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Comfort with Robots Influences Rapport with a Social, Entraining Teachable Robot
Abstract
Teachable agents are pedagogical agents that employ the ‘learning-by-teaching’ strategy, which facilitates learning by encouraging students to construct explanations, reflect on misconceptions, and elaborate on what they know. Teachable agents present unique opportunities to maximize the benefits of a ‘learning-by-teaching’ experience. For example, teachable agents can provide socio-emotional support to learners, influencing learner self-efficacy and motivation, and increasing learning. Prior work has found that a teachable agent which engages learners socially through social dialogue and paraverbal adaptation on pitch can have positive effects on rapport and learning. In this work, we introduce Emma, a teachable robotic agent that can speak socially and adapt on both pitch and loudness. Based on the phenomenon of entrainment, multi-feature adaptation on tone and loudness has been found in human-human interactions to be highly correlated to learning and social engagement. In a study with 48 middle school participants, we performed a novel exploration of how multi-feature adaptation can influence learner rapport and learning as an independent social behavior and combined with social dialogue. We found significantly more rapport for Emma when the robot both adapted and spoke socially than when Emma only adapted and indications of a similar trend for learning. Additionally, it appears that an individual’s initial comfort level with robots may influence how they respond to such behavior, suggesting that for individuals who are more comfortable interacting with robots, social behavior may have a more positive influence.
... These agents have been shown to facilitate learning due to the effect of learning by teaching (Leelawong and Biswas, 2008) and the rapport the agents build with learners (Gulz et al., 2011). Inspired by theories suggesting that rapport is tied to verbal and non-verbal alignment (Lubold et al., 2019;Tickle-Degnen and Rosenthal, 1990), prior educational research has explored relationships between rapport with agents and various forms of alignment such as lexical (Rosenthalvon der Pütten et al., 2016;Lubold, 2018) and acoustic-prosodic (Lubold, 2018;Kory-Westlund and Breazeal, 2019) alignment. ...
... H2: Students feel more rapport with Emma when they align with Emma more (H2-a), she aligns with them more (H2-b), and alignment is more symmetric (H2-c). Human-human interactions show positive correlations between alignment and rapport (Lubold et al., 2019;Tickle-Degnen and Rosenthal, 1990;Sinha and Cassell, 2015). These are bi-directional; people feel a rapport when aligning with their partners and being aligned by their partners (Chartrand and van Baaren, 2009). ...
... Our methods expand prior literature by comparing alignment behavior in H-R and H-H-R settings and extending recent work by Dubuisson Duplessis et al. (2021) to the speaker-level act of activeness in the alignment process. Our results imply learners' lexical alignment with teachable agents may not always increase rapport with a teachable agent, unlike predictions from alignment theories (Lubold et al., 2019;Tickle-Degnen and Rosenthal, 1990) largely based on human-human interactions. Future work can expand our work by looking at the role of H-H portions of H-H-R interactions in their H-R portion and the effect of miscommunication as an intermediate variable on the negative correlations between rapport and learners' alignment and by extending the measures to multi-party settings without disentanglement. ...
... These agents have been shown to facilitate learning due to the effect of learning by teaching (Leelawong and Biswas, 2008) and the rapport the agents build with learners (Gulz et al., 2011). Inspired by theories suggesting that rapport is tied to verbal and non-verbal alignment (Lubold et al., 2019;Tickle-Degnen and Rosenthal, 1990), prior educational research has explored relationships between rapport with agents and various forms of alignment such as lexical (Rosenthalvon der Pütten et al., 2016;Lubold, 2018) and acoustic-prosodic (Lubold, 2018;Kory-Westlund and Breazeal, 2019) alignment. ...
... H2: Students feel more rapport with Emma when they align with Emma more (H2-a), she aligns with them more (H2-b), and alignment is more symmetric (H2-c). Human-human interactions show positive correlations between alignment and rapport (Lubold et al., 2019;Tickle-Degnen and Rosenthal, 1990;Sinha and Cassell, 2015). These are bi-directional; people feel a rapport when aligning with their partners and being aligned by their partners (Chartrand and van Baaren, 2009). ...
