From Data Work to Data Science: Getting Past the Gatekeepers
From Data Work to Data Science: Getting Past the Gatekeepers
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从数据工作到数据科学：越过把关人
DOI：
10.1145/3568812.3603468
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
DiSalvo, Betsy
中科院分区：
文献类型：
--
作者：
Schenck, Lara L.;DiSalvo, Betsy
虽然许多计算教育研究都集中在正规的K-12和本科CS教育上，但越来越多的工作正在探索计算职业的替代途径[7，16]，计算教育的替代结果[15]以及工作场所社区的成人学习[9，13]。在这种情况下，我们正在研究新手友好的计算工作作为计算职业生涯的途径。新颖友好的计算工作是我们用来描述具有低进入门槛的计算活动的短语，用于正式CS空间之外的真实上下文，并且是合法的计算活动，例如，数据工作[13]、网页设计[5]和Salesforce CRM [9]。通过真实的工作实践学习是一条很有前途的计算机职业道路，因为它比编码训练营和在线课程带来更低的财务和可找到性障碍。然而，计算中的守门文化认为Excel，HTML/CSS和JSON等新手友好的工具与“真实的”编程不同。此外，新手工作者可能不被认为是计算实践社区的合法外围成员，尽管他们从事合法的计算工作[6，11]。在数据工作作为通往数据科学职业生涯的途径的背景下，我们正在调查工作场所可以做些什么来建立新手友好的计算工作作为计算中可行的职业途径。我们与DataWorks 1合作，DataWorks 1是格鲁吉亚理工学院计算学院的一个组织，该组织从历史上在计算方面处于少数地位的社区中雇用人员作为数据研究员，进行为期一年的工作培训计划。在前六个月，数据研究员学习Excel，Python和关键数据素养，同时为客户项目执行数据输入，清理和注释工作。在第二个六个月，数据研究员专注于工作和寻找他们的下一个角色。利用参与式行动研究的主题[3]，第一作者在非正式途径计算方面的生活经验，以及情境学习理论[8]，我们开始调查以下研究问题：在一项试点研究中，我们设计了一个职业发展课程，其中包括职业愿景，专业网络，求职心态和求职准备的模块，为期六周，提供给四名数据研究员。通过讲座和讨论为基础的研讨会，脚手架专业网络，非正式的“职业聊天”与客人，并支持工作时间与主持人作为职业教练，课程的目的是让参与者掌握技能，在计算中导航守门。我们对参与者进行的前后访谈的定性分析发现，在研讨会之后，参与者更有战略性地谈论求职，表达了建立新的专业联系的信心，并计划在求职中利用个人和专业网络，而不仅仅是在线求职板。鉴于参与者的反馈意见，职业发展应该在数据研究员的任期内更早开始，更长时间，我们将再次提供课程，为期六个月。在此迭代中，我们将引入DataWorks之外的机会的活动，例如，参加当地的数据科学会议未来的工作将调查这些活动如何挑战保持计算现状的看门人[2，10]。
While much computing education research focuses on formal K-12 and undergraduate CS education, a growing body of work is exploring alternative pathways to computing careers [7, 16], alternative outcomes for computing education [15], and adult learning in workplace communities [9, 13]. Within this context, we are studying novice-friendly computational work as a pathway to computing careers. Novice-friendly computational work is a phrase we use to describe computing activities that have a low barrier to entry, are used in authentic contexts outside formal CS spaces, and are legitimate computational activities, e.g., data work [13], web design [5], and Salesforce CRM [9]. Learning through authentic work practices is a promising pathway to computing careers because it poses lower financial and findability barriers than coding bootcamps [14] and online courses [4]. However, gatekeeping culture in computing deems novice-friendly tools like Excel, HTML/CSS, and JSON distinct from “real” programming [12]. Further, novice workers may not be considered legitimate peripheral members of computing communities of practice despite engaging in legitimate computational work [6, 11].In the context of data work as a pathway to data science careers, we are investigating what workplaces can do to establish novice-friendly computational work as a viable career pathway in computing. We partner with DataWorks1, an organization in Georgia Tech’s College of Computing that hires people from communities historically minoritized in computing as Data Fellows for a one-year work-training program. In their first six months, Data Fellows learn Excel, Python, and critical data literacy while they perform data entry, cleaning, and annotation work for client projects. In their second six months, Data Fellows focus on work and finding their next role. Leveraging themes from participatory action research [3], the first author’s lived experience in informal pathways to computing, and theories of situated learning [8], we are beginning to investigate the following research questions:In a pilot study, we designed a career development curriculum that included modules in career visioning, professional networking, job search mindset, and job search preparation delivered over six weeks to four Data Fellows. Through lecture and discussion-based workshops, scaffolded professional networking, informal "career chats" with guests, and supported work time with the facilitator acting as career coach, the curriculum aimed to equip participants with skills to navigate gatekeeping in computing. Our qualitative analysis of pre- and post-interviews with participants found that, following the workshops, participants spoke about job search more strategically, voiced increased confidence in making new professional connections, and planned to leverage personal and professional networks in their job search instead of only online job boards.Given participants’ feedback that the career development should start earlier and go longer in the Data Fellows’ term, we are delivering the curriculum again, spread out over six months. In this iteration, we are incorporating activities that introduce opportunities outside of DataWorks, e.g., attending a local data science meetup. Future work will investigate how such activities can challenge gatekeeping that preserves the status quo in computing [2, 10].
搜索中迷失：最终用户程序员的信息查找困难
DOI：
--
发表时间：
2013
期刊：
ASIS&T Annual Meeting
影响因子：
--
作者：
Brian Dorn;A. Stankiewicz;Chris Roggi
通讯作者：
Chris Roggi
使用内容分析描述女性计算机职业的替代途径
DOI：
10.1145/3545945.3569798
发表时间：
2023
期刊：
Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1
影响因子：
--
作者：
Jia Zhu;Stephanie J. Lunn;Monique S. Ross
通讯作者：
Monique S. Ross
编码训练营
DOI：
10.1145/3440891
发表时间：
2021
期刊：
ACM Transactions on Computing Education (TOCE)
影响因子：
--
作者：
L. Lyon;Emily Green
通讯作者：
Emily Green