Skip to main content
Springer Nature Link
Log in

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

  • Published:
International Journal of Social Robotics Aims and scope Submit manuscript

    We’re sorry, something doesn't seem to be working properly.

    Please try refreshing the page. If that doesn't work, please contact support so we can address the problem.

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

Notes

  1. Personality and social status are clearly different constructs (concepts) in psychology. Social status is closely connected to social preference (i.e., whether everyone likes him/her), and hence it tends to be the consequence of individual capability, such as social competence [36] or the tendency to engage in aggressive behavior [6]. For example, a child with an extroverted personality is not necessarily popular and might be perceived as annoying or aggressive if he behaves badly; a shy introverted child might be liked if she is socially competent, e.g., helpful and cooperative.

References

  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 19:61–84

    Article  Google Scholar 

  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 378–383

  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 1613–1622

  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 415–422

  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.)

  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 17–59

    Google Scholar 

  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 22:1–15

    Article  Google Scholar 

  8. Crothers LM, Kolbert JB (2008) Tackling a problematic behavior management issue teachers’ intervention in childhood bullying problems. Interv Sch Clin 43:132–139

    Article  Google Scholar 

  9. Rodkin PC, Berger C (2008) Who bullies whom? Social status asymmetries by Victim Gender. Int J Behav Dev 32:473–485

    Article  Google Scholar 

  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 26:290–303

    Article  Google Scholar 

  11. Van Laar C, Sidanius J (2001) Social status and the academic achievement gap: a social dominance perspective. Soc Psychol Educ 4:235–258

    Article  Google Scholar 

  12. Coie JD, Krehbiel G (1984) Effects of academic tutoring on the social status of low-achieving, socially rejected children. Child Dev 55:1465–1478

    Article  Google Scholar 

  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 384–389

  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 25–32

  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 17954–17958

  16. Belpaeme T et al (2012) Multimodal child-robot interaction: building social bonds. J Hum Robot Interact 1:33–53

    Google Scholar 

  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 83–90

  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. 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):641–652

    Article  Google Scholar 

  20. Choudhury T, Pentland A (2003) Sensing and modeling human networks using the sociometer. In: IEEE international symposium on wearable computers, pp 216–222

  21. Kanda T, Ishiguro H (2006) An approach for a social robot to understand human relationships: friendship estimation through interaction with robots. Interact Stud 7:369–403

    Article  Google Scholar 

  22. Lao S, Kawade M (2005) Vision-based face understanding technologies and their applications. Adv Biom Pers Authent pp 339–348

  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 1226–1231

  24. Huang KS, Trivedi MM (2003) Distributed video arrays for tracking, human identification, and activity analysis. IEEE Int Conf Multimed Expo 2:9–12

    Google Scholar 

  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 11–18

  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 835–838

  27. Gottman J, Gonso J, Rasmussen B (1975) Social interaction, social competence, and friendship in children. Child Dev 46:709–718

    Article  Google Scholar 

  28. Cummins D (2005) Dominance, status, and social hierarchies. In: The handbook of evolutionary psychology, pp 676–697

  29. Olguín DO, Gloor PA, Pentland A (2009) Wearable sensors for pervasive healthcare management. In: International conference on pervasive computing technologies for healthcare, pp 1–4

  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 325–328

  31. Mohammadi G, Vinciarelli A (2012) Automatic personality perception: prediction of trait attribution based on prosodic features. IEEE Trans Affect Comput 3:273–284

    Article  Google Scholar 

  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 43:522–534

    Article  Google Scholar 

  33. Hall ET (1966) The hidden dimension. Anchor Books, New York

    Google Scholar 

  34. Pedregosa F et al (2011) Scikit-learn: machine learning in python. JMLR 12:2825–2830

    MathSciNet  MATH  Google Scholar 

  35. Tanaka K (1979) Theory and methods of sociometry. Meiji Press, Tokyo (in Japanese)

    Google Scholar 

  36. Inderbitzen-Pisaruk H, Foster SL (1990) Adolescent friendships and peer acceptance: implications for social skills training. Clin Psychol Rev 10:425–439

    Article  Google Scholar 

  37. Sato S et al (1999) Interpersonal relationship, social adjustment and preventive intervention for children. Ann Rep Educ Psychol Jpn 38:51–63

    Article  Google Scholar 

  38. Yoshio M et al (1987) Sociometric status of children with attention deficit disorder. Nippon Eiseigaku Zasshi (Jpn J Hyg) 42(5):913–921

    Article  Google Scholar 

  39. Sugihara K et al (1986) A comparison between perpetrators and victims of ijime on sociometric status and personality traits. Tsukuba Psychol Res 8:63–72

    Google Scholar 

  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):177–189

    Article  Google Scholar 

  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

    Article  Google Scholar 

  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. ACM

  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, IEEE

  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):441–448

    Article  Google Scholar 

Download references

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.

Author information

Authors and Affiliations

  1. ATR, 2-2-2, Hikaridai, Keihanna Science City, Kyoto, 619-0288, Japan

    Tsuyoshi Komatsubara, Masahiro Shiomi, Thomas Kaczmarek & Takayuki Kanda

  2. Osaka University, 1-3, Machikaneyama, Toyonaka, Osaka, 560-8531, Japan

    Hiroshi Ishiguro

Authors
  1. Tsuyoshi Komatsubara
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Masahiro Shiomi
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Thomas Kaczmarek
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Takayuki Kanda
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Hiroshi Ishiguro
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Masahiro Shiomi.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Komatsubara, T., Shiomi, M., Kaczmarek, T. et al. Estimating Children’s Social Status Through Their Interaction Activities in Classrooms with a Social Robot. Int J of Soc Robotics 11, 35–48 (2019). https://doi.org/10.1007/s12369-018-0474-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12369-018-0474-7

Keywords