... Our methods expand prior literature by comparing alignment behavior in H-R and H-H-R settings and extending recent work by Dubuisson Duplessis et al. (2021) to the speaker-level act of activeness in the alignment process. Our results imply learners' lexical alignment with teachable agents may not always increase rapport with a teachable agent, unlike predictions from alignment theories (Lubold et al., 2019;Tickle-Degnen and Rosenthal, 1990) largely based on human-human interactions. Future work can expand our work by looking at the role of H-H portions of H-H-R interactions in their H-R portion and the effect of miscommunication as an intermediate variable on the negative correlations between rapport and learners' alignment and by extending the measures to multi-party settings without disentanglement. ...
Speakers build rapport in the process of aligning conversational behaviors with each other. Rapport engendered with a teachable agent while instructing domain material has been shown to promote learning. Past work on lexical alignment in the field of education suffers from limitations in both the measures used to quantify alignment and the types of interactions in which alignment with agents has been studied. In this paper, we apply alignment measures based on a data-driven notion of shared expressions (possibly composed of multiple words) and compare alignment in one-on-one human-robot (H-R) interactions with the H-R portions of collaborative human-human-robot (H-H-R) interactions. We find that students in the H-R setting align with a teachable robot more than in the H-H-R setting and that the relationship between lexical alignment and rapport is more complex than what is predicted by previous theoretical and empirical work.
... For this study, a Nao robot named Emma was taught by middle school students how to solve mathematics problems utilizing spoken language [10]. Students sat at a desk with a Surface Pro tablet in front of them. ...
... Table 1 is an example of exchange between Emma and a learner on a ratio and proportions problem. More details on the system design can be found in [10]. Over multiple sessions, Emma mimicked the [19]'s model of rapport as follows. ...
Social robots have been shown to be effective educational tools. Rapport, or interpersonal closeness, can lead to better human-robot interactions and positive learning outcomes. Prior research has investigated the effects of social robots on student rapport and learning in a single session, but little is known about how individuals build rapport with a robot over multiple sessions. We reported on a case study in which 7 middle school students explained mathematics concepts to an intelligent teachable robot named Emma for five sessions. We modeled learners’ rapport-building linguistic strategies to understand whether the ways middle school students build rapport with the robot over time follow the same trends as human conversation, and how individual differences might mediate the rapport between human and robot.
... Lindberg et al. (2017) conducted a within-subjects comparison between a robot tutee and a teachable agent, and mainly found individual differences between children. In a similar vein, children's rapport towards a robot tutee has been shown to fluctuate both between children and over time (Tian et al., 2020), and, e.g., children's pre-existing comfort levels with robots seem to influence their acceptance of a robot tutee's social behavior (Lubold et al., 2019). In one of our previous studies, we found that children employ a range of strategies to repair interactions with a robot tutee behaving in socially inappropriate ways, ranging from trying to understand and adapt to the robot, to establishing a social distance to it . ...
Social robots are increasingly being studied in educational roles, including as tutees in learning-by-teaching applications. To explore the benefits and drawbacks of using robots in this way, it is important to study how robot tutees compare to traditional learning-by-teaching situations. In this paper, we report the results of a within-subjects field experiment that compared a robot tutee to a human tutee in a Swedish primary school. Sixth-grade students participated in the study as tutors in a collaborative mathematics game where they were responsible for teaching a robot tutee as well as a third-grade student in two separate sessions. Their teacher was present to provide support and guidance for both sessions. Participants' perceptions of the interactions were then gathered through a set of quantitative instruments measuring their enjoyment and willingness to interact with the tutees again, communication and collaboration with the tutees, their understanding of the task, sense of autonomy as tutors, and perceived learning gains for tutor and tutee. The results showed that the two scenarios were comparable with respect to enjoyment and willingness to play again, as well as perceptions of learning gains. However, significant differences were found for communication and collaboration, which participants considered easier with a human tutee. They also felt significantly less autonomous in their roles as tutors with the robot tutee as measured by their stated need for their teacher's help. Participants further appeared to perceive the activity as somewhat clearer and working better when playing with the human tutee. These findings suggest that children can enjoy engaging in peer tutoring with a robot tutee. However, the interactive capabilities of robots will need to improve quite substantially before they can potentially engage in autonomous and unsupervised interactions with children.
