Skip to main content
SpringerLink
Log in

A Motivational Approach to Support Healthy Habits in Long-term Child–Robot Interaction

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

Abstract

We examine the use of role-switching as an intrinsic motivational mechanism to increase engagement in long-term child–robot interaction. The present study describes a learning framework where children between 9 and 11-years-old interact with a robot to improve their knowledge and habits with regards to healthy life-styles. Experiments were carried out in Italy where 41 children were divided in three groups interacting with: (i) a robot with a role-switching mechanism, (ii) a robot without a role-switching mechanism and (iii) an interactive video. Additionally, a control group composed of 43 more children, who were not exposed to any interactive approach, was used as a baseline of the study. During the intervention period, the three groups were exposed to three interactive sessions once a week. The aim of the study was to find any difference in healthy-habits acquisition based on alternative interactive systems, and to evaluate the effectiveness of the role-switch approach as a trigger for engagement and motivation while interacting with a robot. The results provide evidence that the rate of children adopting healthy habits during the intervention period was higher for those interacting with a robot. Moreover, alignment with the robot behaviour and achievement of higher engagement levels were also observed for those children interacting with the robot that used the role-switching mechanism. This supports the notion that role-switching facilitates sustained long-interactions between a child and a robot.

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

Access this article

Log in via an institution

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

Similar content being viewed by others

Notes

  1. www.aldebaran.com.

  2. www.urbiforge.org.

  3. This condition is analogous to the Without Role Switching condition, with the difference that children interact with a video instead of a robot.

  4. We were informed by the teachers that, during the period in which the study took place, no explicit references to healthy habits were addressed in the involved classes. Therefore, if any information on this topic was provided to children, it had to be out of school lessons/activities.

  5. A pictorial representation of a 1–5 Likert scale through which respondents identify their answers, feelings or opinions [27].

  6. Children in the video condition (V) did not filled in these questions.

  7. Few differences between annotations were found, and these were mainly due to human error, i.e. missing an observable behaviour, rather than disagreement on the classification of the behaviour.

  8. As already mentioned in the study design, teachers confirmed that children were not having any lessons regarding healthy life styles during the study period.

References

  1. Aylett RS, Castellano G, Raducanu B, Paiva A, Hanheide M (2011) Long-term socially perceptive and interactive robot companions: challenges and future perspectives. In: Proceedings of international conference on multimodal, interfaces, pp 323–326

  2. Baroni I, Nalin M, Coti Zelati M, Oleari E, Sanna A (2014) Designing motivational robot: how robots might motivate children to eat fruits and vegetables. In: Proceedings of the 23rd IEEE international symposium on robot and human interactive communication (RoMAN)

  3. Belpaeme T, Baxter P, de Greeff J, Kennedy J, Read R, Looije R, Neerincx M, Baroni I, Zelati MC (2013) Child–robot interaction: perspectives and challenges. In: Herrmann G, Pearson MJ, Lenz A, Bremner P, Spiers A, Leonards U (eds) Social robotics, vol 8239. Springer, New York, pp 452–459 Lecture Notes in Computer Science

    Chapter  Google Scholar 

  4. Belpaeme T, Baxter PE, Read R, Wood R, Cuayáhuitl Heriberto, Kiefer B, Racioppa S, Kruijff-Korbayová I, Athanasopoulos G, Enescu V et al (2012) Multimodal child–robot interaction: building social bonds. J Hum-Robot Interact 1(2):33–53

    Google Scholar 

  5. Bianchi-Berthouze N (2013) Understanding the role of body movement in player engagement. Hum-Comput Interact 28(1):40–75

    Google Scholar 

  6. Bickmore TW, Picard RW (2005) Establishing and maintaining long-term human–computer relationships. Trans Comput Hum Interact 12(2):293–327

    Article  Google Scholar 

  7. Cynthia LB (2004) Designing sociable robots. MIT press, Cambridge

    Google Scholar 

  8. Bruce A, Nourbakhsh I, Simmons R (2002) The role of expressiveness and attention in human–robot interaction. In: Robotics and automation. Proceedings ICRA’02 IEEE international conference on, IEEE, vol 4, pp 4138–4142

  9. Martyn C, David K, William H, Kerstin D (1999) Robots in the classroom-tools for accessible education. Assistive technology on the threshold of the new millennium, pp 448–452

  10. European Food Information Council (2009) Food-based dietary guidelines in Europe. http://www.eufic.org/article/en/expid/food-based-dietary-guidelines-in-europe/

  11. Dautenhahn K (2007) Socially intelligent robots: dimensions of human–robot interaction. Philos Trans R Soc B 362(1480):679–704

