Definition of reflection characteristics of educational process participants with artificial intelligence application

V. Grinshkun, S. I. Dreytser
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Abstract

Problem statement . Artificial intelligence (AI) conversational tools like chat-bots, virtual assistants and dialog trainers begin to apply in education. However, its efficiency wasn't explored because of novelty and lack of related application experience. In this research an approach to conversations based on AI is considered as means to define reflection of educational process participants. And definition results of reflection are compared between an AI conversational tool and an expert's assessment in the educational process. Methodology . Opportunities of conversational simulations based on AI were analysed for reflection assessment. Behavioural markers of reflection in communication were developed as well as assessment procedures in online mode with AI simulations and in offline mode with an expert assessment. Research was provided as a part of the volunteer’s competition. There were 65 participants of the research, students of schools and universities. Statistical processing of the results was performed using Pearson's criteria. Results. Weak correlation was detected between AI and expert assessment. Conclusion. Suggestions were offered about AI assessment improvement for increasing assessment precision of reflection of educational process participants from the methodological point of view as well as from AI algorithms development.
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人工智能应用对教育过程参与者反思特征的界定
问题陈述。人工智能(AI)会话工具,如聊天机器人、虚拟助手和对话训练器,开始应用于教育领域。然而,由于其新颖性和缺乏相关应用经验,其有效性尚未得到深入探讨。在本研究中,基于人工智能的对话方法被认为是定义教育过程参与者反思的手段。并将人工智能会话工具与专家在教学过程中的评估进行了比较。方法。分析了基于人工智能的会话模拟的机会,以进行反思评估。开发了交流中反思的行为标记以及在线模式下人工智能模拟和离线模式下专家评估的评估程序。研究是志愿者竞赛的一部分。这项研究共有65名参与者,他们都是中学和大学的学生。使用Pearson标准对结果进行统计处理。结果。人工智能与专家评价呈弱相关。结论。从方法学角度和人工智能算法开发角度对提高教育过程参与者反思的评估精度提出了改进人工智能评估的建议。
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24
审稿时长
9 weeks
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