Skip to main content
Log in

Nonverbal Immediacy as a Characterisation of Social Behaviour for Human–Robot Interaction

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

Abstract

An increasing amount of research has started to explore the impact of robot social behaviour on the outcome of a goal for a human interaction partner, such as cognitive learning gains. However, it remains unclear from what principles the social behaviour for such robots should be derived. Human models are often used, but in this paper an alternative approach is proposed. First, the concept of nonverbal immediacy from the communication literature is introduced, with a focus on how it can provide a characterisation of social behaviour, and the subsequent outcomes of such behaviour. A literature review is conducted to explore the impact on learning of the social cues which form the nonverbal immediacy measure. This leads to the production of a series of guidelines for social robot behaviour. The resulting behaviour is evaluated in a more general context, where both children and adults judge the immediacy of humans and robots in a similar manner, and their recall of a short story is tested. Children recall more of the story when the robot is more immediate, which demonstrates an effect predicted by the literature. This study provides validation for the application of nonverbal immediacy to child–robot interaction. It is proposed that nonverbal immediacy measures could be used as a means of characterising robot social behaviour for human–robot interaction.

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

Access this article

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

Similar content being viewed by others

Notes

  1. http://www.jamescmccroskey.com/measures/nis_o.htm.

  2. https://www.aldebaran.com/en/humanoid-robot/nao-robot.

  3. https://www.engineeredarts.co.uk/robothespian/.

  4. http://freestoriesforkids.com/children/stories-and-tales/robot-virus.

  5. http://www.jamescmccroskey.com/measures/nisf_srni.htm.

  6. http://www.tech.plym.ac.uk/SoCCE/CRNS/staff/JKennedy/Robot_Nonverbal_Immediacy_Questionnaire.

References

  1. Gordon G, Breazeal C, Engel S (2015) Can children catch curiosity from a social robot? In: Proceedings of the 10th ACM/IEEE international conference on human-robot interaction, ACM

  2. Kennedy J, Baxter P, Belpaeme T (2015c) The robot who tried too hard: social behaviour of a robot tutor can negatively affect child learning. In: Proceedings of the 10th ACM/IEEE international conference on human-robot interaction, ACM, pp 67–74. doi:10.1145/2696454.2696457

  3. Short E, Swift-Spong K, Greczek J, Ramachandran A, Litoiu A, Grigore EC, Feil-Seifer D, Shuster S, Lee JJ, Huang S, Levonisova S, Litz S, Li J, Ragusa G, Spruijt-Metz D, Matarić M, Scassellati B (2014) How to train your DragonBot: Socially assistive robots for teaching children about nutrition through play. In: Proceedings of the 23rd IEEE international symposium on robot and human interactive communication, IEEE, RO-MAN, 2014, pp 924–929

  4. Alemi M, Meghdari A, Ghazisaedy M (2014) Employing humanoid robots for teaching english language in Iranian junior high-schools. Int J Hum Robot. doi:10.1142/S0219843614500224

  5. Leite I, McCoy M, Lohani M, Ullman D, Salomons N, Stokes C, Rivers S, Scassellati B (2015) Emotional storytelling in the classroom: individual versus group interaction between children and robots. In: Proceedings of the 10th annual ACM/IEEE international conference on human-robot interaction, ACM, pp 75–82

  6. Kyriakides L, Creemers BP, Antoniou P (2009) Teacher behaviour and student outcomes: suggestions for research on teacher training and professional development. Teach Teach Educ 25(1):12–23

    Article  Google Scholar 

  7. 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: Proceedings of the SIGCHI conference on human factors in computing systems, ACM, New York, NY, USA, CHI’10, pp 1613–1622. doi:10.1145/1753326.1753567

  8. Blanson Henkemans OA, Bierman BP, Janssen J, Neerincx MA, Looije R, van der Bosch H, van der Giessen JA (2013) Using a robot to personalise health education for children with diabetes type 1: a pilot study. Patient Educ Couns 92(2):174–181

    Article  Google Scholar 

  9. Leyzberg D, Spaulding S, Scassellati B (2014) Personalizing robot tutors to individual learning differences. In: Proceedings of the 9th ACM/IEEE international conference on human-robot interaction

  10. Janssen J, van der Wal C, Neerincx M, Looije R (2011) Motivating children to learn arithmetic with an adaptive robot game. Soc Robot 153–162

