Estimating Children’s Social Status Through Their Interaction Activities in Classrooms with a Social Robot

  • Tsuyoshi Komatsubara
  • Masahiro Shiomi
  • Thomas Kaczmarek
  • Takayuki Kanda
  • Hiroshi Ishiguro
Article

Abstract

We developed a technique to estimate children’s social status in classrooms with a social robot. Our approach observed children’s behaviors using a sensor network. We used depth cameras to track their positions and identified them with RGB cameras and exploited the presence of a social robot for the estimations. We specifically observed the children’s behavior around the robot, expecting that their interactions with it would provide clues for estimating their social status. We collected data at an actual elementary school and observed 70 fifth graders from three different classes during six lectures for each class period. Our system tracked the positions of the children 93.4% of the time and correctly identified them 65.5% of the time in crowded classrooms that held 28 students. These results were used to estimate the children’s social status. Our developed system successfully estimated the children’s social status with 71.4% accuracy.

Keywords

Estimation of social status Sensor network Robots for classroom Human–Robot Interaction 

Notes

Acknowledgements

We thank the staff and the students of the elementary school for their support. This work was in part supported by JSPS KAKENHI Grant Numbers JP25240042, JP25280095 and JP15H05322.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. 1.
    Kanda T, Hirano T, Eaton D, Ishiguro H (2004) Interactive robots as social partners and peer tutors for children: a field trial. Hum Comput Interact 19:61–84CrossRefGoogle Scholar
  2. 2.
    Han J, Jo M, Park S, Kim S (2005) The educational use of home robots for children. In: IEEE international workshop on robot and human interactive communication, pp 378–383Google Scholar
  3. 3.
    Saerbeck M, Schut T, Bartneck C, Janse MD (2010) Expressive robots in education: varying the degree of social supportive behavior of a robotic tutor. In: ACM Conference on human factors in computing systems (CHI2010), pp 1613–1622Google Scholar
  4. 4.
    Howley I, Kanda T, Hayashi K, Rosé C (2014) Effects of social presence and social role on help-seeking and learning. In: ACM/IEEE international conference on human-robot interaction (HRI2014), pp 415–422Google Scholar
  5. 5.
    Hollingshead AB (1975) Four factor index of social status. (*It was initially unpublished work but extremely well cited. It was later published as: A.B. Hollingshead (2011) Four factor index of social status. Yale Journal of Sociology, vol. 8, pp 21–52.)Google Scholar
  6. 6.
    Coie JD, Dodge KA, Kupersmidt JB (1990) Peer group behavior and social status. In: Asher SR, Coie JD (eds) Peer rejection in childhood. Cambridge University Press, Cambridge, pp 17–59Google Scholar
  7. 7.
    Salmivalli C, Lagerspetz K, Björkqvist K, Österman K, Kaukiainen A (1996) Bullying as a group process: participant roles and their relations to social status within the group. Aggress Behav 22:1–15CrossRefGoogle Scholar
  8. 8.
    Crothers LM, Kolbert JB (2008) Tackling a problematic behavior management issue teachers’ intervention in childhood bullying problems. Interv Sch Clin 43:132–139CrossRefGoogle Scholar
  9. 9.
    Rodkin PC, Berger C (2008) Who bullies whom? Social status asymmetries by Victim Gender. Int J Behav Dev 32:473–485CrossRefGoogle Scholar
  10. 10.
    O’Neil R, Welsh M, Parke RD, Wang S, Strand C (1997) A longitudinal assessment of the academic correlates of early peer acceptance and rejection. J Clin Child Psychol 26:290–303CrossRefGoogle Scholar
  11. 11.
    Van Laar C, Sidanius J (2001) Social status and the academic achievement gap: a social dominance perspective. Soc Psychol Educ 4:235–258CrossRefGoogle Scholar
  12. 12.
    Coie JD, Krehbiel G (1984) Effects of academic tutoring on the social status of low-achieving, socially rejected children. Child Dev 55:1465–1478CrossRefGoogle Scholar
  13. 13.
    Woods S, Davis M, Dautenhahn K, Schulz J (2005) Can robots be used as a vehicle for the projection of socially sensitive issues? Exploring Children’s Attitudes Towards Robots through Stories. In: IEEE international workshop on robot and human interactive communication, pp 384–389Google Scholar
  14. 14.
    Bethel CL, Eakin D, Anreddy S, Stuart JK, Carruth D (2013) Eyewitnesses are misled by human but not robot interviewers. In: ACM/IEEE international conference on human-robot, Interaction, pp 25–32Google Scholar
  15. 15.
    Tanaka F, Cicourel A, Movellan JR (2007) Socialization between Toddlers and Robots at an early childhood education center. In: Proceedings of the national academy of sciences of the USA (PNAS), pp 17954–17958Google Scholar
  16. 16.
    Belpaeme T et al (2012) Multimodal child-robot interaction: building social bonds. J Hum Robot Interact 1:33–53Google Scholar
  17. 17.
    Komatsubara T, Shiomi M, Kanda T, Ishiguro H, Hagita N (2014) Can a social robot help children’s understanding of science in classrooms? In: Proceedings of international conference on human–agent, interaction, pp 83–90Google Scholar
  18. 18.
