domain: scco shs

text:
Frank Jamet

Keywords:

Chai pas, faut qu'j'demande à ma mère »

Introduction

L'objectif de ce travail est de présenter les premiers résultats d'une recherche sur la genèse de la notion d'âge chez l'enfant de 3 à 5 ans, travail qui s'inscrit dans une perspective développementale plus large. Après avoir brossé un état de la littérature sur le domaine, nous développerons un modèle théorique pour rendre compte ensuite des performances des enfants. Nous terminerons notre propos par une illustration à l'aide de protocoles individuels.

Si la littérature sur le concept de temps est abondante [START_REF] Crépault | Raisonnement et psychogénèse du temps : de Störring aux paradigmes et modèles du raisonnement temporel[END_REF][START_REF] Jamet | Raisonnement temporel : étude génétique de l'indécidabilité de l'enfant à l'expert[END_REF], traduisant sa complexité, si bon nombre d'études sur le temps-convention ont été conduites [START_REF] Friedman | Children's representation of a pattern of daily activites[END_REF][START_REF] Godard | Le développement de la localisation dans le temps chez des enfants de 5 à 9 ans de milieux socio-économique différents[END_REF], les travaux spécifiques sur la notion d'âge sont, à notre connaissance, plus rares. L'examen de la littérature nous montre que la majorité des études porte sur des populations occidentales [START_REF] Binet | Le développement de l'intelligence chez l'enfant[END_REF][START_REF] Decroly | Études de psychogénèse[END_REF][START_REF] Looft | Children's judgements of age[END_REF][START_REF] Piaget | Le développement de la notion de temps chez l'enfant[END_REF][START_REF] Ziadé | Quel âge as-tu ? » : une étude sur la notion d'âge chez les enfants de 6 à 10 ans[END_REF]. A notre connaissance, seuls deux travaux s'inscrivent dans le cadre d'une approche culturelle comparative [START_REF] Aaron | Two studies on concept development and their curricular implications[END_REF][START_REF] Koudou-Kessie | La notion de temps chez les enfants ivoiriens de 6 à 12 ans[END_REF].

Les premières données sur la notion d'âge se trouvent dans l'échelle métrique d'intelligence de Binet & Simon (1908). A 6 ans, il est attendu que la majorité des enfants réponde correctement à la question « Quel âge as-tu ? ». La réponse prévue porte sur la valeur numérique « j'ai 6 ans » et non pas sur la date de naissance. Les auteurs remarquent que si l'enfant commet une erreur, elle porte souvent dans le sens d'un rajeunissement. [START_REF] Decroly | Études de psychogénèse[END_REF] consacre le texte le plus conséquent sur cette notion. Méthodologiquement, l'auteur recourt, d'une part, à l'étude de protocoles en questionnant sa fille entre l'âge de 4 et 6 ans, et d'autre part présente des données quantitatives recueillies sur une classe d'enfants « tout venant » et sur quelques enfants de classe spécialisée.

L'étude des protocoles individuels permet à Decroly de brosser un tableau des compétences du jeune enfant d'un point de vue développemental. L'enfant de 4 ans peut indiquer son âge, sans pour autant savoir ce que cela représente. En effet, l'âge est lié à la taille. L'auteur observe que ces deux notions sont initialement confondues. Elles ne sont pas reliées à l'idée de nombre mais plutôt à celle de croissance (« plus on mange, plus on est grand ») ou à une notion plus générale : « c'est une grande fille parce qu'elle a beaucoup d'affaires, elle ». A 4;5 ans, les qualificatifs de jeune, vieux, plus jeune et plus vieux sont associés à l'âge (c'est un vieux chien, c'est un vieil homme). Entre 4;5 et 4;6 ans, l'enfant estime l'âge de ses poupées en fonction de leur taille. Lorsque le jugement porte sur des personnes, la barbe constitue un nouveau critère. Pour l'enfant de cet âge, il signe un âge avancé. A 5 ans, l'enfant pense que l'on change d'âge en fonction de la décision paternelle. Il faut attendre l'âge de 5;1 ans pour que l'enfant s'intéresse à l'âge des autres. La construction de la pensée diachronique, pensée qui consiste à s'interroger sur l'évolution du passé et du futur des choses, apparaît vers 5;3 ans. A 5;4 ans, l'enfant sait que s'il grandit, les autres grandissent également. A 5;5 ans, on observe encore l'attribution de son propre âge à celui d'autrui. A 5;6 ans, la notion d'âge se lie avec le savoir. L'enfant de 5;10 ans s'interroge sur l'âge qu'il a à sa naissance. Sa réponse est alors : « j'ai 1 an ». A 5;11 ans, l'enfant est étonné d'entendre qu'un animal a un âge. Pour l'âge de l'année antérieure, il semble que vers 6 ans, la majorité des enfants donne une réponse exacte. Decroly explique cette réponse par la concordance du développement de la notion de nombre. Il en va de même pour l'année postérieure.

Les résultats des enquêtes collectées par Decroly montrent qu'à 6 ans, les enfants sont en mesure de donner une réponse exacte aux questions « Quel âge avais-tu l'année dernière ? » et « Quel âge aurastu l'année prochaine ? ». A 7 ans, certains enfants commencent à répondre qu'ils connaissent leur âge sans pour autant faire référence aux dires de leurs parents, ainsi que l'âge à leur naissance.

Pour [START_REF] Piaget | Le développement de la notion de temps chez l'enfant[END_REF], la notion d'âge se construit de la même manière que la notion de temps dans ses rapports avec la vitesse et l'espace. Elle se développe au travers de trois stades.

Durant le premier stade, les âges sont indépendants de l'ordre des naissances et les différences d'âges peuvent se modifier avec le temps. Les enfants n'arrivent pas à affirmer qu'ils sont nés après leurs aînés. Ils s'attribuent fréquemment une antériorité.

Avec le second stade, c'est tantôt la succession correcte qui précède la compréhension des durées, tantôt la durée correcte qui précède la succession. Dans le premier cas, l'enfant saura sérier les naissances, mais il n'en conclura pas à la permanence des différences d'âges ; et dans le second cas, il découvre que ces différences se conservent mais il n'en conclut pas à l'ordre des successions correctes des naissances. D'autres sujets comprennent la conservation des différences d'âges (durée de vieillissement) mais sont dans l'impossibilité de conclure à l'ordre correct de la succession des naissances. Le sujet peut sans difficulté affirmer la différence de cinq ans entre son ami et lui, mais se trouve dans l'incapacité de conclure qui est né le premier. Cette évolution, par rapport au stade précédent, est le résultat d'intuitions articulées qui portent soit sur l'ordre des naissances, soit sur les différences d'âges.

Au dernier stade, l'enfant est à même de coordonner l'ordre de successions des naissances et l'emboîtement des âges avec une conservation exacte des différences. Cette évolution est tout à fait identique à la construction du temps « physique ».

La construction de l'âge consiste à coordonner des mouvements et des vitesses. La croissance équivaut aux trajectoires spatiales, et la rapidité plus ou moins grande de cette croissance correspond aux différences de vitesse. Dans les deux domaines (temps physique et âge) au stade I, il y a confusion de la durée avec le chemin parcouru, comme il y a confusion entre l'âge et la taille. Dans les deux cas, il y a incompréhension de l'ordre des événements, par indifférenciation de la succession temporelle et de la succession spatiale. Au stade II, on observe une correction partielle des intuitions primitives de la notion d'âge comme celle du temps « physique ». Le troisième stade est caractérisé par une coordination de nature opératoire grâce au groupement des rapports en jeu. Le sujet parvient à déduire, indifféremment, les âges de l'ordre des naissances ou à déduire l'ordre de la succession de l'emboîtement des âges.

La recherche de [START_REF] Looft | Children's judgements of age[END_REF] a porté sur la relation entre la taille et l'attribution d'un âge chez l'enfant de 3 à 9 ans. Pour ce faire, il propose la tâche suivante : il présente à l'enfant 28 couples de dessins représentant des personnages à quatre périodes de la vie (premier âge, enfance, adolescence, âge adulte). Ces personnages sont de deux tailles. Si l'on croise tous les possibles et que l'on élimine les couples « même ; même », on obtient 28 paires. La tâche de l'enfant est d'indiquer si les deux personnages ont le même âge ou si l'un des deux est plus âgé. Les résultats montrent que l'on passe de 40% de réponses correctes à 3 ans à 81% à 9 ans. Alors que la fréquence de jugements fondés sur la taille est de 6,7 (en moyenne) pour le sujet de 3 ans, cette dernière chute à 2,3 à 9 ans. L'auteur interprète ces résultats dans le cadre de la théorie piagétienne comme une traduction du primat du perceptif (caractéristique du stade préopératoire) sur celui des opérations. L'évolution des réponses observées à l'âge de 8-9 ans s'explique par l'accession de l'enfant à une forme opératoire de pensée.

