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我们到了吗?——关于教育领域聊天机器人的系统文献综述

Are We There Yet? - A Systematic Literature Review on Chatbots in Education.

作者信息

Wollny Sebastian, Schneider Jan, Di Mitri Daniele, Weidlich Joshua, Rittberger Marc, Drachsler Hendrik

机构信息

Information Center for Education, DIPF | Leibniz Institute for Research and Information in Education, Frankfurt am Main, Germany.

Educational Science Faculty, Open University of the Netherlands, Heerlen, Netherlands.

出版信息

Front Artif Intell. 2021 Jul 15;4:654924. doi: 10.3389/frai.2021.654924. eCollection 2021.

Abstract

Chatbots are a promising technology with the potential to enhance workplaces and everyday life. In terms of scalability and accessibility, they also offer unique possibilities as communication and information tools for digital learning. In this paper, we present a systematic literature review investigating the areas of education where chatbots have already been applied, explore the pedagogical roles of chatbots, the use of chatbots for mentoring purposes, and their potential to personalize education. We conducted a preliminary analysis of 2,678 publications to perform this literature review, which allowed us to identify 74 relevant publications for chatbots' application in education. Through this, we address five research questions that, together, allow us to explore the current state-of-the-art of this educational technology. We conclude our systematic review by pointing to three main research challenges: 1) Aligning chatbot evaluations with implementation objectives, 2) Exploring the potential of chatbots for mentoring students, and 3) Exploring and leveraging adaptation capabilities of chatbots. For all three challenges, we discuss opportunities for future research.

摘要

聊天机器人是一项很有前景的技术,有潜力提升工作场所和日常生活。在可扩展性和可及性方面,它们作为数字学习的沟通和信息工具也提供了独特的可能性。在本文中,我们进行了一项系统的文献综述,调查聊天机器人已经应用的教育领域,探讨聊天机器人的教学角色、用于指导目的的聊天机器人的使用情况,以及它们实现教育个性化的潜力。为进行这项文献综述,我们对2678篇出版物进行了初步分析,这使我们能够确定74篇关于聊天机器人在教育中应用的相关出版物。通过这项工作,我们回答了五个研究问题,这些问题共同使我们能够探索这项教育技术的当前发展水平。我们在系统综述的结尾指出了三个主要研究挑战:1)使聊天机器人评估与实施目标保持一致;2)探索聊天机器人指导学生的潜力;3)探索和利用聊天机器人的适应能力。针对所有这三个挑战,我们讨论了未来研究的机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f45/8319668/747b7d8f8c5a/frai-04-654924-g001.jpg

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