  11. Bandura A, McClelland DC (1977) Social learning theory. Prentice-Hall, Englewood Cliffs, NJ

    Google Scholar 

  12. Vygotsky LS (1980) Mind in society: the development of higher psychological processes. Harvard University Press, Cambridge

    Google Scholar 

  13. Wu R, Kirkham NZ (2010) No two cues are alike: depth of learning during infancy is dependent on what orients attention. J Exp Child Psychol 107(2):118–136

    Article  Google Scholar 

  14. Roth WM, Lawless DV (2002) When up is down and down is up: body orientation, proximity, and gestures as resources. Lang Soc 31(01):1–28

    Article  Google Scholar 

  15. Strong M, Gargani J, Hacifazlioğlu Ö (2011) Do we know a successful teacher when we see one? experiments in the identification of effective teachers. J Teach Educ 62(4):367–382

    Article  Google Scholar 

  16. Kreijns K, Kirschner PA, Jochems W (2003) Identifying the pitfalls for social interaction in computer-supported collaborative learning environments: a review of the research. Comput Hum Behav 19(3):335–353

    Article  Google Scholar 

  17. Bloom B, Engelhart M, Furst E, Hill W, Krathwohl D (1956) Taxonomy of educational objectives: the classification of educational goals. Handbook I: cognitive domain. Donald McKay, New York

    Google Scholar 

  18. Kennedy J, Baxter P, Senft E, Belpaeme T (2015d) Higher nonverbal immediacy leads to greater learning gains in child-robot tutoring interactions. In: International conference on social robotics

  19. Castellano G, Paiva A, Kappas A, Aylett R, Hastie H, Barendregt W, Nabais F, Bull S (2013) Towards empathic virtual and robotic tutors. Artificial Intelligence in Education. Springer, New York, pp 733–736. doi:10.1007/978-3-642-39112-5_100

  20. Sharma M, Hildebrandt D, Newman G, Young JE, Eskicioglu R (2013) Communicating affect via flight path: exploring use of the laban effort system for designing affective locomotion paths. In: Proceedings of the 8th ACM/IEEE international conference on human-robot interaction, HRI ’13, pp 293–300

  21. Andrist S, Spannan E, Mutlu B (2013) Rhetorical robots: making robots more effective speakers using linguistic cues of expertise. In: Proceedings of the 8th ACM/IEEE international conference on Human-robot interaction, IEEE Press, pp 341–348

  22. Cramer HS, Kemper NA, Amin A, Evers V (2009) The effects of robot touch and proactive behaviour on perceptions of human-robot interactions. In: Proceedings of the 4th ACM/IEEE international conference on human robot interaction, ACM, pp 275–276

  23. Szafir D, Mutlu B (2012) Pay Attention!: designing adaptive agents that monitor and improve user engagement. In: Proceedings of the SIGCHI conference on human factors in computing systems, ACM, New York, NY, USA, CHI’12, pp 11–20. doi:10.1145/2207676.2207679

  24. Zaki J (2013) Cue integration a common framework for social cognition and physical perception. Perspectives on Psychological Science 8(3):296–312

    Article  Google Scholar 

  25. Mehrabian A (1968) Some referents and measures of nonverbal behavior. behav res methods instrum 1(6):203–207

    Article  Google Scholar 

  26. Richmond VP, McCroskey JC, Johnson AD (2003) Development of the nonverbal immediacy scale (NIS): measures of self- and other-perceived nonverbal immediacy. Commun Q 51(4):504–517

    Article  Google Scholar 

  27. Witt PL, Wheeless LR, Allen M (2004) A meta-analytical review of the relationship between teacher immediacy and student learning. Commun Monogr 71(2):184–207

    Article  Google Scholar 

  28. Krathwohl D, Bloom B, Masia B (1964) Taxonomy of educational objectives: The classification of educational goals. Handbook II: the affective domain. Donald McKay, New York

    Google Scholar 

  29. Krathwohl DR (2002) A revision of bloom’s taxonomy: an overview. Theory Pract 41(4):212–218

    Article  Google Scholar 

  30. Gorham J (1988) The relationship between verbal teacher immediacy behaviors and student learning. Commun Educ 37(1):40–53

    Article  Google Scholar 

  31. Chesebro JL, McCroskey JC (2000) The relationship between students’ reports of learning and their actual recall of lecture material: a validity test. Commun Educ 49(3):297–301

    Article  Google Scholar 

  32. McCroskey JC, Sallinen A, Fayer JM, Richmond VP, Barraclough RA (1996) Nonverbal immediacy and cognitive learning: a cross-cultural investigation. Commun Educ 45(3):200–211