Le travail de Ziadé, Cronier & Zazzo (1981) résulte d'un étonnement de Zazzo qui, au cours de nombreux examens cliniques, constate que, si certes l'enfant est en mesure de répondre correctement à la question « Quel âge as-tu ? », il a beaucoup plus de mal à répondre à la question « Depuis combien de temps es-tu né ? » Les auteurs ont interrogé 88 enfants de 6 à 10 ans à l'aide d'un questionnaire comportant cinq questions : « Quel âge as-tu ? », « Depuis combien de temps es-tu né ? », « Comment as-tu fait pour savoir ? », « Qui peut nous le dire ? », « Qui sait ? ». Les résultats montrent que la quasi-totalité des enfants de 6 à 10 ans interrogés répond correctement à la première question (« Quel âge as-tu ? »). En effet, seuls deux enfants donnent un âge inexact. On constate que si l'enfant de 6 ans donne son âge, il est dans l'incapacité de le justifier. En revanche, sa mère le sait. Il faut attendre l'âge de 10 ans pour que l'ensemble des enfants fournisse une réponse chiffrée exacte à la question « Depuis combien de temps es-tu né ? » Comme nous pouvons le voir, en fonction des différentes études, les âges de référence des compétences relatives à la notion d'âge diffèrent. Les raisons peuvent s'expliquer, entre autres, par les diverses méthodes de recueil des données. Si la littérature nous donne des points de repères quant à la maîtrise des compétences relatives à la notion d'âge, seule la théorie piagétienne offre un cadre théorique pour en expliquer l'évolution. La maîtrise de la notion d'âge implique, d'une part, la mise en oeuvre et la coordination d'opérations complexes, et d'autre part, de disposer des connaissances relatives aux systèmes conventionnels. Ces opérations complexes relatives à l'ordre temporel portent sur la succession : « être né avant ou être né après » ; sur la simultanéité : « être né en même temps » ; sur la durée : « j'ai tel âge » mais également sur l'emboîtement des durées, la récurrence ainsi que la notion de cycle. Les connaissances nécessaires portent sur les systèmes du temps-convention comme les moments de la journée (matin, midi, après-midi, soir), les jours de la semaine, les mois de l'année, les saisons, les années. Les travaux de Piaget (1946a) montrent que ce n'est pas avant l'âge de 8 ans que l'enfant est en mesure de maîtriser ces opérations appliquées au temps. Il constate également qu'en fonction de certains dispositifs, cette maîtrise se décale dans le temps (Piaget, 1946b). Pour [START_REF] Friedman | Children's representation of a pattern of daily activites[END_REF], la mise en oeuvre de ces opérations temporelles dans le domaine du tempsconvention n'apparaît pas avant 9 ans et se poursuit jusqu'à l'adolescence lorsque l'on aborde la coordination des périodes historiques. D'une manière générale, les travaux exposés dans la revue de questions montrent que la perspective temporelle relative à la notion d'âge s'accroît avec le développement du sujet. A 4 ans, l'enfant peut indiquer son âge en référence aux dires de sa mère [START_REF] Decroly | Études de psychogénèse[END_REF][START_REF] Ziadé | Quel âge as-tu ? » : une étude sur la notion d'âge chez les enfants de 6 à 10 ans[END_REF]. L'âge est, dans la perspective temporelle, réduit en un point. A 5 ans, il peut indiquer l'âge qu'il aura après son anniversaire [START_REF] Ames | The development of sense of time in the young child[END_REF]. La perspective temporelle de l'âge s'inscrit dans un mouvement à deux unités. A 6 ans, elle acquiert davantage de mobilité. L'enfant connaît l'âge qu'il avait avant et celui qu'il aura après son anniversaire [START_REF] Decroly | Études de psychogénèse[END_REF]. A 10 ans, l'âge est déduit à partir d'un calcul [START_REF] Ziadé | Quel âge as-tu ? » : une étude sur la notion d'âge chez les enfants de 6 à 10 ans[END_REF].

L'introduction de la mobilité dans la perspective temporelle relative à l'âge est tout à fait compatible avec les travaux de Piaget (1946a) en ce qui concerne les opérations temporelles, mais également avec les modèles néopiagétiens [START_REF] Case | The role of central conceptual structures in the development of children's thought[END_REF][START_REF] Halford | Children's understanding. The development of mental models[END_REF] et post-piagétiens [START_REF] Crépault | Raisonnement et psychogénèse du temps : de Störring aux paradigmes et modèles du raisonnement temporel[END_REF][START_REF] Jamet | Raisonnement temporel : étude génétique de l'indécidabilité de l'enfant à l'expert[END_REF]) pour ce qui touche à la capacité de traitement de l'information.

Nous faisons l'hypothèse que :

 l'évolution de la nature des arguments pour justifier l'âge devrait être le suivant : (1) la référence aux parents [START_REF] Decroly | Études de psychogénèse[END_REF][START_REF] Ziadé | Quel âge as-tu ? » : une étude sur la notion d'âge chez les enfants de 6 à 10 ans[END_REF], (2) la référence à l'anniversaire et enfin (3) se fonder sur une justification quantitative [START_REF] Piaget | Le développement de la notion de temps chez l'enfant[END_REF] ;

 l'enfant de 3-4 ans donnera son âge et échouera à indiquer celui qu'il avait avant et l'âge qu'il aura après [START_REF] Decroly | Études de psychogénèse[END_REF][START_REF] Ziadé | Quel âge as-tu ? » : une étude sur la notion d'âge chez les enfants de 6 à 10 ans[END_REF]. A 4-5 ans, il mentionnera l'âge qu'il aura l'année prochaine [START_REF] Ames | The development of sense of time in the young child[END_REF]. A 5-6 ans, il sera capable d'indiquer son âge, celui qu'il avait l'année dernière et celui qu'il aura l'année prochaine [START_REF] Decroly | Études de psychogénèse[END_REF].

Méthode

Nous avons interrogé à ce jour 71 enfants, garçons et filles, âgés de 3 à 5 ans : 12 enfants de 3 ans (âge moyen 3;6 ans, min. 3;1, max. 3;11) ; 27 enfants de 4 ans (âge moyen 4;3 ans, min. 4;0, max. 4;11) et 32 enfants de 5 ans (âge moyen 5;4 ans, min. 5;0, max. 5;11). Ils ont été soumis individuellement à un entretien clinique piagétien.

Cet entretien a été structuré autour de deux thèmes, soit une douzaine de questions relatives à la notion d'âge : « Quel âge as-tu ? », « Comment sais-tu que tu as cet âge ? », « Pourquoi as-tu cet âge ? », « L'année prochaine, tu auras quel âge ? », « L'année dernière, tu avais quel âge ? », etc. et sept questions relatives à l'anniversaire : « Qu'est-ce qu'un anniversaire ? », « Qu'est-ce que l'on fête à un anniversaire ? », « Combien de bougies as-tu soufflé lors de ton anniversaire ? », etc. En fonction de l'âge, l'entretien clinique dure entre 10 et 25 minutes.

Résultats

Après avoir présenté les résultats à la question « Quel âge as-tu ? », nous examinerons la distribution des trois types de justifications : la référence aux parents, la référence à l'anniversaire et la référence à un processus quantitatif pour enfin examiner la profondeur de la perspective temporelle : connaissance de l'âge que l'on avait avant son anniversaire et celui que l'on aura après.

Les résultats montrent que 90% des enfants de 3 ans donnent une réponse correcte à la question relative à l'âge, ainsi que la totalité des 4 ans et des 5 ans.

Graphique 1 : Distribution des arguments qui justifient l'âge chez les enfants de 3 à 5 ans

Les arguments qui justifient la notion d'âge (Graphique 1) se distribuent comme suit : chez les 3 ans, 54% des enfants justifient leur âge en se référant aux parents. En revanche, aucun ne se réfère à l'anniversaire ou à un argument de type purement quantitatif. Chez les 4 ans, on remarque que 30% des enfants justifient leur âge sur la base des dires de leurs parents, 37% le font en référence à leur anniversaire et 7% utilisent un argument de type quantitatif. A 5 ans, la référence aux parents représente 13% des justifications, celle à l'anniversaire 18% et l'argument quantitatif 13%.

