教育机器人如何影响高中生判断,研究发现其语气越确定,学生越易被说服。
Sense and Sensibility: What makes a social robot convincing to high-school students?
- 通过语调、表情等信号展示不同确定性,测试机器人对学生的影响力
- 机器人表现确定时,94.4%的学生认同其答案,错误时仍75%超出预期表现
- 熟悉大模型的学生更易受误导,提示需警惕AI信息过载
本研究对40名高中生开展实验,考察社交教育机器人在电学知识判断中的影响。机器人在8道真假题中对6题给出正确答案,2题错误。75%的学生表现超出预期水平:正确时提升,错误时下降。使用大语言模型经验较多的学生更易被误导,尤其在机器人犯错的简单问题上。研究进一步测试了三种不同确定性表达方式(语义、语调、面部信号)的影响。当机器人表现为‘确定’时,学生一致率达94.4%;‘中性’为82.6%;‘不确定’为71.4%。问卷显示,学生最信服‘确定’状态的机器人。结果表明,教育机器人应根据信息可靠性动态调整确定性表达,以培养批判性思维,避免不当影响。
原文摘要 · Abstract (English)
This study with 40 high-school students demonstrates the high influence of a social educational robot on students' decision-making for a set of eight true-false questions on electric circuits, for which the theory had been covered in the students' courses. The robot argued for the correct answer on six questions and the wrong on two, and 75% of the students were persuaded by the robot to perform beyond their expected capacity, positively when the robot was correct and negatively when it was wrong. Students with more experience of using large language models were even more likely to be influenced by the robot's stance -- in particular for the two easiest questions on which the robot was wrong -- suggesting that familiarity with AI can increase susceptibility to misinformation by AI. We further examined how three different levels of portrayed robot certainty, displayed using semantics, prosody and facial signals, affected how the students aligned with the robot's answer on specific questions and how convincing they perceived the robot to be on these questions. The students aligned with the robot's answers in 94.4% of the cases when the robot was portrayed as Certain, 82.6% when it was Neutral and 71.4% when it was Uncertain. The alignment was thus high for all conditions, highlighting students' general susceptibility to accept the robot's stance, but alignment in the Uncertain condition was significantly lower than in the Certain. Post-test questionnaire answers further show that students found the robot most convincing when it was portrayed as Certain. These findings highlight the need for educational robots to adjust their display of certainty based on the reliability of the information they convey, to promote students' critical thinking and reduce undue influence.
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