    Article  Google Scholar 

  33. Kennedy J, Baxter P, Belpaeme T (2015a) Can less be more? The impact of robot social behaviour on human learning. In: Proceedings of the 4th international symposium on new frontiers in HRI at AISB 2015

  34. Christensen LJ, Menzel KE (1998) The linear relationship between student reports of teacher immediacy behaviors and perceptions of state motivation, and of cognitive, affective, and behavioral learning. Commun Educ 47(1):82–90. doi:10.1080/03634529809379112

    Article  Google Scholar 

  35. Christophel DM (1990) The relationships among teacher immediacy behaviors, student motivation, and learning. Commun Educ 39(4):323–340

    Article  Google Scholar 

  36. Chesebro JL (2003) Effects of teacher clarity and nonverbal immediacy on student learning, receiver apprehension, and affect. Commun Educ 52(2):135–147

    Article  Google Scholar 

  37. Goodboy AK, Weber K, Bolkan S (2009) The effects of nonverbal and verbal immediacy on recall and multiple student learning indicators. J Classr Interact 44(1):4–12

  38. Witt PL, Wheeless LR (2001) An experimental study of teachers’ verbal and nonverbal immediacy and students’ affective and cognitive learning. Commun Educ 50(4):327–342. doi:10.1080/03634520109379259

    Article  Google Scholar 

  39. Chesebro JL, McCroskey JC (1998) The relationship of teacher clarity and teacher immediacy with students experiences of state receiver apprehension. Commun Q 46(4):446–456

    Article  Google Scholar 

  40. Chidambaram V, Chiang YH, Mutlu B (2012) Designing persuasive robots: how robots might persuade people using vocal and nonverbal cues. In: Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction, ACM, pp 293–300

  41. Jeong S, Gu J, Shin DH (2015) I am interested in what you are saying: role of nonverbal immediacy cues in listening. In: Proceedings of the tenth annual ACM/IEEE international conference on human-robot interaction extended abstracts, ACM, pp 129–130

  42. Comstock J, Rowell E, Bowers JW (1995) Food for thought: teacher nonverbal immediacy, student learning, and curvilinearity. Commun Educ 44(3):251–266

    Article  Google Scholar 

  43. Witt PL, Schrodt P (2006) The influence of instructional technology use and teacher immediacy on student affect for teacher and course. Commun Rep 19(1):1–15

    Article  Google Scholar 

  44. Kelly SD, Manning SM, Rodak S (2008) Gesture gives a hand to language and learning: perspectives from cognitive neuroscience, developmental psychology and education. Lang Linguist Compass 2(4):569–588

    Article  Google Scholar 

  45. Macedonia M, von Kriegstein K (2012) Gestures enhance foreign language learning. Biolinguistics 6(3–4):393–416

    Google Scholar 

  46. Goldin-Meadow S, Wagner SM (2005) How our hands help us learn. Trends Cogn Sci 9(5):234–241

    Article  Google Scholar 

  47. Goldin-Meadow S, Kim S, Singer M (1999) What the teacher’s hands tell the student’s mind about math. J Educ Psychol 91(4):720–730. doi:10.1037/0022-0663.91.4.720

    Article  Google Scholar 

  48. Goodwyn SW, Acredolo LP (1998) Encouraging symbolic gestures: A new perspective on the relationship between gesture and speech. New Dir Child Adolesc Dev 79:61–73

    Article  Google Scholar 

  49. Goldin-Meadow S, Nusbaum H, Kelly SD, Wagner S (2001) Explaining math: gesturing lightens the load. Psychol Sci 12(6):516–522

    Article  Google Scholar 

  50. Cook SW, Mitchell Z, Goldin-Meadow S (2008) Gesturing makes learning last. Cognition 106(2):1047–1058

    Article  Google Scholar 

  51. Goldin-Meadow S, Wein D, Chang C (1992) Assessing knowledge through gesture: using children’s hands to read their minds. Cogn Instr 9(3):201–219

    Article  Google Scholar 

  52. Valenzeno L, Alibali MW, Klatzky R (2003) Teachers gestures facilitate students learning: a lesson in symmetry. Contemp Educ Psychol 28(2):187–204

    Article  Google Scholar 

  53. Roth WM (2001) Gestures: their role in teaching and learning. Rev Educ Res 71(3):365–392

    Article  Google Scholar 

  54. Rumme P, Saito H, Ito H, Oi M, Lepe A (2008) Gestures as effective teaching tools: are students getting the point? In: Japanese Cognitive Science Society Meeting 2008