A quel âge l'enfant est-il en mesure d'indiquer l'âge qu'il avait avant son anniversaire et l'âge qu'il aura après ? Le Graphique 2 montre que 16% des 3 ans, 55% des 4 ans et 78% des 5 ans sont en mesure d'indiquer l'âge qu'ils avaient avant leur anniversaire et l'âge qu'ils auront à l'anniversaire suivant. Chez les 3 ans, on observe que 8% des enfants peuvent indiquer uniquement l'âge qu'ils avaient avant et 16% uniquement l'âge qu'ils auront lors de leur prochain anniversaire ; 58% ne savent pas répondre. Chez les 4 ans, on constate que 11% donnent une réponse correcte seulement pour l'âge qu'ils avaient avant, 18% seulement pour l'âge qu'ils auront à l'anniversaire suivant et 11% commettent des erreurs ; 4% ne savent pas répondre. Chez les 5 ans, 3% ne peuvent qu'indiquer l'âge qu'ils avaient avant leur anniversaire, 19% l'âge qu'ils auront après.

Discussion

Nous faisions l'hypothèse que l'évolution des arguments qui justifient l'âge des enfants entre 3 et 5 ans devrait être la suivante : d'abord référence aux parents, puis à la notion d'anniversaire, avant d'être de nature quantitative. Nos résultats montrent qu'entre 3 et 5 ans, la référence aux parents baisse (54% à 3 ans, 30% à 4 ans et 13% à 5 ans). Il faut attendre l'âge de 4 ans, pour que les enfants commencent à justifier leur âge en se référant à leur anniversaire (26% à 4 ans et 34% à 5 ans). Durant cette même période, un nouvel argument apparaît, de nature quantitative : « J'ai 4 ans parce qu'avant j'avais 3 ans et avant j'avais 2 ans », ou « J'ai 4 ans parce que j'ai eu mon anniversaire au mois d'octobre ». C'est entre 4 et 5 ans qu'apparaît l'argument purement quantitatif (7% à 4 ans et 13% à 5 ans).

Si certes, ces trois types d'arguments (parents, anniversaire, quantitatif) nous permettent de rendre compte des réponses de 50% des 3 ans, de 70% des 4 ans et 52% des 5 ans, l'examen des autres arguments fait apparaître une autre catégorie. La seconde hypothèse portait sur l'incidence de l'âge sur l'évolution de la profondeur de la perspective temporelle, c'est-à-dire la capacité à indiquer l'âge qu'il avait avant son anniversaire et celui qu'il aura à l'anniversaire suivant. Nos résultats montrent que seuls 16% des enfants de 3 ans peuvent indiquer à la fois l'âge qu'ils avaient avant et après leur anniversaire. Nos résultats sont conformes à ceux de [START_REF] Decroly | Études de psychogénèse[END_REF] et à ceux de Ziadé, Cronier & Zazzo (1981).

En revanche, on observe que 32% des 3 ans et 73% des 4 ans sont en mesure d'indiquer l'âge qu'ils auront l'année prochaine. Cette compétence est plus précoce que ne le laissaient penser les travaux d' [START_REF] Ames | The development of sense of time in the young child[END_REF] pour qui il fallait attendre 4-5 ans. Nous observons le même phénomène pour la compétence qui consiste à donner l'âge qui précède son anniversaire ainsi que l'âge que l'on aura au prochain anniversaire. Alors que pour Decroly, seuls les enfants de 5-6 ans répondent correctement à cette question, nos résultats montrent qu'entre 4 et 5 ans la majorité des enfants dispose de cette capacité (55% à 4 ans 78% à 5 ans). Ce résultat peut s'expliquer par le travail spécifique conduit par les enseignants sur la notion de temps-convention dans la classe. En effet, chaque matin, les enfants sont invités à manipuler les jours de la semaine, le quantième, le mois et l'année. L'anniversaire est fêté en classe et constitue un repère dans la frise du temps. De surcroît, ce travail s'effectue dans des groupes hétérogènes de 3 ans, 4 ans et 5 ans.

Conclusion

Cette première approche montre que dès l'âge de 3 ans, l'enfant dispose des compétences relatives à la notion d'âge. Ce travail mérite d'être développé en s'intéressant d'une part aux rapports que cette notion entretient avec l'organisation des jours, mois et années, et d'autre part aux questions relatives à l'âge, du type « Depuis combien de temps es-tu né ? » ou « Quel âge avais-tu à ta naissance ? ».

  des réponses correctes aux questions « Quel âge avais-tu avant ton anniversaire ? » et « Quel âge auras-tu après ton anniversaire ? » chez les enfants de 3 à 5 ans, en %

  références, en plus nos explications, elles permettent de rendre compte de 75% des réponses des 3 ans (Parents : 54%, parce que 15% et double référence parents quantitatifs 6%), de 89% des réponses des 4 ans (Parents : 30%, Anniversaire 37%, quantitatif 7% et double référence parents quantitatifs 7,5% et anniversaire parents (7,5%), et de 79% des réponses des 5 ans (Parents : 13%, Anniversaire 18%, quantitatif 13% et double référence du type : anniversaire parents (3%), parents quantitatifs 6% et anniversaire quantitatif (26%).

	de type doubles
	90%
	80%						78%
	70%
	60%						55%	58%
	50%						3 ans
							4 ans
	40%
	30%
	20%			16%	18%	19%	16%
	10%	8%	11%	3%			4%	11%
	0%
			avant		Après	avant après	NSP	Erreur
							En effet, on observe parmi les enfants de 3ans, 4ans et
	5ans ans un nouveau type d'argument : les doubles références du type anniversaire-parents,
	anniversaire-grandir ou parents-argument quantitatif. Alors que la majorité des arguments sont
	simples (parents 54%, parce que 15%) chez les 3 ans, 6 % recourent à une double référence (Parents
	quantitatif). A 4 ans, 15 % se justifient leur âge par une double référence du type parents quantitatif

(7,5%)

ou anniversaire parents (7,5%). Chez les 5 ans, les doubles références sont massives. 35 % des arguments sont de ce type. Ils se distribuent comme suit 3% sont de type anniversaire parents 6% parents-quantitatif et 26% anniversaire-quantitatif. Ces doubles références sont intéressantes car ils peuvent traduire un mécanisme de passage entre un premier niveau de décentration : le recours à l'anniversaire, et une objectivation : la référence quantitative. Si l'on prend en compte ces arguments

Maître de conférence, IUFM de l'Académie de Rouen et Université de Paris 8.


domain: scco info

text:
O Masson

J Baratgin

F Jamet

F Ruggieri

D Filatova

Use a robot to serve experimental psychology: some examples of methods with children and adults

Keywords: Human-system interactions, reactive systems, humanoid robots, embodied robots, HRI, NAO, social norms, pragmatics, relevance theory, politeness rules, cognitive bias, decision making, class inclusion, endowment effect I

Robots are increasingly used in scientific research. Given the multitude of existing robots, how to choose the most adapted robot to a research and above all, how to use it to study biases in reasoning or in decision making? We suggested studying well-known biases from a new point of view: social norms, including social behaviors, social context and pragmatics of language. How to measure the impact of implicit social factors on the term of an experimental interaction when the experimenter cannot control non-verbal social cues he emits? A robot, whose behavior can entirely be programmed, constitutes a useful tool for this level. Authors' purpose is to expose a new method, accessible to all and neophytes in computers, which can be applied to a humanoid reactive robot for scientific research. Harel's "statechart" bring a formalism allowing deriving from it a program in which the states of the artificial system can be modeled in terms of states-actions. The technics and advantages brought by this proposed method will be reviewed through the illustration of two studies: the first one focusing on inclusion processes in younger children, the second one on the endowment effect within a sample of adults.

INTRODUCTION

When the role of robots becomes more important within humans' environments, current research is only beginning to be extended to the study of its impact on the character of social relationships. Do errors of judgment associated with some human interaction contexts persist when individuals interact with a humanoid robot? This paper provides a building block to identify non-verbal cues, programmable in a robot, that are able to activate social norms in a human-robot interaction.

A. Robots as sociable entities

Literature reports of studies showing that human-robot relationships can become social when adequate criteria are met, particularly with humanoid robots. There is also a strong tendency to anthropomorphize robots, which is to say, lending to robots human thoughts and emotions [START_REF] Kiesler | Anthropomorphic interactions with a robot and robot-like agent[END_REF]. This is paradoxical in studies, as participants know that they interact with a robot. This anthropomorphism would respond to a primary need to recover a satisfactory state of familiarity in the situation of interaction and is independent of technological knowledge [START_REF] Baddoura | Social vs. useful HRI: experiencing the familiar, perceiving the robot as a sociable partner and responding to its actions[END_REF].