    Komatsubara T, Shiomi M, Kanda T, Ishiguro H (2017) Can using pointing gestures encourage children to ask questions? Int J Soc Robot.  https://doi.org/10.1007/s12369-017-0444-5
  19. 19.
    Shiomi M, Kanda T, Howley I, Hayashi K, Hagita N (2015) Can a social robot stimulate science curiosity in classrooms? Int J Soc Robot 7(5):641–652CrossRefGoogle Scholar
  20. 20.
    Choudhury T, Pentland A (2003) Sensing and modeling human networks using the sociometer. In: IEEE international symposium on wearable computers, pp 216–222Google Scholar
  21. 21.
    Kanda T, Ishiguro H (2006) An approach for a social robot to understand human relationships: friendship estimation through interaction with robots. Interact Stud 7:369–403CrossRefGoogle Scholar
  22. 22.
    Lao S, Kawade M (2005) Vision-based face understanding technologies and their applications. Adv Biom Pers Authent pp 339–348Google Scholar
  23. 23.
    Kirchner N, Alempijevic A, Virgona A (2012) Head-to-shoulder signature for person recognition. In: IEEE international conference on robotics and automation (ICRA), pp 1226–1231Google Scholar
  24. 24.
    Huang KS, Trivedi MM (2003) Distributed video arrays for tracking, human identification, and activity analysis. IEEE Int Conf Multimed Expo 2:9–12Google Scholar
  25. 25.
    Aran O, Gatica-Perez D (2013) One of a kind: inferring personality impressions in meetings. In: Proceedings of the ACM international conference on multimodal, interaction, pp 11–18Google Scholar
  26. 26.
    Hung H, Jayagopi D, Yeo C, Friedland G, Ba S, Odobez JM., Ramchandran K, Mirghafori N, Gatica-Perez D (2007) Using audio and video features to classify the most dominant person in a group meeting. In: Proceedings of the ACM international conference on multimedia, pp 835–838Google Scholar
  27. 27.
    Gottman J, Gonso J, Rasmussen B (1975) Social interaction, social competence, and friendship in children. Child Dev 46:709–718CrossRefGoogle Scholar
  28. 28.
    Cummins D (2005) Dominance, status, and social hierarchies. In: The handbook of evolutionary psychology, pp 676–697Google Scholar
  29. 29.
    Olguín DO, Gloor PA, Pentland A (2009) Wearable sensors for pervasive healthcare management. In: International conference on pervasive computing technologies for healthcare, pp 1–4Google Scholar
  30. 30.
    Kalimeri K (2013) Towards a dynamic view of personality: multimodal classification of personality states in everyday situations. In: Proceedings of the ACM on international conference on multimodal, interaction, pp 325–328Google Scholar
  31. 31.
    Mohammadi G, Vinciarelli A (2012) Automatic personality perception: prediction of trait attribution based on prosodic features. IEEE Trans Affect Comput 3:273–284CrossRefGoogle Scholar
  32. 32.
    Brscic D, Kanda T, Ikeda T, Miyashita T (2013) Person tracking in large public spaces using 3D range sensors. IEEE Trans Hum Mach Syst 43:522–534CrossRefGoogle Scholar
  33. 33.
    Hall ET (1966) The hidden dimension. Anchor Books, New YorkGoogle Scholar
  34. 34.
    Pedregosa F et al (2011) Scikit-learn: machine learning in python. JMLR 12:2825–2830MathSciNetMATHGoogle Scholar
  35. 35.
    Tanaka K (1979) Theory and methods of sociometry. Meiji Press, Tokyo (in Japanese)Google Scholar
  36. 36.
    Inderbitzen-Pisaruk H, Foster SL (1990) Adolescent friendships and peer acceptance: implications for social skills training. Clin Psychol Rev 10:425–439CrossRefGoogle Scholar
  37. 37.
    Sato S et al (1999) Interpersonal relationship, social adjustment and preventive intervention for children. Ann Rep Educ Psychol Jpn 38:51–63CrossRefGoogle Scholar
  38. 38.
    Yoshio M et al (1987) Sociometric status of children with attention deficit disorder. Nippon Eiseigaku Zasshi (Jpn J Hyg) 42(5):913–921CrossRefGoogle Scholar
  39. 39.
    Sugihara K et al (1986) A comparison between perpetrators and victims of ijime on sociometric status and personality traits. Tsukuba Psychol Res 8:63–72Google Scholar
  40. 40.
    Aiello John R, De Carlo T, Aiello DCT (1974) The development of personal space: proxemic behavior of children 6 through 16. Hum Ecol 2(3):177–189CrossRefGoogle Scholar
  41. 41.
    Yamaji Y, Miyake T, Yuta Yoshiike P, Silva RS, Okada M (2011) STB: child-dependent sociable trash box. Int J Soc Robot 3(4):359.  https://doi.org/10.1007/s12369-011-0114-y CrossRefGoogle Scholar
  42. 42.
    Vázquez Marynel, et al (2014) Spatial and other social engagement cues in a child–robot interaction: effects of a sidekick. In: Proceedings of the 2014 ACM/IEEE international conference on Human–robot interaction. ACMGoogle Scholar
  43. 43.
    Walters Michael L et al. (2005) Close encounters: spatial distances between people and a robot of mechanistic appearance. In: 5th IEEE-RAS international conference on humanoid robots, 2005, IEEEGoogle Scholar
  44. 44.
    Shiomi M, Kurumizawa K, Kanda T, Ishiguro H, Hagita N (2014) Finding a Person with a Wi-Fi device in a crowd of pedestrians. Adv Robot 28(7):441–448CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Tsuyoshi Komatsubara
    • 1
  • Masahiro Shiomi
    • 1
  • Thomas Kaczmarek
    • 1
  • Takayuki Kanda
    • 1
  • Hiroshi Ishiguro
    • 2
  1. 1.ATRKeihanna Science CityJapan
  2. 2.Osaka UniversityToyonaka, OsakaJapan

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