  55. Wang X, Williams MA, Gardenfors P, Vitale J, Abidi S, Johnston B, Kuipers B, Huang A (2014) Directing human attention with pointing. In: 23rd IEEE international symposium on IEEE robot and human interactive communication, 2014 RO-MAN, pp 174–179

  56. Gullberg M, Holmqvist K (2002) Visual attention towards gestures in face-to-face interaction vs. on screen. In: Wachsmuth I, Sowa T (eds) Gesture and sign language in human-computer interaction. Springer, Berlin, pp 206–214

    Chapter  Google Scholar 

  57. Wu R, Gopnik A, Richardson DC, Kirkham NZ (2010) Social cues support learning about objects from statistics in infancy. In: Proceedings of the 32nd annual conference of the cognitive science society, pp 1228–1233

  58. Yu C, Ballard DH (2007) A unified model of early word learning: integrating statistical and social cues. Neurocomputing 70(13):2149–2165

    Article  Google Scholar 

  59. Houston-Price C, Plunkett K, Duffy H (2006) The use of social and salience cues in early word learning. J Exp Child Psychol 95(1):27–55

    Article  Google Scholar 

  60. Powell KL, Roberts G, Nettle D (2012) Eye images increase charitable donations: evidence from an opportunistic field experiment in a supermarket. Ethology 118(11):1096–1101

    Article  Google Scholar 

  61. Boucher JD, Ventre-Dominey J, Dominey PF, Fagel S, Bailly G (2010) Facilitative effects of communicative gaze and speech in human-robot cooperation. In: Proceedings of the 3rd international workshop on affective interaction in natural environments, ACM, New York, NY, USA, AFFINE ’10, pp 71–74. doi:10.1145/1877826.1877845

  62. Okumura Y, Kanakogi Y, Kanda T, Ishiguro H, Itakura S (2013) The power of human gaze on infant learning. Cognition 128(2):127–133

    Article  Google Scholar 

  63. Admoni H, Bank C, Tan J, Toneva M, Scassellati B (2011) Robot gaze does not reflexively cue human attention. In: Processings of the 33rd annual conference of the cognitive science society (2011), pp 1983–1988

  64. Sherwood JV (1987) Facilitative effects of gaze upon learning. Percept Mot Skills 64(3c):1275–1278

    Article  Google Scholar 

  65. Otteson JP, Otteson CR (1979) Effect of teacher’s gaze on children’s story recall. Percept Mot Skills 50(1):35–42

    Article  Google Scholar 

  66. Dalzel-Job O, Oberlander J, Smith TJ (2011) Don’t look now: the relationship between mutual gaze, task performance and staring in second life. In: Proceedings of the 33rd annual conference of the cognitive science society, pp 832–837

  67. Kennedy J, Baxter P, Belpaeme T (2015b) Comparing robot embodiments in a guided discovery learning interaction with children. Int J Social Robot 7(2):293–308. doi:10.1007/s12369-014-0277-4

    Article  Google Scholar 

  68. Looije R, van der Zalm A, Neerincx MA, Beun RJ (2012) Help, I need some body the effect of embodiment on playful learning. In: The 21st IEEE international symposium on robot and human interactive communication, IEEE, RO-MAN 2012, pp 718–724. doi:10.1109/ROMAN.2012.6343836

  69. Atkinson RK, Mayer RE, Merrill MM (2005) Fostering social agency in multimedia learning: examining the impact of an animated agents voice. Contemp Educ Psychol 30(1):117–139

    Article  Google Scholar 

  70. Mayer RE, Sobko K, Mautone PD (2003) Social cues in multimedia learning: role of speaker’s voice. J Educ Psychol 95(2):419–425

    Article  Google Scholar 

  71. Mori M, MacDorman KF, Kageki N (2012) The uncanny valley [from the field]. IEEE Robot Autom Mag 19(2):98–100

    Article  Google Scholar 

  72. Baylor A, Ryu J, Shen E (2003) The effects of pedagogical agent voice and animation on learning, motivation and perceived persona. In: World conference on educational multimedia, hypermedia and telecommunications, pp 452–458

  73. Remland MS, Jones TS (1994) The influence of vocal intensity and touch on compliance gaining. J Soc Psychol 134(1):89–97