Between humans, the action to influence another person is crucial for just about any type of social relationship [START_REF] Byom | Theory of mind: mechanisms, methods, and new directions[END_REF]. The literature on robotics has identified a number of factors that could make a robot appearing more sociable and influences the behavior of the user:

Appearance and behavior: level of presence -physical or non-physical [START_REF] Baratgin | Effet de dotation et normes sociales : une approche interculturelle[END_REF]; the gender of the robot -male or female [START_REF] Kahneman | Anomalies: the endowment effect, loss aversion, and Status Quo Bias[END_REF], [START_REF] Cassell | Embodiment in conversational interfaces: Rea[END_REF].

Modalities of interaction: the robot must be able to interpret and reproduce the non-verbal cues of his interlocutor (body language, eye contact); the interaction between robot and user must extend the senses to sight and touch [START_REF] Takayama | Influences on proxemic behaviors in human-robot interaction[END_REF], [START_REF] Wilcock | Speech, gaze and gesturing: multimodal conversational interaction with Nao robot[END_REF].

Autonomy and interactivity: the robot knows how to take decisions in a given situation, without the needing a human intermediary [START_REF] Yasser | Toward combining autonomy and interactivity for social robots[END_REF].

These factors influence many behavioral dimensions in human contact, including: Fun [START_REF] Bateson | Steps to an ecology of mind[END_REF], [START_REF] Bartneck | A design centred framework for social human-robot interaction[END_REF],

Cooperation in action [START_REF] Siegel | Persuasive robotics: the influence of robot gender on human behavior[END_REF],

Trust and respect shown to the agent [START_REF] Breazeal | Humanoid robots as cooperative partners for people[END_REF],

The general perception of the presence of an artificial agent or robot's [START_REF] Bartneck | A design centred framework for social human-robot interaction[END_REF].

B. Benefits to use a robot to test social factors in interaction

Humans' capacity to behave socially with other social individuals makes them able to treat artificial intelligent agents as social entities [START_REF] Reeves | The media equation: how people treat computers, television, and new media like real people and places[END_REF]. As social norms can be defined by interactions between people, they can be defined by the interactions between humans and robots [START_REF] Byom | Theory of mind: mechanisms, methods, and new directions[END_REF]. By analyzing the factors enabling social norms among humans, we can recreate those factors or controlling them by applying them to a robot.

Another benefit in using a robot is that it could endorse different social roles regarding its programmed behavior, impacting the social context of interaction. Thus, by using a robot we can further analyze the impact of each behavioral factor, alone or in combination, on a socialized relationship between human and robot. This last feature offers new possibilities in the study of biases observed in social relations, including the "endowment effect", as a widespread Some recent studies use this offer to analyze human cognition in interaction with robots by manipulating a whole set of factors, showing that to study human cognition with robot is not such an abstract idea. These show that humans have a tendency to implicitly consider computers as social actors when individuals are invited to through subtle clues [START_REF] Nass | Machines and mindlessness: social responses to computers[END_REF]. This tendency was named "media equation" [START_REF] Reeves | The media equation: how people treat computers, television, and new media like real people and places[END_REF] and has been analyzed by applying some categories and social behaviors as for example gender and cooperative feeling with computers [START_REF] Nass | Machines and mindlessness: social responses to computers[END_REF].

More recently, this phenomenon was applied to HRIs [START_REF] Syrdal | Exploring human mental models of robots through explicitation interviews[END_REF]. For example, the manner by humans respond physically to robots is exactly the same than in front of another human. Specifically, proxemic distance that takes place between humans and robots is identical than in interactions between humans interactions [START_REF] Reeves | The media equation: how people treat computers, television, and new media like real people and places[END_REF]. Moreover, research on proxemical distance in human-robots interactions show that this factor can impact interactions as it would do within between humans' interactions [START_REF] Byom | Theory of mind: mechanisms, methods, and new directions[END_REF].

Bateson suggests [START_REF] Bateson | Steps to an ecology of mind[END_REF], according to his "double-bind" theory, that inconsistency in human communication can produce mental illness. Findings of Nomura showing that inconsistency between postures and verbal statements emitted by robots can impacts reasoning and memorizing, particularly in a specific combination: impolite posture and polite statements. Results of Nomura's study and others imply the possibility of an interaction between different several factors in HRIs [START_REF] Nomura | Influences of inconsistency between phrases and postures of robots: A psychological experiment in Japan[END_REF].

Studies mentioned above focus on comparisons between human-robot interactions and human-human interactions, in terms of impact on quality of interactions and social perceptions. These works often use new methods to do it. Another branch of research is interesting by reuse some existent methods to show differences of cognitive performances during an experimental task. Thus, non-verbal behaviors as gestures and body postures, and the context of interaction, are important factors in human communication.

C. Well-know paradigms reviewed with robots to study social norms -towards a new paradigm with robot as experimenter

In psychological experiments on reasoning, probability judgment and decision-making, numerous evidences underlined the importance to the pragmatics and to contextual implicitations in the participants' inference and behavior induced by human experimenters (see for example [START_REF] Kiesler | Anthropomorphic interactions with a robot and robot-like agent[END_REF], [START_REF] Baratgin | The psychology of dynamic probability judgment: order effect, normative theories, and experimental methodology[END_REF], [START_REF] Politzer | Reasoning, Judgement and Pragmatics[END_REF][START_REF] Politzer | The class inclusion question: a case study in applying pragmatics to the experimental study of cognition[END_REF][START_REF] Politzer | Reasoning, Judgement and Pragmatics[END_REF][START_REF] Politzer | Are conjunction rule violations the result of conversational rule violations?[END_REF], [START_REF] Schwarz | Cognition and Communication[END_REF], [START_REF] Sperber | Relevance: Communication and Cognition[END_REF], [START_REF] Sperber | Relevance theory explains the selection task[END_REF]). Especially, these pragmatical and contextual factors can explain a different interpretation or representation of the task for participants where outcomes would be the result of compliance with social norms 1 .

In order to place individuals in a totally neutral and disambiguated environment, the use of a humanoid robot in place of the experimenter constitutes a very good tool. This methodology allows feedback to finely control contextual and cues which can cause pragmatical effects. Retrospectively, several applications in human-robot interactions are expected.

Going further in this prospect, some authors started to study some biases analyzed since a long time from a totally new point of view: pragmatics of language and social context [START_REF] Baratgin | Effet de dotation et normes sociales : une approche interculturelle[END_REF].

In this paper will be presented two particular examples where a robot was used as experimenter within old paradigms to make experiments in cognitive psychology. This new way to use these paradigms could bring some important elements to psychology and retrospectively to robotics, to know how a robot can be programed to behave properly in specific situations. Our team studied two elements which are very important for psychologists: class inclusion and the endowment effect.

We based on these two elements to build a methodology in order to test impacts of pragmatics on results previously founded in literature, applicable to all psychological processes studied implying politeness rules and pragmatics. Thus, pragmatics in the standard inclusion task with children will set an implicit situation which suggests to the child that the experimenter expects some good results from him (theory of relevance [START_REF] Sperber | Relevance theory explains the selection task[END_REF]). This task is one that allows to test the impacts of pragmatics on a very simple task with young children.

In the paradigm of exchange with adults to measure endowment effect, pragmatics plays a role in the attribution towards the experimenter that he is expecting a polite answer form the participant [START_REF] Masson | NAO robot and the endowment effect[END_REF]. This choice was oriented towards politeness rules and pragmatics of language in the fact they take place in a lot of everyday life situations and have a lot of applications in psychology, in robotics and in economy [START_REF] Elster | Social Norms and Economic Theory[END_REF], [START_REF] Kahneman | Anomalies: the endowment effect, loss aversion, and Status Quo Bias[END_REF]. We could so generalize it to other experimental situations where politeness rules and pragmatics of language could lead to some error in reasoning or decision making. Then these new results will be interesting for robotics to create more sociable robot behaving as to reproduce natural human behaviors and reasoning as humans would do.

1) Class inclusion with children

Thus, we analyzed the capacity of class inclusion with younger children, previously tested accordingly to Piaget's theories on stages of development, regarding social context and pragmatics of language [START_REF] Takayama | Influences on proxemic behaviors in human-robot interaction[END_REF], [START_REF] Piaget | Essai sur quelques aspects du developpement de la notion de partie chez l'enfant[END_REF]. Endowment effect has also been studied according the paradigm of exchange [START_REF] Knetsch | The endowment effect and evidence of nonreversible indifference curves[END_REF] with adults by manipulating social context and norms. The originality of these works is to study well known biases along years with new technics, using recent technologies. Piaget's theories suggest that when children do not have met a development stage called "concrete operations", including the operation of classification, children cannot be inclusive. The experimental initially used to test capacities of class inclusions with children consists to ask them to compare a super category with a subcategory. For example it is asked to the child if among objects presented in front of him (tulips among another kind of flowers): "Are there more of tulips or are there more of flowers?" [START_REF] Piaget | Essai sur quelques aspects du developpement de la notion de partie chez l'enfant[END_REF].