    Article  Google Scholar 

  12. Fasola J Mataric MJ (2010) Robot motivator: Increasing user enjoyment and performance on a physical/cognitive task. In: Development and learning (ICDL), IEEE 9th international conference on, IEEE, pp 274–279

  13. Fong T, Nourbakhsh I, Dautenhahn K (2003) A survey of socially interactive robots. Robot Auton Syst 42(3):143–166

    Article  MATH  Google Scholar 

  14. Gockley R, Bruce A, Forlizzi J, Michalowski M, Mundell A, Rosenthal S, Sellner B, Simmons R, Snipes K, Schultz AC et al (2005) Designing robots for long-term social interaction. In: IEEE/RSJ international conference on intelligent robots and systems (IROS)

  15. Hanna L, Risden K, Alexander K (1997) Guidelines for usability testing with children. Interactions 4(5):9–14

    Article  Google Scholar 

  16. Kanda T, Sato R, Saiwaki N, Ishiguro H (2007) A two-month field trial in an elementary school for long-term human–robot interaction. Robot IEEE Trans 23(5):962–971

    Article  Google Scholar 

  17. Kennedy J, Baxter P, Belpaeme T (2015) The robot who tried too hard: social behaviour of a robot tutor can negatively affect child learning. In: Proceedings of the 10th annual ACM/IEEE international conference on human–robot interaction, ACM, pp 67–74

  18. Kidd CD, Breazeal C (2007) A robotic weight loss coach. In: Proceedings of the 22nd national conference on artificial intelligence, vol 2, 1985–1986, AAAI Press, London

  19. Kidd CD, Breazeal C (2008) Robots at home: understanding long-term human–robot interaction. In: IEEE/RSJ international conference on intelligent robots and systems (IROS)

  20. Laurent Jeff, Catanzaro Salvatore J, Thomas E Joiner Jr, Karen D Rudolph, Kirsten I Potter, Sharon Lambert, Lori Osborne, Tamara Gathright (1999) A measure of positive and negative affect for children: scale development and preliminary validation. Psychol Assess 11(3):326–338

    Article  Google Scholar 

  21. Lee MK, Kiesler S, Forlizzi J (2010) Receptionist or information kiosk: how do people talk with a robot? In: Proceedings of conference on computer supported cooperative work, pp 31–40

  22. Leite I, Martinho C, Pereira A, Paiva A (2009) As time goes by: long-term evaluation of social presence in robotic companions. In: International symposium on robot and human interactive, communication, pp 669–674

  23. Leite I, Martinho C, Paiva A (2013) Social robots for long-term interaction: a survey. Int J Soc Robot 5:1–18

  24. Leite I, Pereira A, Castellano G, Mascarenhas S, Martinho C, Paiva A (2011) Social robots in learning environments: a case study of an empathic chess companion. In: Proceedings of the international WS on personalization approaches in learning. Environments 732:8–12

  25. Lewis M, Cañamero L (2014) An affective autonomous robot toddler to support the development of self-efficacy in diabetic children. In: Proceedings of the 23rd annual IEEE international symposium on robot and human interactive communication (RO-MAN)

  26. Stephen PL, Brian EN, Symen M, Catherine LL (2001) Facilitating active learning with inexpensive mobile robots. J Comput Sci Coll 16(4):21–33

    Google Scholar 

  27. Markopoulos P, Read J, MacFarlane S, Hoysniemi J (2008) Evaluating children’s interactive products: principles and practices for interaction designers. Morgan Kaufmann

  28. Ng-Thow-Hing V, Sarvadevabhatla RK, Okita S (2011) The learning with kids project: retrospective and status report. In: WS on human-robot interaction: perspectives and contributions to robotics from the human sciences

  29. Office of Disease Prevention and Health Promotion (2015) Physical activity guidelines. http://www.health.gov/paguidelines/

  30. Okita SY, Ng-Thow-Hing V (2009) Learning together: ASIMO developing an interactive learning partnership with children. In: International symposium on robot and human interactive, communication, pp 1125–1130

  31. World Health Organization (2015) A healthy lifestyle. http://www.euro.who.int/en/health-topics/disease-prevention/nutrition/a-healthy-lifestyle

  32. Park S, Moshkina L, Arkin RC (2010) Recognizing nonverbal affective behavior in humanoid robots. Intell Auton Syst 11: IAS-11, 12–21

  33. Robins B, Dautenhahn K, Te Boekhorst R, Billard A (2004) Effects of repeated exposure to a humanoid robot on children with autism. In: Designing a more inclusive world, Springer, New York, pp. 225–236

  34. Robins B, Dautenhahn K (2010) Developing play scenarios for tactile interaction with a humanoid robot: a case study exploration with children with autism. In: Social robotics, vol 6414, pp 243–252. Springer, Berlin. Lecture Notes in Computer Science