    Article  Google Scholar 

  74. Simonds BK, Meyer KR, Quinlan MM, Hunt SK (2006) Effects of instructor speech rate on student affective learning, recall, and perceptions of nonverbal immediacy, credibility, and clarity. Commun Res Rep 23(3):187–197. doi:10.1080/08824090600796401

    Article  Google Scholar 

  75. Fulford CP (1992) Systematically designed text enhanced with compressed speech audio. In: Proceedings of selected research and development presentations at the convention of the association for educational communications and technology

  76. Velez JJ, Cano J (2008) The relationship between teacher immediacy and student motivation. J Agric Educ 49(3):76–86

    Article  Google Scholar 

  77. Becker-Asano C, Stahl P, Ragni M, Courgeon M, Martin JC, Nebel B (2013) An affective virtual agent providing embodied feedback in the paired associate task: system design and evaluation. In: Intelligent Virtual Agents, Springer, pp 406–415

  78. Peters P (2007) Gaining compliance through non-verbal communication. Pepperdine Dispute Resolut Law J 7(1):87–112

    Google Scholar 

  79. Segrin C (1993) The effects of nonverbal behavior on outcomes of compliance gaining attempts. Commun Stud 44(3–4):169–187

    Article  Google Scholar 

  80. Greene LR (1977) Effects of verbal evaluation feedback and interpersonal distance on behavioral compliance. J Couns Psychol 24(1):10

    Article  MathSciNet  Google Scholar 

  81. Hiroi Y, Ito A (2011) Influence of the size factor of a mobile robot moving toward a human on subjective acceptable distance. Mob Robots Curr Trends. doi:10.5772/26512

  82. Kim Y, Mutlu B (2014) How social distance shapes humanrobot interaction. Int J Hum Comput Stud 72(12):783–795. doi:10.1016/j.ijhcs.2014.05.005

    Article  Google Scholar 

  83. Walters ML, Dautenhahn K, Te Boekhorst R, Koay KL, Kaouri C, Woods S, Nehaniv C, Lee D, Werry I (2005) The influence of subjects’ personality traits on personal spatial zones in a human-robot interaction experiment. In: IEEE international workshop on Robot and human interactive communication, 2005. ROMAN 2005, IEEE, pp 347–352

  84. Kennedy J, Baxter P, Belpaeme T (2014) Children comply with a robot’s indirect requests. In: Proceedings of the 9th ACM/IEEE international conference on human-robot interaction, pp 198–199. doi:10.1145/2559636.2559820

  85. Aiello JR, Aiello TDC (1974) The development of personal space: proxemic behavior of children 6 through 16. Hum Ecol 2(3):177–189

    Article  Google Scholar 

  86. Huettenrauch H, Severinson Eklundh K, Green A, Topp E (2006) Investigating spatial relationships in human-robot interaction. In: IEEE/RSJ international conference on intelligent robots and systems, pp 5052–5059. doi:10.1109/IROS.2006.282535

  87. Takayama L, Pantofaru C (2009) Influences on proxemic behaviors in human-robot interaction. In: IEEE/RSJ international conference on intelligent robots and systems, pp 5495–5502. doi:10.1109/IROS.2009.5354145

  88. Mumm J, Mutlu B (2011) Human-robot proxemics: physical and psychological distancing in human-robot interaction. In: Proceedings of the 6th international conference on human-robot interaction, ACM, HRI ’11, pp 331–338. doi:10.1145/1957656.1957786

  89. Rae I, Takayama L, Mutlu B (2013) The influence of height in robot-mediated communication. In: Proceedings of the 8th ACM/IEEE international conference on Human-robot interaction, IEEE Press, pp 1–8

  90. Fisher JD, Rytting M, Heslin R (1976) Hands touching hands: affective and evaluative effects of an interpersonal touch. Sociometry 39(4):416–421

  91. Fukuda H, Shiomi M, Nakagawa K, Ueda K (2012) ‘Midas touch’ in human-robot interaction: evidence from event-related potentials during the ultimatum game. In: Proceedings of the 7th ACM/IEEE international conference on human-robot interaction, ACM, pp 131–132

  92. Gurung RA, Vespia K (2007) Looking good, teaching well? linking liking, looks, and learning. Teach Psychol 34(1):5–10

    Google Scholar 

  93. Guéguen N (2002) Touch, awareness of touch, and compliance with a request. Perceptual and motor skills 95(2):355–360

    Article  Google Scholar 

  94. Salter T, Dautenhahn K, te Boekhorst R (2006) Learning about natural human-robot interaction styles. Robot Auton Syst 54(2):127–134