If children are inclusive, so as for Piaget, once the adapted development stage is passed, they will answer by telling there are more flowers than tulips, in contrast with children who are not inclusive and could only compare categories on an horizontal level, for example "tulips" and "roses".

2) The endowment effect with adults

The endowment effect is another process, constituting a "bias" in decision making that we are investigated by using methods presented here. The endowment effect [START_REF] Thaler | Toward a positive theory of consumer Choice[END_REF] consists to attribute a larger greater value to an object when we own it, than when we do not own it. This "bias" is very often measured according the paradigm of exchange [START_REF] Knetsch | The endowment effect and evidence of nonreversible indifference curves[END_REF], grouping three experimental steps: experimenter gives an object A to the participant.

Then the participant makes a masking task, usually consisting in a treatment task during about fifteen minutes.

The experimenter comes back in the session room and asks the participant whether he would change or note the first given object A against an object B about an equally economic value. This experiment is led into a second independent group where objects A and B are permuted. According to this method, the level of the endowment effect produced is measured along the refusals' rates in front of the proposition to exchange the given object against the second one.

In a very large literature on this subject, factors emerging to produce this effect are the "loss aversion" [START_REF] Kahneman | Anomalies: the endowment effect, loss aversion, and Status Quo Bias[END_REF] and the phenomenon of "ownership" [START_REF] Reb | Possession, feelings of ownership and the endowment effect[END_REF].

Through these two kinds of processes, we will then show how to program a robot to lead associated experiments. This present work makes a good illustration to show that another benefit to use a robot is it can be applicable to a large panel, going from children to adults.

II. A NEW PARADIGM FOR NEW HYPOTHESES

In these different studies one question remains that is to make results affordable if we want to finely test the impacts of social behaviors on effects measured. A social interaction is not only based on verbal contents exchanged between interlocutors, but stands on social non-verbal clues emitted which are out of control of protagonists.

How to evaluate the impact of implicit factors on the measured effect when the experimenter cannot control all of the clues he emits in front of the participant?

It is here that a humanoid robot can be a very useful tool since it is possible to entirely program its behavior, so as to annihilate all social cues or to artificially recreate it in the robot. It is possible to preprogram a robot to make him behaving autonomously during a whole experimental session but they are many technical constraints, as for example: Speech recognition module cannot perfectly understand all kinds of voice in all configurations.

Then, the program has to process some statements in a limited set of forecasted words in the experimental situation.

The visual recognition does not work perfectly.

These different constraints make it difficult to reach the end of the experiment with a perfect behavior.

Studies using robots, as well as some studies presented in introduction, often use a technic called the "wizard of Oz" methods. This term, usually met in literature means that when participant faces a robot, this one is tele operated from another room, unbeknownst to them. A major advantage of this technic is that experimenters can leave the participant alone with the robot and make it appear totally autonomous.

A lot of technical constraint still existing, this method has the advantage of allowing a whole experiment lonely with a robot, without the presence of any human in the experimental session's place, while avoiding lost results where a totally preprogrammed autonomous behavior could stop or malfunction during experiments.

Whereas this technic is now well known in research, it has the disadvantage to break one of basic offer that was initially brought by robots, that is to say a perfect standardization of actions led by the experimenter. In wizard of Oz methods, the robot which leads experiments is always directly tele operated by a human, so rhythms of gestures are never exactly the same.

In this present work, a hybrid method is used to simultaneously preserve standardization all by avoiding all malfunctioning. We will go through two concrete examples brought by the measure of endowment and show that these methods allow to test new hypotheses to test inclusion among children and the endowment effect among adults.

First, we assume that inclusion errors made by children in the inclusion task of Piaget's study not only depend on the factor of age but largely on social context: the inclusion task is usually led by a teacher which is implicitly perceived by the child as a social entity in front whom he has to give the good answer [START_REF] Baratgin | Stupid NAO and Piaget's class inclusion question: a new argument for the relevancetheoretic explanation[END_REF].

Then we assume that the level of the endowment effect measured according the experimental situation of the paradigm of exchange by Knetsch is more due to social factors: politeness rules engaged in the human participant-experimenter interactions prohibit to change a given object -considered as a present in our culture -against another or to refuse this gift [START_REF] Masson | NAO robot and the endowment effect[END_REF].

To test these new hypotheses regarding well known processes in literature, we use a robot NAO (Aldebaran) to design an hybrid experimental technic that takes a place between wizard of Oz method and a fully previously programmed behavior.

III. METHODOLOGY

A. Materials

Both experimental sessions are led by a humanoid robot NAO (Aldebaran version 4 -"Evolution"). The behavior of the robot is programmed with the software Choregraphe in version 2 built by Aldebaran, and stored on a laptop connected to the robot via Wi-Fi from another room.

The advantage of NAO is that it can reproduce all needed experimental gestures that would be expressed by a human experimenter. Thus the NAO robot possesses 25 degrees of freedom, allowing him to move its limbs as a human. Then, this robot's appearance is not too closed than humans' and we can assume that no other uncontrolled factors as anthropomorphism or uncanny valley effect affect results [START_REF] Macdorman | The uncanny advantage of using androids in cognitive and social science research[END_REF].

The robot also owns two hands making it able to hold little and soft objects (see Fig. 1).

We can list the embedded useful modules needed as following:

A vocal synthesis: allow the robot to make verbal statements to the participant and to explain him the experimental procedure. This module is useful for example when it is wanted to keep neutral vocal intonations.

The possibility to store audio files in the robot makes it possible to pre-record vocal statements by making them identical form humans' voice.

The robot is sensitive to noise and owns sensors: these capacities allow the robot to be autonomously responsive to the behavior of the participant A camera is embedded in the head of the robot: as this camera can be used for objects' or faces' recognition, it is used here to see the behavior of the participant by distance, as facial expressions for example. In the paradigm of exchange, two conditions. In "neutral robot" condition, the robot was presented as a simple tool to collect data, and all non-verbal indices were controlled to be annihilated. In the "sociable experimenter robot" condition, all these non-verbal indices were reintroduced: gazes, participants face tracking, vocal intonations.

IV. DESIGN OF A NEW PROCEDURE, STARTING FROM

"PAPER" TO EXPERIMENTAL SESSIONS Works presented here focus on the methods used to permit a whole experiment with a solely robot in the room interacting participant, without breaking a perfectly standardization in actions conducted. One thing important here is that the same approach can be used, both with very different topics : inclusion and endowment effect, and on another side both with very different samples: adults and children.

A. Harel's statecharts

Statecharts (SC) of Harel, included in UML approach, bring a formalism to represent all different steps state-action during a procedure. This model meets some advantages listed below: SC are adapted to all reactive system: it takes in account actions of the participant regarding the system, that may change its status.

SC can be decomposed in several sub-statecharts: that allows focusing on several levels in the model of the system.

SC can show all configurations in a system at different several times. So SC take in account all dynamic operations of the system. SC are easily readable, including neophytes for new technologies.

Here, these points are interesting because SC allow us to take in account the technical constraint of a robot and to prevent possible hazards which can occur in experimental sessions.

Mostly, a high difficulty for an autonomous robot is to capture all reactions of a human participant. For example, speech recognition or visual recognition are as much as hazards which could impact on the quality of experimental sessions: when it is crucial to wait for a precise response from the participant, it may be a risky way to use directly the vocal recognition module to catch the expected signal to continue, when the following of experiment is important for the study.

In the case of inclusion, robot often catches children enunciated words with difficulty.

So, what we propose is to articulate the statechart model around these constraints, that is to say participant's actions which can encounter some technical limits of the robot. SC take account of the expected action of the participant, which is to give his answer regarding the proposal enunciated by the robot to trade the first given object against the second one (see Fig. 2).

B. From statecharts to the programmed behavior

The software Choregraphe is very well adapted to derive statecharts in programmed behaviors, in the way it takes account about the same elements: actions of the participants, status and actions of the NAO robot. Choregraphe is also useful because it allows experimenters to launch different parts of the program in an independent way.

