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人工智能对在线学习中学习者与教师互动的影响。

The impact of artificial intelligence on learner-instructor interaction in online learning.

作者信息

Seo Kyoungwon, Tang Joice, Roll Ido, Fels Sidney, Yoon Dongwook

机构信息

Department of Applied Artificial Intelligence, Seoul National University of Science and Technology, 232 Gongneung-ro, Gongneung-dong, Nowon-gu, Seoul, 01811 Korea.

Department of Computer Science, The University of British Columbia, Vancouver, Canada.

出版信息

Int J Educ Technol High Educ. 2021;18(1):54. doi: 10.1186/s41239-021-00292-9. Epub 2021 Oct 26.

Abstract

Artificial intelligence (AI) systems offer effective support for online learning and teaching, including personalizing learning for students, automating instructors' routine tasks, and powering adaptive assessments. However, while the opportunities for AI are promising, the impact of AI systems on the culture of, norms in, and expectations about interactions between students and instructors are still elusive. In online learning, learner-instructor interaction (inter alia, communication, support, and presence) has a profound impact on students' satisfaction and learning outcomes. Thus, identifying how students and instructors perceive the impact of AI systems on their interaction is important to identify any gaps, challenges, or barriers preventing AI systems from achieving their intended potential and risking the safety of these interactions. To address this need for forward-looking decisions, we used Speed Dating with storyboards to analyze the authentic voices of 12 students and 11 instructors on diverse use cases of possible AI systems in online learning. Findings show that participants envision adopting AI systems in online learning can enable personalized learner-instructor interaction at scale but at the risk of violating social boundaries. Although AI systems have been positively recognized for improving the quantity and quality of communication, for providing just-in-time, personalized support for large-scale settings, and for improving the feeling of connection, there were concerns about responsibility, agency, and surveillance issues. These findings have implications for the design of AI systems to ensure explainability, human-in-the-loop, and careful data collection and presentation. Overall, contributions of this study include the design of AI system storyboards which are technically feasible and positively support learner-instructor interaction, capturing students' and instructors' concerns of AI systems through Speed Dating, and suggesting practical implications for maximizing the positive impact of AI systems while minimizing the negative ones.

摘要

人工智能(AI)系统为在线学习和教学提供了有效的支持,包括为学生提供个性化学习、自动化教师的日常任务以及推动自适应评估。然而,尽管人工智能带来的机遇前景广阔,但人工智能系统对学生与教师之间互动的文化、规范和期望的影响仍不明确。在在线学习中,学习者与教师的互动(尤其是沟通、支持和在场)对学生的满意度和学习成果有着深远的影响。因此,确定学生和教师如何看待人工智能系统对他们互动的影响,对于找出任何可能阻碍人工智能系统发挥预期潜力并危及这些互动安全性的差距、挑战或障碍至关重要。为了满足做出前瞻性决策的这一需求,我们使用带有故事板的快速约会法,分析了12名学生和11名教师对于在线学习中可能的人工智能系统不同用例的真实看法。研究结果表明,参与者设想在在线学习中采用人工智能系统能够实现大规模的个性化学习者与教师互动,但存在违反社会界限的风险。尽管人工智能系统在改善沟通的数量和质量、为大规模环境提供及时的个性化支持以及增强联系感方面得到了积极认可,但人们对责任、能动性和监督问题仍存在担忧。这些发现对人工智能系统的设计具有启示意义,以确保可解释性、人在回路中以及谨慎的数据收集和呈现。总体而言,本研究的贡献包括设计出技术上可行且能积极支持学习者与教师互动的人工智能系统故事板,通过快速约会法捕捉学生和教师对人工智能系统的担忧,并提出实际建议,以在最大限度地发挥人工智能系统的积极影响的同时,将消极影响降至最低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fbe6/8545464/091257adec4c/41239_2021_292_Fig1_HTML.jpg

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