Digital transformation has disrupted learning in educational institutions, with conversational AI, such as ChatGPT, playing a significant role. Conversational AI varies from knowledgable fact-based dialogue systems to bonding learning companions (LC) that have gained attention in research and practice, aiming to establish long-term relationships with learners. This study conceptualizes the subjective value-in-use (ViU) of conversational AI, employing the framework of service-dominant logic. By conducting a systematic literature review and examining qualitative experiences of university students using conversational AI in a multi-week context, we explore ViU dimensions and discuss implications for the application of conversational AI in education. Our research highlights the multifaceted ViU of LCs, emphasizing aspects like social and hedonic value, autonomy, and inspiration. Considering perspectives of both learners and educators is crucial for integrating conversational AI effectively. This study provides insights from a value-centered perspective and encourages further exploration of the teachers' viewpoint and the ethical use of conversational AI in education.
Customer comfort during service interactions is essential for creating enjoyable customer experiences. However, although service robots are already being used in a number of service industries, it is currently not clear how customer comfort can be ensured during these novel types of service interactions. Based on a 2 × 2 online between-subjects design including 161 respondents using pictorial and text-based scenario descriptions, we empirically demonstrate that human-like (vs machine-like) service robots make customers feel more comfortable because they facilitate rapport building. Social presence does not underlie this relationship. Importantly, we find that these positive effects diminish in the presence of service failures.
Purpose: Conversational entrainment, the phenomenon whereby communication partners synchronize their behavior, is considered essential for productive and fulfilling conversation. Lack of entrainment could, therefore, negatively impact conversational success. Although studied in many disciplines, entrainment has received limited attention in the field of speech-language pathology, where its implications may have direct clinical relevance.
Method: A novel computational methodology, informed by expert clinical assessment of conversation, was developed to investigate conversational entrainment across multiple speech dimensions in a corpus of experimentally elicited conversations involving healthy participants. The predictive relationship between the methodology output and an objective measure of conversational success, communicative efficiency, was then examined.
Results: Using a real versus sham validation procedure, we find evidence of sustained entrainment in rhythmic, articulatory, and phonatory dimensions of speech. We further validate the methodology, showing that models built on speech signal entrainment measures consistently outperform models built on nonentrained speech signal measures in predicting communicative efficiency of the conversations.
Conclusions: A multidimensional, clinically meaningful methodology for capturing conversational entrainment, validated in healthy populations, has implications for disciplines such as speech-language pathology where conversational entrainment represents a critical knowledge gap in the field, as well as a potential target for remediation.
We propose to change the default P-value threshold for statistical significance for claims of new discoveries from 0.05 to 0.005.
Prior research with preschool children has established that dialogic or active book reading is an effective method for expanding young children’s vocabulary. In this exploratory study, we asked whether similar benefits are observed when a robot engages in dialogic reading with preschoolers. Given the established effectiveness of active reading, we also asked whether this effectiveness was critically dependent on the expressive characteristics of the robot. For approximately half the children, the robot’s active reading was expressive; the robot’s voice included a wide range of intonation and emotion (Expressive). For the remaining children, the robot read and conversed with a flat voice, which sounded similar to a classic text-to-speech engine and had little dynamic range (Flat). The robot’s movements were kept constant across conditions. We performed a verification study using Amazon Mechanical Turk (AMT) to confirm that the Expressive robot was viewed as significantly more expressive, more emotional, and less passive than the Flat robot. We invited 45 preschoolers with an average age of 5 years who were either English Language Learners (ELL), bilingual, or native English speakers to engage in the reading task with the robot. The robot narrated a story from a picture book, using active reading techniques and including a set of target vocabulary words in the narration. Children were post-tested on the vocabulary words and were also asked to retell the story to a puppet. A subset of 34 children performed a second story retelling 4–6 weeks later. Children reported liking and learning from the robot a similar amount in the Expressive and Flat conditions. However, as compared to children in the Flat condition, children in the Expressive condition were more concentrated and engaged as indexed by their facial expressions; they emulated the robot’s story more in their story retells; and they told longer stories during their delayed retelling. Furthermore, children who responded to the robot’s active reading questions were more likely to correctly identify the target vocabulary words in the Expressive condition than in the Flat condition. Taken together, these results suggest that children may benefit more from the expressive robot than from the flat robot.