So, first we have several statecharts corresponding to all parts of the robot's behavior. Then these part-statecharts are derived in Choregraphe in subgroups of behaviors (see Fig. 3). Statecharts take in account of different sates of a system regarding stimuli of the environment. It is possible to derive it in Choregraphe thanks to entries corresponding in responses received by the robot's sensors, then to launch useful following simple actions. This kind of development is called event programming This point is crucial in our methods because these different subparts can be launch separately. This presents real advantages:

Each part or sub-behavior can be launched at any time: for example, when robot is giving instructions to the participant, when this one does not understand them, he can express it in a whole set of very different ways. Then, if the "giving instructions" step is grouped in an isolate sub-behavior, the experimenter can launch again this block of actions as many times as it is necessary to make the participant understand the rules.

At any time, the experimenter can choose the part that will be launched, even in a same step. This advantage offers three other points :

Even if the step consists in giving rules of the experiment to the participant, it is possible to make some variations in the statements enunciated, maybe when the participant would understand the same rules but in a different presentation.

When the robot is waiting for an answer of the participant, this one can emit different words. In that case, we have to pre-record different sub-behaviors, accordingly to each step, to ensure that the NAO's behavior will well adapt to each participant.

Initially, in all experimentation in this kind of procedure, these are the actions of each participant that gives the rhythm of experimental session, not directly by the experimenter himself. Thus, acting in this manner will allow the robot to behave accordingly to the rhythm of the participant in each step.

These advantages draw a new paradigm in the use of robots in experimental tasks by allowing:

To keep a perfect standardization in actions during each step: even when the experimenter can choose the subgroup of behavior which will be launched at specific times, actions include in this block are preprogrammed, so the experimenter keeps an entire control of actions which will be engaged by the robot. It is interesting for us here, because all social cues emitted by the robot experimenter will be will all be controlled.

If the main program is well built, it can just let to experimenter all the appreciation of the experimental situation to know what to execute to continue on in the best way to lead the session at its term. So, to summarize here, were are not completely in a magician of Oz technic, nor in the use of an entirely preprogrammed main behavior in a purpose to make the robot autonomous and to let it all conduct by itself.

V. EXPERIMENTAL TRIALS

A. Physical configuration NAO:

In both experiments -inclusion and endowment effect -the robot NAO is sitting in front the participant, so as to keep is gaze at the same level than participant's one (see Fig. 4 for inclusion and Fig. 5 for endowment effect). In these two experiments, each participant was left in the room with the robot, presented as acting autonomously. In each configuration, NAO can move its arms to make all useful gestures during the experiments. In the experiment on the endowment effect, NAO holds the first object in its right arm and the other one is hidden beside its leg so as when the participant faces it, he cannot see this second object. In the inclusion experiment, NAO is sitting in front of the child, and between them fruits are disposed on a table in an apparently randomized way.

Human experimenters:

In both experiments, one experimenter is placed in a separate room to tele operate NAO. This experimenter can follow in live all situations with the embedded robot cameras which face the participant. In the task of inclusion, two human experimenters were needed, one of them to introduce the robot to the child, the other to prepare and launch the program.

B. Conditions

In the task of inclusion, the experimenter accompanying the child in the room containing the robot shows the robot as to be very stupid. Thus, the child is placed in the role of a teacher for the robot. Once the session is launched, the robot tell the child that he will teach him a lot of things, and starts by asking what are the different objects disposed on the table. Once the child has named all kinds of fruits, the experiment can continue on with the classic situation of the inclusion's task.

For the endowment effect, it is a little different in terms of procedure. There are two interesting conditions with opposite behaviors held by the robot: "neutral experimenter" robot and "sociable experimenter" robot.

In the "neutral" robot condition, NAO is programmed to behave in a way to annihilate all non-verbal social cues: it does not track the face of the participant; it does not more gestures that it is necessary and vocal intonations are almost nonexistent and are only there to make the artificial discourse understandable with some punctuation. In this condition, only the speech synthesis of the robot is used to make statements. Also, the robot is shown as a simple mechanic tool to help human experimenters to collect data. In the "sociable" robot condition, social non-verbal cues identified in the literature are artificially implemented in the robot. Cues are listed below: NAO tracks the face of the participant NAO blinks rancorously during all the interaction NAO's speech is filled with vocal intonations from pre-recorded MP3 files, made by a human with all natural intonation, but arranged to keep nearly the same voice than in "neutral" condition.

In that second condition, social context is also manipulated for NAO is shown as a real collaborator which works directly in collaboration with human experimenters, as a social being.

VI. FIRST RESULTS AND DISCUSSION

According to previous studies on inclusion and endowment, the measured dependent variables are the same that in literature using this procedure with human experimenters for both studies: the Piaget's task of inclusion and the endowment effect. To reproduce these procedures by using a robot allowed us to manipulate two further classes of factors: Social context: as the robot appearance is near human's one but not the same -so the participant keeps in mind that he faces a robot -this makes it possible to introduce him as for example a stupid being, in the task of inclusion, or as a simple mechanic tool to collect results in the neutral condition in the paradigm of exchange.

The social behavior of the robot: this variable was manipulated for the endowment effect experiments in which there are two behavioral conditions. In the "neutral" robot condition, NAO was programmed so as to behave neutrally, annihilating all social non-verbal cues. In "sociable" robot condition, social non-verbal cues have been artificially implemented to the robot. These offers brought by the use of a humanoid robot allowed us to test a new kind of factors producing the endowment effect with adults or impacting results in the task of inclusion: social norms activated automatically in all interaction with some entity assuming a specific social role -or not.

In the task of class inclusion with 20 children, the first results by pilot sessions using new technics reported here tend to show that more younger children (close to 50%) were inclusive than in the Piaget's standard condition. These findings are interesting, showing that in some case social roe endorsed by human teachers can impact learning with children. In experiments focusing the endowment effect, the both conditions, "neutral experimenter robot" and "sociable experimenter robot", show that the two factors listed above, the social context exposed and the robot's behavior, can nuance the level of the endowment effect produced. The fact that we always use the same robot, only its behavior and social context can explain differences found in results.

There are notable differences between the two conditions regarding rates of refusals to the exchange proposition. These results tend to show that different artificial behaviors could annihilate or could enhance an endowment effect. In the sociable condition, refusal rates are significantly higher than acceptances', so an endowment effect is measured. In that last condition, social non-verbal cues are emitted by NAO. Thus, it shows that these cues reactivate social norms, which are expressed here by the respect of politeness rules in destination of the robot. Thus in this case we find a repartition close to those found in literature [START_REF] Cassell | Embodiment in conversational interfaces: Rea[END_REF]. These results are beforehand useful for psychology for they finely show how social factors can impact on measured data. These results will also be useful in robotics in the fact they bring interesting new data on behaviors to implement to a robot to annihilate or minimize some cognitive biases. Especially, vocal intonations are a main factor to nuance social norms activation for the situation of paradigm of exchange [START_REF] Knetsch | The endowment effect and evidence of nonreversible indifference curves[END_REF].

VII. CONCLUSION

These two illustrations using a robot to test the inclusion with younger children and the endowment effect with adults allowed explaining well-documented processes in literature regarding a new class of factors: social context and pragmatics of language. Findings emerging from the new methods presented here are very interesting in psychology, but have the double advantage to make this useful in all fields linked to reasoning and progress in robotics. Technics presented here, that is to say a new approach situated between the wizard of Oz method and an entire programmed autonomous main behavior; make it possible to finely measure the impact of sub-behaviors, which can be used separately on in combination, on whole sets of processes where social norms could play a role. Moreover, technics used are accessible and do not require to be an expert in computer sciences. Statecharts' formalism of Harel, combined with software as Choregraphe permits to control each experimental situation by a high degree of control in the standardization of the procedure.

Further to the study of human factors which can bring to reasoning biases in everyday life within human interactions, these new technics allow us to isolate non-controlled human behaviors, finely identifying those which can improve learning or by contrast annihilate social cues which may induce biases in reasoning or in making of decisions processes.

Figure 1 .

 1 Figure 1. Picture of one NAO's handB. Procedure with a "semi-wizard of Oz" methodSo we reproduced the two main experimental situations as described in introduction by replacing experimenter by NAO. In each situation, robot can launch from another room unbeknownst to the participant:

Figure 2 .

 2 Figure 2. Simplified example of statechart used in the paradigm of exchange, at the step of proposal of exchange

Figure 3 .

 3 Figure 3. Capture of Choregraphe software (Aldebaran) based on a statechart (see also Fig. 2)

Figure 5 .Figure 6 .