    Article  Google Scholar 

  95. Byrd CE, McNeil N, D’Mello S, Cook SW (2014) Gesturing may not always make learning last. In: Proceedings of the 36th annual conference of the cognitive science society, pp 1982–1987

  96. Langton SR (2000) The mutual influence of gaze and head orientation in the analysis of social attention direction. Q J Exp Psychol A 53(3):825–845

    Article  Google Scholar 

  97. Langton SR, Bruce V (2000) You must see the point: automatic processing of cues to the direction of social attention. J Exp Psychol Hum Percept Perform 26(2):747

    Article  Google Scholar 

  98. Lohan KS, Rohlfing K, Saunders J, Nehaniv C, Wrede B (2012) Contingency scaffolds language learning. In: IEEE international conference on development and learning and epigenetic robotics, ICDL, pp 1–6

  99. Anderson LW (1975) Student involvement in learning and school achievement. Calif J Educ Res 26(2):53–62

    Google Scholar 

  100. Richmond VP, McCroskey JC (1998) Nonverbal communication in interpersonal relationships, 3rd edn. Allyn and Bacon, Boston

    Google Scholar 

  101. Hulme C, Tordoff V (1989) Working memory development: the effects of speech rate, word length, and acoustic similarity on serial recall. J Exp Child Psychol 47(1):72–87. doi:10.1016/0022-0965(89)90063-5

    Article  Google Scholar 

  102. Borgers N, Sikkel D, Hox J (2004) Response effects in surveys on children and adolescents: the effect of number of response options, negative wording, and neutral mid-point. Qual Quant 38(1):17–33

    Article  Google Scholar 

  103. Borgers N, De Leeuw E, Hox J (2000) Children as respondents in survey research: cognitive development and response quality 1. Bulletin de methodologie Sociologique 66(1):60–75

    Article  Google Scholar 

  104. Dede C (2009) Immersive interfaces for engagement and learning. Science 323(5910):66–69

    Article  Google Scholar 

  105. Pickett CL, Gardner WL, Knowles M (2004) Getting a cue: the need to belong and enhanced sensitivity to social cues. Pers Soc Psychol Bull 30(9):1095–1107

    Article  Google Scholar 

  106. Witkin HA, Moore CA, Goodenough DR, Cox PW (1977) Field-dependent and field-independent cognitive styles and their educational implications. Rev Educ Res 1–64

  107. Bauminger N (2002) The facilitation of social-emotional understanding and social interaction in high-functioning children with autism: intervention outcomes. J Autism Dev Disord 32(4):283–298

    Article  Google Scholar 

  108. Hall CW, Peterson AD, Webster RE, Bolen LM, Brown MB (1999) Perception of nonverbal social cues by regular education, ADHD, and ADHD/LD students. Psychol Sch 36(6):505–514

  109. Jellema T, Lorteije J, van Rijn S, van t’Wout M, de Haan E, van Engeland H, Kemner C (2009) Involuntary interpretation of social cues is compromised in autism spectrum disorders. Autism Res 2(4):192–204

    Article  Google Scholar 

  110. Bailenson J, Blascovich J, Beall A, Loomis J (2001) Equilibrium theory revisited: mutual gaze and personal space in virtual environments. Presence 10(6):583–598

    Article  Google Scholar 

  111. Bailenson JN, Blascovich J, Beall AC, Loomis JM (2003) Interpersonal distance in immersive virtual environments. Pers Soc Psychol Bull 29(7):819–833

    Article  Google Scholar 

  112. Bailenson JN, Beall AC, Loomis J, Blascovich J, Turk M (2005) Transformed social interaction, augmented gaze, and social influence in immersive virtual environments. Hum Commun Res 31(4):511–537

    Article  Google Scholar 

  113. Bull R, Gibson-Robinson E (1981) The influences of eye-gaze, style of dress, and locality on the amounts of money donated to a charity. Hum Relat 34(10):895–905

    Article  Google Scholar 

  114. Baylor AL, Kim Y (2004) Pedagogical agent design: the impact of agent realism, gender, ethnicity, and instructional role. Intelligent Tutoring Systems. Springer, New York, pp 592–603

    Chapter  Google Scholar 

  115. Coe R, Aloisi C, Higgns S, Major LE (2014) What makes great teaching?. Review of the underpinning research. Tech. rep, Sutton Trust