  35. Ros R, Baroni I, Demiris Y (2014) Adaptive human–robot interaction in sensorimotor task instruction: from human to robot dance tutors. Robot Auton Syst 62(6):707–720

    Article  Google Scholar 

  36. Raquel R, Yiannis D (2013) Creative dance: an approach for social interaction between robots and children. In: AlbertAli S, Hayley H, Oya A, Hatice G (eds) Human behavior understanding, vol 8212. Springer, New York, pp 40–51 Lecture Notes in Computer Science

    Chapter  Google Scholar 

  37. Ryan RM, Deci EL (2000) Intrinsic and extrinsic motivations: classic definitions and new directions. Contemp Educ Psychol 25(1):54–67

    Article  Google Scholar 

  38. Sabanovic S, Michalowski MP, Caporael LR (2007) Making friends: building social robots through interdisciplinary collaboration. In: Multidisciplinary collaboration for socially assistive robotics: papers from the 2007 AAAI spring symposium, technical report SS-07-07, AAAI, pp 71–77

  39. Brian S (1999) Imitation and mechanisms of joint attention: a developmental structure for building social skills on a humanoid robot. In: ChrystopherL N (ed) Computation for metaphors, analogy, and agents, vol 1562. Springer, Berlin, pp 176–195 Lecture Notes in Computer Science

    Chapter  Google Scholar 

  40. Smith-Autard JM (2002) The art of dance in education. A&C Black Publishers, London

    Google Scholar 

  41. Tanaka F, Cicourel A, Movellan JR (2007) Socialization between toddlers and robots at an early childhood education center. Proc Natl Acad Sci 104(46):17954–17958

    Article  Google Scholar 

  42. Tanaka F, Matsuzoe S (2012) Children teach a care-receiving robot to promote their learning: field experiments at a classroom for vocabulary learning. J Hum–Robot Interact 1(1):78–95

    Google Scholar 

  43. Tanaka F, Movellan JR, Fortenberry B, Kazuki A (2006) Daily hri evaluation at a classroom environment: reports from dance interaction experiments. In: Proceedings of the 1st ACM SIGCHI/SIGART conference on human–robot interaction, ACM, pp 3–9

  44. Richard J (1984) Vallerand and greg reid. On the causal effects of perceived competence on intrinsic motivation: a test of cognitive evaluation theory. J Sport Psychol 6(1):94–102

    Article  Google Scholar 

  45. Wada K, Shibata T (2007) Robot therapy in a care house-change of relationship among the residents and seal robot during a 2-month long study. In: Robot and Human interactive communication. RO-MAN 2007. The 16th IEEE international symposium on, IEEE, pp 107–112

  46. Wada K, Shibata T, Musha T, Kimura S (2005) Effects of robot therapy for demented patients evaluated by eeg. In: IEEE/RSJ international conference on intelligent robots and systems (IROS), IEEE, pp 1552–1557

  47. Wada K, Shibata T, Musha T, Kimura S (2008) Robot therapy for elders affected by dementia. Eng Med Biol Mag, IEEE 27(4):53–60

    Article  Google Scholar 

  48. Wittenburg P, Brugman H, Russel A, Klassmann A, Sloetjes H (2006) ELAN: a professional framework for multimodality research. In: Proceedings of Fifth international conference on language resources and evaluation, pp 1556–1559

Download references

Acknowledgments

The work was supported in part by the EU FP7 ALIZ-E project, Grant No. ICT-248116, and EU H2020 project PAL, Grant H2020-PHC-643783. We wish to thank Sara Bellini, Monica Verga and Marco Mosconi for being a key part of this experience as well as the children, their families and teachers who supported us and participated enthusiastically in this research.

Author information

Authors and Affiliations

  1. Imperial College London, Exhibition Road, SW7 2BT, London, UK

    Raquel Ros & Yiannis Demiris

  2. Fondazione Centro San Raffaele, via Olgettina 60, 20132, Milan, Italy

    Elettra Oleari, Clara Pozzi, Daniele Baranzini & Anahita Bagherzadhalimi

  3. Ospedale San Raffaele, via Olgettina 60, 20132, Milan, Italy

    Francesca Sacchitelli & Alberto Sanna

Authors
  1. Raquel Ros
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Elettra Oleari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Clara Pozzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Francesca Sacchitelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Daniele Baranzini
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Anahita Bagherzadhalimi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Alberto Sanna
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yiannis Demiris
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Raquel Ros.

Appendix

Appendix

The following questionnaires were provided to the participating children during the study period. The formatting has been changed: the originals used images combined with the answers in multiple choice questions and emoticons in the Likert-scale responses to make them more accessible for children. The original questionnaires were given in Italian. The following questionnaires are a translation of these.