 56 Figure 5. Picture of an experimental session in inclusion task

The question of the implication of social norms for economical decisions is studied since a long time in philosophy and in economics (see for example[START_REF] Elster | Social Norms and Economic Theory[END_REF])

ACKNOWLEDGMENT

Financial support for this work was provided, by a grant from the ANR Chorus 2011 (project BTAFDOC), and by a grant of Institut des Sciences Complexes (2014-ISC-PIF petits et moyens équipements).

This work was performed within the Labex SMART supported by French state funds managed by the ANR within the Investissements d'Avenir programme under reference ANR-11-IDEX-0004-02.


Nicolas Kusz
email: nicolas.kusz@gmail.com

Jean-François Lemoine
email: jean-francois.lemoine@univ-paris1.fr

Voice app (Google Actions and Alexa Skills) : the influence of the assistant's voice on users

Keywords: voice assistant, trust, social presence Digital Marketing & Social Media

Introduction

Made famous by the voice-activated connected speakers Google Home (Google Assistant) and Amazon Echo (Alexa) released respectively in France in 2017 and 2018, the virtual voiceactivated assistant is defined as an intelligent system connected to the Internet, capable of understanding a question formulated orally by a human, then to perform certain actions or to give a response by synthetic voice [START_REF] Lahoual | De l'utilisabilité à l'appropriabilité des assistants vocaux. Étudier les interactions vocales en situation domestique à partir d'une démarche centrée utilisateurs[END_REF]. Assistants now offer many functionalities: information search, conversations with brands, online shopping, office or administrative tasks, entertainment or even home automation [START_REF] Ammari | Music, Search, and IoT: How People (Really) Use Voice Assistants[END_REF][START_REF] Gouliaéva | La révolution des assistants vocaux : comprendre les enjeux et réussir ses stratégies marketing[END_REF]. For their part, companies have the possibility of connecting a voice version of their website (i.e. a voice application) to virtual voice-activated assistants, to offer a new channel of interaction with their customers [START_REF] Mclean | Alexa, do voice assistants influence consumer brand engagement?-Examining the role of AI powered voice assistants in influencing consumer brand engagement[END_REF]. At the end of 2019, there were 200 million connected speakers worldwide (3 million in France), but there were actually more than 2.5 billion voice assistants (50 million in France) because there are more and more voiceactivated devices, like the smartphones, speakers, smart TVs and many other connected objects, ensuring very quick adoption (Médiamétrie 2018, CSA 2019and Hadopi 2019 studies). Unlike chatbots and virtual agents that complement browsing on a website or mobile application, the characteristics of voice assistants differ from other technologies; they can be used (totally or almost) independently without any other interface and, thus, replace classic web browsing with a screen and a keyboard [START_REF] Natale | To believe in Siri: A critical analysis of AI voice assistants[END_REF]. This technology completely puts into perspective the way individuals consume content on the web, search for information and buy products or services [START_REF] Mclean | Hey Alexa… Examine the variables influencing the use of Artificial Intelligent In-home Voice Assistants[END_REF][START_REF] Ramadan | The Advent of the Voice Moment of Truth: The Case of Amazon's Alexa[END_REF]. The voice, much more than the image, touches the imagination, invites pleasure and confidence. Although the voice, universal and innate, appears to be the most obvious solution for exchanging between man and machine, it also gives opportunities to new challenges associated with web design; with no visual reference or text to guide or spark interest, no buttons or links to click and navigate [START_REF] Devillers | Assistants connectés : des ordres dans la voix », interview dans le cadre l'émission de radio Magnétique[END_REF]. Given the recent arrival of virtual voice-activated assistants to the general public, this technology is still a new field of research and the work is mainly focused on understanding the first uses. The study problem that we have identified can be summarized as follows: does the voice of the assistant generated specific reactions ? The theoretical interest of this research is to highlight the effects of virtual assistant's voice on the reactions of users. From a managerial point of view, this research aims to propose lines of thought for brands wishing to develop their voice assistant.

The conceptual framework of the research

Being interested in the effects of assistant's voice on the user reactions naturally leads us to study the literature on human-machine interfaces and the voice. All of these two areas of research will provide a theoretical framework on the effects of the voice on users.

Voice as Human-Machine Interface

The success of voice assistants is also largely explained by the ease of use of its interface [START_REF] Ammari | Music, Search, and IoT: How People (Really) Use Voice Assistants[END_REF][START_REF] Rzepka | Why Another Customer Channel ? Consumers' Perceived Benefits and Costs of Voice Commerce[END_REF], in this case the voice, as well as the emotion that is able to send back to its user. It easier to interact with systems thanks to IHMs, there was the keyboard and the screen, the mouse, then the touch screens and the touch, and finally the voice.

The virtual voice-activated assistant changes the situation, since here the HMI is "invisible", without visuals, without design, without logo or without button to click [START_REF] Velkovska | The illusion of natural conversation: interacting with smart assistants in home settings[END_REF]. The voice as Man-Machine Dialogue (DHM) considerably influences behaviors, orally the user will express himself 3 times faster [START_REF] Poirier | Quelle modalité pour l'interaction avec les petits appareils mobiles et vestimentaires : texte ou vocal ? Comment choisir entre clavier et assistant personnel ?[END_REF]. One can wonder if communicating with a system in the same way as we communicate with a person, would this not ultimately be the most successful HMI there is? The human voice is a mechanical process composed of very rich characteristics: frequency, intensity, pitch, timbre of the voice and finally prosody. This is obviously the most effective way to communicate between individuals [START_REF] Cornut | La voix[END_REF]. The so-called synthetic voice, on the other hand, corresponds to the production of an artificial voice that imitates the human voice. Synthetic voices were first mechanical (1780), then electronic (1938), and finally computerized. If, before the 2000s, robotic synthetic voices were still quite far from a human voice and not very expressive, now they are modeled on the basis of real human voices, where actors recite many sentences in a loop allowing a machine to produce any sentence based on this voice. Anthropomorphism also humanizes the characteristics of synthetic voices; the sound of the voice obviously (robotic or human), but also onomatopoeia, hesitations, even silences such as moments of reflection or breathing, these are all markers that humanize the assistants [START_REF] Dubiel | A Survey Investigating Usage of Virtual Personal Assistants[END_REF]. Finally, the characteristics of the assistant's voice, such as familiarity or formality, serious or friendly, low or high tone, gender, the ability to be humorous are all characteristics that shape "the identity voice" of a brand through its voice assistant. Not very expressive in the 2000s [START_REF] Stern | The persuasiveness of synthetic speech versus human speech[END_REF][START_REF] Nass | Machines and Mindlessness: Social Responses to Computers[END_REF], now the assistants' voices perfectly imitate that of a real person [START_REF] Shen | Natural TTS synthesis by conditionning wavenet on mel spectogram predictions[END_REF]. According to [START_REF] Natale | To believe in Siri: A critical analysis of AI voice assistants[END_REF], voice synthesis technology and its paralinguistic characteristics (based on real human voices) would no longer allow individuals to discern a synthesized voice from a human voice as mimicry is pushed to its climax. According to [START_REF] Obin | Des voix de synthèse presque humaines[END_REF], from now on "speech is no longer the privilege of humans".

The effects of synthetic voice on users

The effects of machine voice on user behavior are numerous. Mehrabian indicated as early as 1967 that only 7% of language passes through words, and 38% through the voice in reality.

Even if at this stage, to our knowledge, there is no study on the assistant's voice, there are however many studies on the effects of the voice of virtual agents and chatbots on the behavioral intentions and reactions of consumers, on many dependent variables traditionally studied in marketing [START_REF] Lee | Designing social presence of social actors in human computer interaction[END_REF][START_REF] Qiu | Evaluating Anthropomorphic Product Recommendation Agents: A Social Relationship Perspective to Designing Information Systems[END_REF][START_REF] Chérif | Les conseillers virtuels anthropomorphes et les réactions des internautes : une expérimentation portant sur la voix du conseiller[END_REF]. The user tends to interact naturally with the machine as with a human [START_REF] Porcheron | Voice Interfaces in Everyday Life[END_REF]. Among the main effects of the voice, we can cite trust in technology, such as perceived honesty and credibility or the consideration of consumer expectations and motivations [START_REF] Lemoine | Agent virtuel et confiance des internautes vis-à-vis d'un site web[END_REF]. In the field of voice assistants, early work also confirms the impact of the voice on perceived trust in technology [START_REF] Pagani | Adding voice to the omnichannel and how that affects brand trust[END_REF][START_REF] Liao | Comparing the User Preferences Towards Emotional Voice Interaction Applied on Different Devices: An Empirical Study[END_REF]. The literature also states that the theory of social presence (i.e. the ability of a technology or interface to release a form of human warmth and allow the user to have the feeling of being in the presence of another individual) could also apply to voice assistants and motivate users to adopt the technology [START_REF] Sundar | Cheery companions or serious assistants? Role and demeanour congruity as predictors of robot attraction and use intentions among senior citizens[END_REF][START_REF] Chattaraman | Should AI-Based, conversational digital assistants employ social-or task-oriented interaction style? A taskcompetency and reciprocity perspective for older adults[END_REF][START_REF] Mclean | Hey Alexa… Examine the variables influencing the use of Artificial Intelligent In-home Voice Assistants[END_REF][START_REF] Mclean | Alexa, do voice assistants influence consumer brand engagement?-Examining the role of AI powered voice assistants in influencing consumer brand engagement[END_REF]. The literature suggests that individuals interact with a voice assistant instinctively, in the same way as they would with a human and thus develop a special relationship with the device (e.g. users naturally tend to say hello to their assistant or the thank), we can deduce that social presence plays an essential part in user behavior (Kiseleva et al., 2016;[START_REF] Lopatovska | Talk to me: Exploring user interactions with the Amazon Alexa[END_REF]. Finally, the work carried out on virtual agents also sheds light on the effects measured on other variables, such as attachment, realism or amusement.