  116. Hill HC, Rowan B, Ball DL (2005) Effects of teachers mathematical knowledge for teaching on student achievement. Am Educ Res J 42(2):371–406

    Article  Google Scholar 

  117. Askew M, Brown M, Rhodes V, Johnson D, Wiliam D (1997) Effective teachers of numeracy. Kings College, London

    Google Scholar 

  118. Garner PW (2010) Emotional competence and its influences on teaching and learning. Educ Psychol Rev 22(3):297–321

    Article  MathSciNet  Google Scholar 

  119. Ronfeldt M, Loeb S, Wyckoff J (2012) How teacher turnover harms student achievement. Am Educ Res J 50(1):4–36. doi:10.3102/0002831212463813

    Article  Google Scholar 

  120. Wang N, Johnson WL, Gratch J (2010) Facial expressions and politeness effect in foreign language training system. In: Intelligent tutoring systems, Springer, pp 165–173

  121. Bloom BS (1984) The 2 sigma problem: the search for methods of group instruction as effective as one-to-one tutoring. Educ Res 13:4–16

    Article  Google Scholar 

  122. VanLehn K (2011) The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educ Psychol 46(4):197–221

    Article  Google Scholar 

  123. Beebe B, Jaffe J, Lachmann F (1992) A dyadic systems view of communication. In: Warshaw S (ed) Relational perspectives in psychoanalysis. Analytic Press, Hillsdale, NJ

    Google Scholar 

  124. Jaffe J, Beebe B, Feldstein S, Crown CL, Jasnow MD, Rochat P, Stern DN (2001) Rhythms of dialogue in infancy: coordinated timing in development. Monogr Soc Res Child Dev 66(2):i–149

  125. Green J, Weade R (1985) Reading between the words: social cues to lesson participation. Theory Pract 24(1):14–21. doi:10.1080/00405848509543141

    Article  Google Scholar 

  126. Nicol D, Minty I, Sinclair C (2003) The social dimensions of online learning. Innov Educ Teach Int 40(3):270–280

    Article  Google Scholar 

  127. Baxter P, Wood R, Baroni I, Kennedy J, Nalin M, Belpaeme T (2013) Emergence of turn-taking in unstructured child-robot social interactions. In: Proceedings of the 8th ACM/IEEE international conference on human-robot interaction, IEEE Press, pp 77–78

  128. Zajonc RB (1965) Social facilitation. Science 149(3681):269–274

    Article  Google Scholar 

Download references

Acknowledgments

This research was partially funded by the EU FP7 DREAM project (FP7-ICT-611391) and the School of Computing and Maths, Plymouth University, UK. Thanks goes to CAEN Community Primary School, Braunton, UK. for taking part in the evaluation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to James Kennedy.

Appendices

Appendix 1: Short Story Script

The following is the short story script as used in all evaluation conditions. The story is largely based on one from the following website: http://freestoriesforkids.com/children/stories-and-tales/robot-virus (produced here with permission from the author).

Hello, I’m Charlie. Today I’m going to tell you one of my favourite robot stories. It is about a boy, his name is Ricky, and his robot helper, Johnny. Ricky lived in a lovely futuristic house, which had everything you could ever want. Though he didn’t help much around the house, Ricky was still as pleased as punch when his parents bought him the latest model of helper robot. As soon as it arrived, off it went; cooking, cleaning, ironing, and—most importantly—gathering up old clothes from Ricky’s bedroom floor, which Ricky didn’t like having to walk on.

On that first day, when Ricky went to sleep, he had left his bedroom in a truly disastrous state. When he woke up the next morning, everything was perfectly clean and tidy. In fact, it was actually too clean. Ricky could not find his favourite blue skateboard. However much he searched, it did not reappear, and the same was starting to happen with other things. Ricky looked with suspicion at the gleaming helper robot. He hatched a plan to spy on the robot, and began following it around the house.

Finally he caught it red-handed. It was picking up a toy to hide it. Off he went, running to his parents, to tell them that the helper was broken and badly programmed. Ricky asked them to have it changed. But his parents said absolutely not; it was impossible, they were delighted with the new helper, and that it was the best cleaner they had ever met. So Ricky needed to get some kind of proof; maybe take some hidden photos. He kept nagging his parents for three whole weeks about how much good stuff the robot was hiding. Ricky argued that this was not worth the clean house because toys are more important.