This chapter discusses design challenges encountered when developing a conversational pedagogical agent. By tracing the historical roots of pedagogical agents in Intelligent Tutoring Systems (ITS), we discern central developments in creating an agent that is both knowledgeable and fosters a social relationship with the learner. Main challenges faced when attempting to develop a pedagogical agent of this kind relate to: i) learners' expectations on the agent's knowledge and social profile, ii) dealing with learners' engagement in off-task conversation and iii) managing potential abuse of the agent. We discuss these challenges and possible ways to address them, with reference to an ongoing Research & Development project, and with a focus on the design of a pedagogical agent's visual embodiment and its conversational capabilities.
Conversational entrainment, a pervasive communication phenomenon in which dialogue partners adapt their behaviors to align more closely with one another, is considered essential for successful spoken interaction. While well-established in other disciplines, this phenomenon has received limited attention in the field of speech pathology and the study of communication breakdowns in clinical populations. The current study examined acoustic-prosodic entrainment, as well as a measure of communicative success, in three distinctly different dialogue groups: (i) healthy native vs. healthy native speakers (Control), (ii) healthy native vs. foreign-accented speakers (Accented), and (iii) healthy native vs. dysarthric speakers (Disordered). Dialogue group comparisons revealed significant differences in how the groups entrain on particular acoustic–prosodic features, including pitch, intensity, and jitter. Most notably, the Disordered dialogues were characterized by significantly less acoustic-prosodic entrainment than the Control dialogues. Further, a positive relationship between entrainment indices and communicative success was identified. These results suggest that the study of conversational entrainment in speech pathology will have essential implications for both scientific theory and clinical application in this domain.
In conversational dialogue, grounding refers to the joint activity of speakers and listeners establishing common ground—a shared understanding of their mutual knowledge, beliefs, and assumptions. Grounding is a critical component of successful collaborative interactions and plays an important role in collaborative learning. In this work, we investigate grounding utilizing acoustic-prosodic entrainment. Acoustic-prosodic entrainment occurs in spoken dialogue when speakers adapt their tone, loudness, voice quality, or speaking rate to that of their partner. We explore the relationship between grounding and acoustic-prosodic entrainment within on-task and off-task dialogue, and we find that grounding behaviors in both on-task and off-task dialogue are differentiated by how speakers entrain.
In spoken dialogue analysis, the speech signal is a rich source of information. We explore in this paper how low level features of the speech signal, such as pitch, loudness, and speaking rate, can inform a model of student interaction in collaborative learning dialogues. For instance, can we observe the way that two people's manners of speaking change over time to model something like rapport? By detecting interaction qualities such as rapport, we can better support collaborative interactions, which have been shown to be highly conducive to learning. For this, we focus on one particular phenomenon of spoken conversation, known as acoustic-prosodic entrainment, where dialogue partners become more similar to each other in their pitch, loudness, or speaking rate during the course of a conversation. We examine whether acoustic-prosodic entrainment is present in a novel corpus of collaborative learning dialogues, how people appear to entrain, to what degree, and report on the acoustic-prosodic features which people entrain on the most. We then investigate whether entrainment can facilitate detection of rapport, a social quality of the interaction. We find that entrainment does correlate to rapport; speakers appear to entrain primarily by matching their prosody on a turn-by-turn basis, and pitch is the most significant acoustic-prosodic feature people entrain on when rapport is present.
The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental results, particularly as a recommendation for articles in the Journal of Problem Solving. The Bayes factor provides information with a similar purpose to the p-value—to allow the researcher to make statistical inferences from data provided by experiments. While the p-value is widely used, the Bayes factor provides several advantages, particularly in that it allows the researcher to make a statement about the alternative hypothesis, rather than just the null hypothesis. In addition, it provides a clearer estimate of the amount of evidence present in the data. Building on previous work by authors such as Wagenmakers (2007), Rouder et al. (2009), and Masson (2011), this article provides a short introduction to Bayes factors, before providing a practical guide to their computation using examples from published work on problem solving.