Methodology

This qualitative study conducted with consumers is based on 15 semi-structured interviews, conducted face-to-face from may to october 2021. In order to benefit from a representative sample of users of this type of technology, we have selected a varied audience in terms of sociodemographic variables, but also proximity to the device (frequent or occasional use, seasoned users or not).

In a second step, we used the method of protocols, in order to circumvent any brakes on the perception of technology. For our study, we invited respondents to manipulate and interact with voice assistants. This allowed us to highlight the emotions felt by the individuals interviewed and to observe their behavior in real situations of use. We asked the interviewees to discuss with five branded voice assistants, selected from a benchmark of around fifty assistants offered by certain brands.

Results and discussion

Our analysis reveals that the voice type of assistants has a significant impact on user reactions and emotions.

Perception of the voice HMI

The ease of use provided by the voice HMI stands out as one of the main success factors of voice assistants and thus confirms the literature [START_REF] Kowalczuk | Consumer acceptance of smart speakers: a mixed methods approach: An International Journal[END_REF], "there is still a story of ease. I can ask my son to ask for the weather." The HMI is a unanimous success with respondents, "I like my voice assistants because I don't need to type, you see... I just say OK Google and it answers me", or "There, without instructions , it's still very simple to use". The device also reduces the cognitive load of searching for information on a search engine and the web, "I'm going to go to Google or Yahoo and I'm going to have to look for information myself on lots of websites, whereas with a voice assistant I don't need to ask myself which website to get the information from, the assistant will do it automatically". Conversely, some consumers are afraid of falling into a certain form of harmful ease provided by this HMI, "even if it provides ease of answering questions, if it is fast, it is also a bit soothing, I would say . Soothing because it takes away the need or the will to get up and get the information yourself", some users add "I don't want my son to get used to this automaticity. […] to give him the impression that everything is easy and that the information can be found like that, with the snap of his fingers". Finally, despite obvious ease of use, respondents mentioned the blank page syndrome, "using a voice assistant is when you know what you can do with it […] and in fact, as you don't know, you don't don't use it", a disadvantage noted by many respondents "when you buy something you don't even have a user manual, so you don't really know how to really use them 100%. What are good keywords? ".

Voice and its effects on the consumer

The voice emerges as one of the determining variables that motivate the use of a voice assistant, one respondent indicates "finally the voice of the assistants was not something that I paid too much attention to until now, but with the tests I realize unconsciously that the voice matters a lot". Referring to synthetic voices, one respondent said "I really don't feel like it's a machine, it's almost scary. The tone is also very impressive, the non-verbal language, and it is extremely natural".

For our study, we selected branded voice applications (backed by Google or Alexa systems) with a wide variety of voice characteristics, among which we can cite: gender, speaking speed, tone, pitch, timbre, prosody and type of voice (human or robotic).

After interacting with branded voice apps, our study found that assistants with a more robotic synthetic voice were more successful, "OuiSCNF's voice I found more human, but not 100% either. I found it more pleasant", or even speaking of another robotic synthetic voice "the voice I didn't give myself any particular thought […] there was a little robotic side to it but that didn't bother me ". Contrary to the work carried out on chatbots and virtual agents [START_REF] Lee | Designing social presence of social actors in human computer interaction[END_REF][START_REF] Wang | Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs[END_REF][START_REF] Chérif | Les conseillers virtuels anthropomorphes et les réactions des internautes : une expérimentation portant sur la voix du conseiller[END_REF], a human voice that nevertheless has some robotic characteristics thus seems to generate a positive effect on trust, "I don't really like human voices, I prefer when it's more robotic, a bit spatial because it's more modern, it's more futuristic...it's a machine, I expect a voice machine", another respondent adds "it doesn't bother me that the voice is robotic, it doesn't bother me on the contrary, that way I'm aware that I'm exchanging with a machine and not a human, I don't want the robot to imitate the human, it's not a human". The perceived realism strongly influences the reactions of users, "if it was a human voice it would be weirder than if it was a robot voice [...] I prefer this robot side because a human voice would put me more uncomfortable. A human voice tends to humanize technology even more and this boundary between human and machine could scare me", a phenomenon which is reminiscent of the valley of the uncanny (MacDorman, 2019), "you imagine I'm talking to someone thinking it's a human and finally I realize it was a robot… frankly I wouldn't trust it". The voice assistant having no visual representation unlike virtual agents and chatbots, a respondent adds that with this type of technology it is necessary to have "a few clues that allow to clearly identify the artificial character of the voice and the system with whom I speak". An assistant with a very realistic human voice seems disturbing, "I find the voice more unhealthy, it looks more stupid" or even "this does not inspire confidence in me". It even brings a certain form of mistrust, "I don't really know what I have to do, he has a human voice but it's weird, I will trust him less". In addition, the voice seems to have an impact on social presence, as some respondents indicate, "sometimes it gives a nice side to talking to someone", or even "I preferred the voice of Google Home because we have the impression that he was no longer there with us". One respondent told us "it also brings a presence, even if it is not human, it is still more pleasant than staying behind a screen to type, it is more lively, more playful and more pleasant". The anthropomorphic character adds a little more to the technology, "what's nice is that the assistant has a first name, so it allows you to get closer to him and the voice". Conversely, when users interact with a voice assistant benefiting from a very realistic human voice, they seem to be in resistance "I had the impression that it was an answering machine completely".

Contribution of research and conclusion

The theoretical interest of this research is to study the multidisciplinary concepts of HMIs and voice, making it possible to highlight the effects of the assistant's voice on user reactions and to enrich the literature in digital marketing. Despite the work on the uses of virtual voiceactivated assistants (the levers and obstacles to their adoption in particular), or the work on the voice of chatbots and virtual agents, we found no study that was specifically interested in the voice of the assistant. If the voice gives substance to a machine, and more particularly to a voice assistant devoid of visual representation, we are faced with two possible choices: to provide the assistant with a synthetic voice that resembles a human voice in every way or to opt for a synthetic voice which, although based on human phonemes, allows the user to identify that he is exchanging with a machine, and not with a human. Our qualitative consumer research confirms the literature on the importance of the assistant's voice. On the other hand, our analysis on the voice is opposed to the literature carried out on virtual agents, we highlight that a voice assistant equipped with a more robotic synthetic voice seems better appreciated than an overly realistic human voice. From a managerial point of view, this research aims to suggest lines of thought for designers of voice assistants as well as brands wishing to develop their voice assistant and improve the relationship with their consumers [START_REF] Viot | Les agents virtuels intelligents : quels atouts pour la relation client ?[END_REF]. The voice offers tremendous opportunities for experimentation and invention of new uses, an unprecedented opportunity to create an online experience specific to each site and to stand out on the web (Reeves et al, 2019). The next few years promise a disruption of web browsing inherited from aging HMIs, voice assistants are likely to significantly change both consumer behaviors and marketing strategies [START_REF] Mari | The Evolution of Marketing in the Context of Voice Commerce[END_REF]. The voice opens up new perspectives, where the rules of the game have to be reinvented [START_REF] Kumar | Transformative Marketing: The Next 20 Years[END_REF]. Given the exploratory nature of our research, our conclusions still have certain limitations. Our study has limited external validity due to the size and composition of our sample. It would be appropriate to undertake an experiment on a voice assistant in order to modulate its voice (human versus robotic) and test the impact of the different voice characteristics on the users.