One day the robot was whirring past, and heard the boy’s complaints. The robot returned with five of his toys, and some clothes for him.“Here sire, I did not know it was bothering you”, said the helper, with its metallic voice. “How could it not you thief?! You’ve been nicking my stuff for weeks”, the boy answered, furiously. The robot replied, “the objects were left on the floor. I therefore calculated that you did not like them. I am programmed to collect all that is not wanted, and at night I send it to places other humans can use it. I am a maximum efficiency machine. Did you not know?”.

Ricky started feeling ashamed. He had spent all his life treating things as though they were useless. He looked after nothing. Yet it was true that many other people would be delighted to treat those things with all the care in the world. And he understood that the robot was neither broken nor badly programmed, rather, it had been programmed extremely well! Since then, Ricky decided to become a Maximum Efficiency Boy, and he put real care into how he treated his things. He kept them tidy, and made sure that he didn’t have more than was necessary. And, often, he would buy things, and take them along with his good friend, the robot, to help out those other people who needed them.

The end... I hope you enjoyed the story. Goodbye!

Appendix 2: Robot Nonverbal Immediacy Questionnaire (RNIQ)

The following is the questionnaire used by participants in the evaluation to rate the nonverbal immediacy of the robot, as based on the short-form nonverbial immediacy scale-observer report. The directions are provided verbally by the experimenter, so the top of the survey simply asks to ‘please put a circle around your choice for each question’. Options are provided in equally sized boxes below each question. The options are: 1 = Never; 2 = Rarely; 3 = Sometimes; 4 = Often; 5 = Very Often. The questions are as follows:

  1. 1.

    The robot uses its hands and arms to gesture while talking to you

  2. 2.

    The robot uses a dull voice while talking to you

  3. 3.

    The robot looks at you while talking to you

  4. 4.

    The robot frowns while talking to you

  5. 5.

    The robot has a very tense body position while talking to you

  6. 6.

    The robot moves away from you while talking to you

  7. 7.

    The robot varies how it speaks while talking to you

  8. 8.

    The robot touches you on the shoulder or arm while talking to you

  9. 9.

    The robot smiles while talking to you

  10. 10.

    The robot looks away from you while talking to you

  11. 11.

    The robot has a relaxed body position while talking to you

  12. 12.

    The robot stays still while talking to you

  13. 13.

    The robot avoids touching you while talking to you

  14. 14.

    The robot moves closer to you while talking to you

  15. 15.

    The robot looks keen while talking to you

  16. 16.

    The robot is bored while talking to you

Scoring

Step 1 Add the scores from the following items:1, 3, 7, 8, 9, 11, 14, and 15.

Step 2 Add the scores from the following items:2, 4, 5, 6, 10, 12, 13, and 16.

Total Score = 48 plus Step 1 minus Step 2.

This questionnaire can also be downloaded online.Footnote 6 The online version has been modified from the version shown here as children commonly did not understand the word ‘varies’ in question 7, so this now reads ‘changes’.

Appendix 3: Recall Quesionnaire

The following questions are those used in the recall questionnaire; in brackets after each question are the possible answers.

  1. 1.

    What is the name of the boy in the story? {Ricky, Mickey, Harry, Jeff}

  2. 2.

    What is the name of the robot in the story? {Rupert, John, Johnny, George}

  3. 3.

    What was the most important thing for the robot to pick up from the floor of the boy’s bedroom? {clothes, food, toys, t-shirts}

  4. 4.

    What did the boy think about doing to get proof of the robot taking his things? {taking photos, shouting at it, taking video, telling his parents}

  5. 5.

    What toy couldn’t the boy find the first day after the robot had tidied? {orange skateboard, games console, blue skateboard, blue doll}

  6. 6.

    How many toys did the robot give back to the boy after he complained? {eight (8), five (5), three (3), six (6)}

  7. 7.

    How long did the boy complain to his parents for? {three (3) weeks, eight (8) days, three (3) days, four (4) weeks}

  8. 8.

    What type of boy did he decide to be at the end of the story? {maximum efficiency, tidy, minimum efficiency, messy}

  9. 9.

    What type of robot is the one in the story? {angry, purple, helper, flying}

  10. 10.

    What is the robot in the story especially good at? {ironing, swimming, jumping, cleaning}

  11. 11.

    What was the moral of the story? free text answer

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kennedy, J., Baxter, P. & Belpaeme, T. Nonverbal Immediacy as a Characterisation of Social Behaviour for Human–Robot Interaction. Int J of Soc Robotics 9, 109–128 (2017). https://doi.org/10.1007/s12369-016-0378-3

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12369-016-0378-3

Keywords

Navigation