Social robots are finding increasing application in the domain of education, particularly for children, to support and augment learning opportunities. With an implicit assumption that social and adaptive behaviour is desirable, it is therefore of interest to determine precisely how these aspects of behaviour may be exploited in robots to support children in their learning. In this paper, we explore this issue by evaluating the effect of a social robot tutoring strategy with children learning about prime numbers. It is shown that the tutoring strategy itself leads to improvement, but that the presence of a robot employing this strategy amplifies this effect, resulting in significant learning. However, it was also found that children interacting with a robot using social and adaptive behaviours in addition to the teaching strategy did not learn a significant amount. These results indicate that while the presence of a physical robot leads to improved learning, caution is required when applying social behaviour to a robot in a tutoring context.
We explore gender differences in the importance of reflected appraisals, self-perceived competence, and social comparisons as sources of self-esteem. Gender differences are expected for several reasons: sex role socialization may lead men and women to develop abilities to exploit different sources of self-esteem; men and women may learn to embrace different criteria for self-evaluation; and opportunities to experience self-enhancement in various ways may the distributed unequally between men and women. We find that women attach greater importance to reflected appraisals than do men, and that men attach greater importance to social comparisons than do women. No difference is found for self-perceived competence. Men and women are also much alike, we find, in that reflected appraisals are the most important source of self-esteem for both groups, followed by self-perceived competence and then by social comparisons. These finding are interpreted in terms of compensation/availability dynamic that is hypothesized to underlie self-esteem formation. Some implications of this analysis for modifying identity theory are discussed.
We provide evidence of persistent gender effects for students using advanced adaptive technology while learning mathematics. This technology improves each gender’s learning and affective predispositions toward mathematics, but specific features in the software help either female or male students. Gender differences were seen in the students’ style of use of the system, motivational goals, affective needs, and cognitive/affective benefits, as well as the impact of affective interventions involving pedagogical agents. We describe 4 studies, with hundreds of students in public schools over several years, which suggest that technology responses should probably be customized to each gender. This article shows differential results before, during, and after the use of adaptive tutoring software, indicating that digital tutoring systems can be an important supplement to mathematics classrooms but that male and female students should be addressed differently. Female students were more receptive than male students to seeking and accepting help provided by the tutoring system and to spending time seeing the hints; thus, they had a consistent general trend to benefit more from it, especially when affective learning companions were present. In addition, female students expressed positively valenced emotions most often and exhibited more productive behaviors when exposed to female characters; these affective pedagogical agents encouraged effort and perseverance. This was not the case for male students, who had more positive outcomes when no learning companion was present and their worst affective and cognitive outcomes when the female character was present. (PsycINFO Database Record (c) 2013 APA, all rights reserved)
In conversation, speakers have been shown to entrain, or become more similar to each other, in various ways. We measure entrainment on eight acoustic features extracted from the speech of subjects playing a cooperative computer game and associate the degree of entrainment with a number of manually-labeled social variables acquired using Amazon Mechanical Turk, as well as objective measures of dialogue success. We find that male-female pairs entrain on all features, while male-male pairs entrain only on particular acoustic features (intensity mean, intensity maximum and syllables per second). We further determine that entrainment is more important to the perception of female-male social behavior than it is for same-gender pairs, and it is more important to the smoothness and flow of male-male dialogue than it is for female-female or mixed-gender pairs. Finally, we find that entrainment is more pronounced when intensity or speaking rate is especially high or low.
Lexical entrainment is a measure of how the words that speakers use in a conversation become more similar over time. In this paper, we propose a measure of lexical entrainment for multi-party speaking situations. We apply this score to a corpus of student engineering groups using high-frequency words and project words, and investigate the relationship between lexical entrainment and group success on a class project. Our initial findings show that, using the entrainment score with project-related words, there is a significant difference between the lexical entrainment of high performing groups, which tended to increase with time, and the entrainment for low performing groups, which tended to decrease with time.
