{"title":"观察机器人同伴的失败有助于学生的课堂学习","authors":"Liuqing Chen, Yu Cai, Yuyang Fang, Ziqi Yang, Duowei Xia, Jiaxiang You, Shuhong Xiao, Yaxuan Song, Lingwei Zhan, Juanjuan Chen, Lingyun Sun","doi":"10.1126/scirobotics.adu5257","DOIUrl":null,"url":null,"abstract":"<div >According to productive failure (PF) theory, experiencing failure during problem-solving can enhance students’ knowledge acquisition in subsequent instruction. However, challenging students with problems beyond their current capabilities may strain their skills, prior knowledge, and emotional well-being. To address this, we designed a social robot–assisted teaching activity in which students observed a robot’s unsuccessful problem-solving attempts, offering a PF-like preparatory effect without requiring direct failure. We conducted two classroom-based studies in a middle school setting to evaluate the method’s effectiveness. In study 1 (<i>N</i> = 135), we compared three instructional methods—observing robot failure (RF), individual problem-solving failure, and direct instruction—in an eighth-grade mathematics lesson. Students in the RF condition showed the greatest gains in conceptual understanding and reported lower social pressure, although no significant differences were found in procedural knowledge or knowledge transfer. Follow-up study 2 (<i>N</i> = 110) further validated the method’s effectiveness in supporting knowledge acquisition after a 2-week robot-involved adaptation phase, when the novelty effect had largely subsided. Students confirmed their perception of the robot as a peer, and they offered positive evaluations of its intelligence and neutral views of its anthropomorphism. Our findings suggest that observing the robot’s failure has a comparable, or even greater, effect on knowledge acquisition than experiencing failure firsthand. These results underscore the value of social robots as peers in science, technology, engineering, and mathematics education and highlight the potential of integrating robotics with evidence-based teaching strategies to enhance learning outcomes.</div>","PeriodicalId":56029,"journal":{"name":"Science Robotics","volume":"10 106","pages":""},"PeriodicalIF":27.5000,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Observing a robot peer’s failures facilitates students’ classroom learning\",\"authors\":\"Liuqing Chen, Yu Cai, Yuyang Fang, Ziqi Yang, Duowei Xia, Jiaxiang You, Shuhong Xiao, Yaxuan Song, Lingwei Zhan, Juanjuan Chen, Lingyun Sun\",\"doi\":\"10.1126/scirobotics.adu5257\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div >According to productive failure (PF) theory, experiencing failure during problem-solving can enhance students’ knowledge acquisition in subsequent instruction. However, challenging students with problems beyond their current capabilities may strain their skills, prior knowledge, and emotional well-being. To address this, we designed a social robot–assisted teaching activity in which students observed a robot’s unsuccessful problem-solving attempts, offering a PF-like preparatory effect without requiring direct failure. We conducted two classroom-based studies in a middle school setting to evaluate the method’s effectiveness. In study 1 (<i>N</i> = 135), we compared three instructional methods—observing robot failure (RF), individual problem-solving failure, and direct instruction—in an eighth-grade mathematics lesson. Students in the RF condition showed the greatest gains in conceptual understanding and reported lower social pressure, although no significant differences were found in procedural knowledge or knowledge transfer. Follow-up study 2 (<i>N</i> = 110) further validated the method’s effectiveness in supporting knowledge acquisition after a 2-week robot-involved adaptation phase, when the novelty effect had largely subsided. Students confirmed their perception of the robot as a peer, and they offered positive evaluations of its intelligence and neutral views of its anthropomorphism. Our findings suggest that observing the robot’s failure has a comparable, or even greater, effect on knowledge acquisition than experiencing failure firsthand. These results underscore the value of social robots as peers in science, technology, engineering, and mathematics education and highlight the potential of integrating robotics with evidence-based teaching strategies to enhance learning outcomes.</div>\",\"PeriodicalId\":56029,\"journal\":{\"name\":\"Science Robotics\",\"volume\":\"10 106\",\"pages\":\"\"},\"PeriodicalIF\":27.5000,\"publicationDate\":\"2025-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science Robotics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.science.org/doi/10.1126/scirobotics.adu5257\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ROBOTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science Robotics","FirstCategoryId":"94","ListUrlMain":"https://www.science.org/doi/10.1126/scirobotics.adu5257","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ROBOTICS","Score":null,"Total":0}
Observing a robot peer’s failures facilitates students’ classroom learning
According to productive failure (PF) theory, experiencing failure during problem-solving can enhance students’ knowledge acquisition in subsequent instruction. However, challenging students with problems beyond their current capabilities may strain their skills, prior knowledge, and emotional well-being. To address this, we designed a social robot–assisted teaching activity in which students observed a robot’s unsuccessful problem-solving attempts, offering a PF-like preparatory effect without requiring direct failure. We conducted two classroom-based studies in a middle school setting to evaluate the method’s effectiveness. In study 1 (N = 135), we compared three instructional methods—observing robot failure (RF), individual problem-solving failure, and direct instruction—in an eighth-grade mathematics lesson. Students in the RF condition showed the greatest gains in conceptual understanding and reported lower social pressure, although no significant differences were found in procedural knowledge or knowledge transfer. Follow-up study 2 (N = 110) further validated the method’s effectiveness in supporting knowledge acquisition after a 2-week robot-involved adaptation phase, when the novelty effect had largely subsided. Students confirmed their perception of the robot as a peer, and they offered positive evaluations of its intelligence and neutral views of its anthropomorphism. Our findings suggest that observing the robot’s failure has a comparable, or even greater, effect on knowledge acquisition than experiencing failure firsthand. These results underscore the value of social robots as peers in science, technology, engineering, and mathematics education and highlight the potential of integrating robotics with evidence-based teaching strategies to enhance learning outcomes.
期刊介绍:
Science Robotics publishes original, peer-reviewed, science- or engineering-based research articles that advance the field of robotics. The journal also features editor-commissioned Reviews. An international team of academic editors holds Science Robotics articles to the same high-quality standard that is the hallmark of the Science family of journals.
Sub-topics include: actuators, advanced materials, artificial Intelligence, autonomous vehicles, bio-inspired design, exoskeletons, fabrication, field robotics, human-robot interaction, humanoids, industrial robotics, kinematics, machine learning, material science, medical technology, motion planning and control, micro- and nano-robotics, multi-robot control, sensors, service robotics, social and ethical issues, soft robotics, and space, planetary and undersea exploration.