants hold? (4) Activities - what do the participants do? what activities do they participate in? More specifically, the investigative team will use novel methodology to (a) analyze interaction patterns of the categorized users and create interaction networks by considering nodes as users and edges as the interaction strength; (b) use topic modeling techniques to gain insight about users' awareness of STEM; (c) employ target-specific sentiment mining techniques to gain insight about users' attitudes; (d) use geographic and spatio-temporal analysis, such as Density Based Spatial Clustering of Applications with Noise (DBSCAN), to gain insight about STEM activities. This project has the potential to contribute to our understanding of STEM education from the lens of social media. There is novelty in the approach and the methods of this project that serves to potentially transform how social media in STEM education is utilized.

强大而有效的STEM劳动力对于国家的社会经济福祉至关重要。因此，每年在一系列联邦和州机构中进行改善STEM教育的努力，并支持成千上万的STEM教育活动，活动和倡议。这些努力在某种程度上取得了成功，但是在STEM劳动力需求不断提高的时候，历史上人口不足的人群的参与继续落后。为了改善未来的努力，建立对整体茎空间的细微和经验理解至关重要：与STEM有关的问题的性质是什么？谁表现出兴趣并参加？不同与STEM相关的计划的结果和影响是什么？该建议的项目将使用社交媒体数据研究这些问题并回答此类问题。社交媒体数据是一种未充分利用的资源，因为几乎87％的美国人口现在参与了某种形式的社交媒体活动。该项目有可能通过阐明人们对人们感兴趣的思想和感兴趣的活动，当前的努力以及参与者分享的内容以及在哪里来改善和增加与STEM教育相关的工作的影响。这些信息可用于努力，例如通过更好地定位旨在增加对STEM的兴趣并与个人和组织联系以创造更多想法，事件或主题的动力来扩大参与的努力。这项研究将使用Twitter数据并将重点放在研究上：（1）参与STEM教育问题的演员？ （2）意识 - 参与者知道什么？ （3）态度 - 参与者保持什么态度和信念？ （4）活动 - 参与者做什么？他们参加什么活动？更具体地说，调查团队将使用新颖的方法来（a）分析分类用户的交互模式，并通过将节点视为用户和边缘作为交互强度来创建交互网络； （b）使用主题建模技术来了解用户对STEM的认识； （c）采用特定目标的情感挖掘技术来了解用户态度； （d）使用地理和时空分析，例如基于噪声（DBSCAN）应用的基于密度的空间聚类，以获取有关STEM活动的洞察力。该项目有可能为我们从社交媒体视角理解STEM教育做出贡献。 该方法和该项目的方法具有新颖性，可以改变STEM教育中的社交媒体的利用方式。

项目成果

Use of Twitter across educational settings: a review of the literature

• DOI: 10.1186/s41239-019-0166-x
• 发表时间: 2019-09-25
• 期刊: INTERNATIONAL JOURNAL OF EDUCATIONAL TECHNOLOGY IN HIGHER EDUCATION
• 影响因子: 8.6
• 作者: Malik, Aqdas;Heyman-Schrum, Cassandra;Johri, Aditya
• 通讯作者: Johri, Aditya

ILookLikeAnEngineer: Using Social Media Based Hashtag Activism Campaigns as a Lens to Better Understand Engineering Diversity Issues

ILookLikeAnEngineer：使用基于社交媒体的标签激进主义活动作为更好地理解工程多样性问题的镜头

• 发表时间: 2018
• 期刊: USA.
• 作者: Malik, A;Johri, A;Handa, R;Karbasian, H;Purohit, H
• 通讯作者: Purohit, H

Engineers' Situated Use of Digital Resources to Augment their Workplace Learning Ecology

工程师利用数字资源来增强工作场所学习生态

• DOI: 10.1109/fie49875.2021.9637421
• 发表时间: 2021
• 期刊: 2021 IEEE Frontiers in Education Conference (FIE
• 作者: Le, Hieu-Trung;Johri, Aditya
• 通讯作者: Johri, Aditya

Keeping Curriculum Relevant: Identifying Longitudinal Shifts in Computer Science Topics through Analysis of Q&A Communities

• DOI: 10.1109/fie49875.2021.9637144
• 发表时间: 2021-10
• 期刊: 2021 IEEE Frontiers in Education Conference (FIE)
• 作者: Habib Karbasian;A. Johri

AI for Trustworthiness! Credible User Identification on Social Web for Disaster Response Agencies

人工智能带来可信度！

• 发表时间: 2018
• 期刊: AAAI FSS-18: Artificial Intelligence in Government and Public Sector Proceedings
• 作者: Pandey, Rahul;Purohit, Hemant;Chan, Jennifer;Johri, Aditya
• 通讯作者: Johri, Aditya