1.1 Knowledge Questionnaire (Q1)

  1. Q1.1

    Watching TV, using a PC and playing videogames are activities that we must:

    • Try to avoid

    • Try to do everyday

    • Do daily, also several times a day

  2. Q1.2

    Fruits and vegetables are food that we can eat:

    • Daily, also several times a day

    • Few times a week

    • Rarely, and better try not to eat them

  3. Q1.3

    What should we do daily?

    • Walk, use the stairs, being physically active

    • Play videogames

    • Eat very savory snacks and sweet snacks

  4. Q1.4

    Which food can we eat many times a week?

    • Legumes

    • Cold cuts

    • Eggs

  5. Q1.5

    Which beverage can we daily drink?

    • Milk

    • Energy drink

    • Sugary drink (like cold tea, soft drinks,...)

1.2 Habit Questionnaire (Q2)

  1. Q2.1

    What do you usually drink?

    • Water

    • Coke

    • Orange juice

    • Cold tea

    • Milk

  2. Q2.2

    How many servings of fruit do you eat per day?

    • Less than 1 in a day

    • 1 or 2 in a day

    • 3 or 4 in a day

    • 5 or more

  3. Q2.3

    How many servings of vegetables do you eat per day?

    • Less than 1 time in a day

    • 1 or 2 in a day

    • 3 or 4 in a day

    • 5 or more

  4. Q2.4

    How many times do you eat savory or sweet snacks?

    • Less than 1 time in a week

    • 1-2 times a week

    • 4-5 times a week

    • Daily or several times a day

  5. Q2.5

    Which activity do you usually do in your free time?

    • Watch TV

    • Play at the pc

    • Play sport

    • Go to the park

    • Other, specify:

  6. Q2.6

    If you play with a PC, for how long do you do it?

    • Less than 1 hour

    • Between 1 or 2 hours

    • More than 2 hours

    • I don’t play with a PC

1.3 Parents Questionnaire (Q3)

  1. 1.

    Has your son/daughter spoken spontaneously about the activity done?

  2. 2.

    Has your son/daughter given more attention towards the food in the last week?

  3. 3.

    Has your son/daughter requested more fruits or vegetables in the last week?

  4. 4.

    Has your son/daughter asked you to modify something in HIS/HER food habit?

  5. 5.

    Has your son/daughter asked you information on food composition?

  6. 6.

    Has your son/daughter asked you to modify something in YOUR food habit?

  7. 7.

    Has your son/daughter done more physical activity than the usual (for example walk to school, use the stairs, ride a bicycle, etc.)?

  8. 8.

    Has your son/daughter proposed you to do some physical exercise together (for example walk instead of using the car, use the stairs instead of the lift, etc.)?

1.4 Engagement Questionnaire (Q4)

The questions are reported for both the robot and video study groups. Those highlighted with \((\star )\) were designed and given only to the children interacting with the robot.

  1. 1.

    How fun was the activity with [Nao/the interactive video]?

    • Not fun at all

      figure a

    • Not that fun

      figure b

    • Neutral

      figure c

    • Good fun

      figure d

    • Great fun

      figure e
  2. 2.

    Would you like to play again with [Nao/the interactive video]?

    • Yes

    • No

    • Maybe

  3. 3.

    \((\star )\) How much did you like Nao?

    • Not at all

      figure f

    • Not so much

      figure g

    • Neutral

      figure h

    • A lot

      figure i

    • I loved it

      figure j
  4. 4.

    \((\star )\) In your opinion, Nao seems more like...

    • a friend

    • a pet

    • an adult

    • a toy

    • a computer

  5. 5.

    Did understand what [Nao/the interactive] video was requesting from you?

    • Yes

    • No

    • Sometimes

  6. 6.

    Do you think you’ve learned something new with [Nao/the interactive video]?

    • Yes

    • No

    • Maybe

  7. 7.

    Would you like to learn something else with [Nao/the interactive video]?

    • Yes

    • No

    • Maybe

  8. 8.

    If yes, what would you like to learn with [Nao/the interactive video]?

  9. 9.

    \((\star )\) Choose the word that in your opinion best describes Nao:

    • mechanical

    • kind

    • fun

    • smart

    • fake

    • fragile

    • tender

    • lovely

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ros, R., Oleari, E., Pozzi, C. et al. A Motivational Approach to Support Healthy Habits in Long-term Child–Robot Interaction. Int J of Soc Robotics 8, 599–617 (2016). https://doi.org/10.1007/s12369-016-0356-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12369-016-0356-9

Keywords

Search

Navigation