Chatbots: A Tool to Supplement the Future Faculty Mentoring of Doctoral Engineering Students

Q2 Social Sciences International Journal of Doctoral Studies Pub Date : 2020-06-28 DOI:10.28945/4579
S. Mendez, K. Johanson, V. Conley, Kinnis Gosha, Naja Mack, C. Haynes, R. Gerhardt
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引用次数: 8

Abstract

Aim/Purpose: The purpose of this paper is to explore the efficacy of simulated interactive virtual conversations (chatbots) for mentoring underrepresented minority doctoral engineering students who are considering pursuing a career in the professoriate or in industry. Background: Chatbots were developed under the National Science Foundation INCLUDES Design and Developments Launch Pilot award (17-4458) and provide career advice with responses from a pre-programmed database populated by renowned emeriti engineering faculty. Chatbots have been engineered to fulfill a myriad of roles, such as undergraduate student advisement, but no research has been found that addresses their use with supplemental future faculty mentoring for doctoral students. Methodology: Chatbot efficacy is examined through a phenomenological design with focus groups with underrepresented minority doctoral engineering students. No theoretical or conceptual frameworks exist relative to chatbots designed for future faculty mentoring; therefore, an adaptation and implementation of the conceptual model posited on movie recommendations was utilized to ground this study. The four-stage process of phenomenological data analysis was followed: epoché, horizontalization, imaginative variation, and synthesis. Contribution: No studies have investigated the utility of chatbots in providing supplemental mentoring to future faculty. This phenomenological study contributes to this area of investigation and provides greater consideration into the unmet mentoring needs of these students, as well as the potential of utilizing chatbots for supplementary mentoring, particularly for those who lack access to high quality mentoring. Findings: Following the data analysis process, the essence of the findings was, while underrepresented minority doctoral engineering students have ample unmet mentoring needs and overall are satisfied with the user interface and trustworthiness of chatbots, their intent to use them is mixed due to a lack of personalization in this type of supplemental mentoring relationship. Recommendations for Practitioners: One of the major challenges faced by underrepresented doctoral engineering students is securing quality mentoring relationships that socialize them into the engineering culture and community of practice. While creating opportunities for students and incentivizing faculty to engage in the work of mentoring is needed, we must also consider the ways in which to leverage technology to offer supplemental future faculty mentoring virtually. Recommendation for Researchers: Additional research on the efficacy of chatbots in providing career-focused mentoring to future faculty is needed, as well as how to enhance the functionality of chatbots to create personal connections and networking opportunities, which are hallmarks of traditional mentoring relationships. Impact on Society: An understanding of the conceptual pathway that can lead to greater satisfaction with chatbots may serve to expand their use in the realm of mentoring. Scaling virtual faculty mentoring opportunities may be an important breakthrough in meeting mentoring needs across higher education. Future Research: Future chatbot research must focus on connecting chatbot users with human mentors; standardizing the process for response creation through additional data collection with a cadre of diverse, renowned faculty; engaging subject matter experts to conduct quality verification checks on responses; testing new responses with potential users; and launching the chatbots for a broad array of users.
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聊天机器人:一种补充未来教师指导工程博士生的工具
目的/目的:本文的目的是探讨模拟互动虚拟对话(聊天机器人)对那些考虑在教授或工业中追求职业生涯的少数族裔工程博士生的指导效果。背景:聊天机器人是在美国国家科学基金会INCLUDES设计和开发启动试点奖(17-4458)下开发的,并从一个由著名名誉工程学院组成的预编程数据库中提供职业建议。聊天机器人被设计成可以承担无数的角色,比如为本科生提供咨询服务,但目前还没有研究发现,它们的用途是为博士生提供补充的未来教师指导。研究方法:聊天机器人的功效是通过一种现象学设计来检验的,研究对象是代表性不足的少数民族工程博士生。目前还没有为未来教师指导而设计的聊天机器人的理论或概念框架;因此,改编和实施电影推荐的概念模型是本研究的基础。现象学数据分析的四个阶段是:时代、水平化、想象变异和综合。贡献:没有研究调查聊天机器人在为未来教师提供补充指导方面的效用。这项现象学研究有助于这一领域的调查,并为这些学生未满足的指导需求提供了更多的考虑,以及利用聊天机器人进行补充指导的潜力,特别是对于那些无法获得高质量指导的学生。研究结果:在数据分析过程中,研究结果的实质是,虽然少数族裔工程博士生有充分的未满足的指导需求,并且总体上对聊天机器人的用户界面和可信度感到满意,但由于这种补充指导关系缺乏个性化,他们使用聊天机器人的意图参差不齐。对实践者的建议:代表性不足的工程博士生面临的主要挑战之一是确保高质量的指导关系,使他们融入工程文化和实践社区。在为学生创造机会和激励教师参与指导工作的同时,我们还必须考虑利用技术为未来的教师指导提供补充的方法。对研究人员的建议:需要进一步研究聊天机器人在为未来教师提供以职业为中心的指导方面的功效,以及如何增强聊天机器人的功能,以创造个人联系和网络机会,这些都是传统指导关系的标志。对社会的影响:对概念途径的理解可以导致对聊天机器人的更大满意度,这可能有助于扩大它们在指导领域的使用。扩大虚拟教师指导机会可能是满足高等教育指导需求的重要突破。未来研究:未来的聊天机器人研究必须专注于将聊天机器人用户与人类导师联系起来;通过额外的数据收集,与多元化、知名的师资队伍合作,使响应创建过程标准化;聘请主题专家对答复进行质量验证检查;在潜在用户中测试新的响应;并为广大用户推出聊天机器人。
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来源期刊
International Journal of Doctoral Studies
International Journal of Doctoral Studies Social Sciences-Education
CiteScore
4.10
自引率
0.00%
发文量
16
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