Understanding how children perceive and interact with teachable agents (systems where children learn through teaching a synthetic character embedded in an intelligent tutoring system) can provide insight into the effects of so-cial interaction on learning with intelligent tutoring systems. We describe results from a think-aloud study where children were instructed to narrate their experience teaching Stacy, an agent who can learn to solve linear equations with the student's help. We found treating her as a partner, primarily through aligning oneself with Stacy using pronouns like you or we rather than she or it significantly correlates with student learning, as do playful face-threatening comments such as teasing, while elaborate explanations of Stacy's behavior in the third-person and formal tutoring statements reduce learning gains. Additionally, we found that the agent's mistakes were a significant predictor for students shifting away from alignment with the agent.
Prior research has established that peer tutors can benefit academically from their tutoring experiences. However, although tutor learning has been observed across diverse settings, the magnitude of these gains is often underwhelming. In this review, the authors consider how analyses of tutors' actual behaviors may help to account for variation in learning outcomes and how typical tutor- ing behaviors may create or undermine opportunities for learning. The authors examine two tutoring activities that are commonly hypothesized to support tutor learning: explaining and questioning. These activities are hypothesized to sup- port peer tutors' learning via reflective knowledge-building, which includes self-monitoring of comprehension, integration of new and prior knowledge, and elaboration and construction of knowledge. The review supports these hypothe- ses but also finds that peer tutors tend to exhibit a pervasive knowledge-telling bias. Peer tutors, even when trained, focus more on delivering knowledge rather than developing it. As a result, the true potential for tutor learning may rarely be achieved. The review concludes by offering recommendations for how future research can utilize tutoring process data to understand how tutors learn and perhaps develop new training methods.
The purpose of this article is to offer a conceptualization of rapport that has utility for identifying the nonverbal correlates associated with rapport. We describe the nature of rapport in terms of a dynamic structure of three interrelating components: mutual attentiveness, positivity, and coordination. We propose that the relative weighting of these components in the experience of rapport changes over the course of a developing relationship between individuals. In early interactions, positivity and attentiveness are more heavily weighted than coordination, whereas in later interactions, coordination and attentiveness are the more heavily weighted components. Because of the gestalt nature of the experience of rapport, it is not easy to identify nonverbal behavioral correlates of the components. We discuss two approaches to nonverbal measurement, molecular and molar, along with recommendations for their appropriate application in the study of rapport at different stages of an interpersonal relationship. We present a meta-analytic study that demonstrates the effect of nonverbal behavior, measured at the molecular level, on the positivity component of rapport, and we conclude with an outline of hypotheses relevant to the investigation of the nonverbal correlates of rapport.
Betty’s Brain is a computer-based learning environment that capitalizes on the social aspects of learning. In Betty’s Brain,
students instruct a character called a Teachable Agent (TA) which can reason based on how it is taught. Two studies demonstrate
the protégé effect: students make greater effort to learn for their TAs than they do for themselves. The first study involved 8th-grade students
learning biology. Although all students worked with the same Betty’s Brain software, students in the TA condition believed
they were teaching their TAs, while in another condition, they believed they were learning for themselves. TA students spent
more time on learning activities (e.g., reading) and also learned more. These beneficial effects were most pronounced for
lower achieving children. The second study used a verbal protocol with 5th-grade students to determine the possible causes
of the protégé effect. As before, students learned either for their TAs or for themselves. Like study 1, students in the TA
condition spent more time on learning activities. These children treated their TAs socially by attributing mental states and
responsibility to them. They were also more likely to acknowledge errors by displaying negative affect and making attributions
for the causes of failures. Perhaps having a TA invokes a sense of responsibility that motivates learning, provides an environment
in which knowledge can be improved through revision, and protects students’ egos from the psychological ramifications of failure.
We describe acoustic/prosodic and lexical correlates of social variables annotated on a large corpus of task-oriented spontaneous speech. We employ Amazon Mechanical Turk to label the corpus with a large number of social behaviors, examining results of three of these here. We find significant differences between male and female speakers for perceptions of attempts to be liked, likeability, speech planning, that also differ depending upon the gender of their conversational partners.
Prosodic synchrony has been reported to be an important aspect of conversational dyads. In this paper, synchrony in four different dyads is examined. A Time Aligned Moving Average (TAMA) procedure is used to temporally align the prosodic measurements for the detection of synchrony in the dyads. An overlapping windowed correlation procedure is used to measure synchrony for six different prosodic parameters: mean pitch, pitch range, mean intensity, intensity range, centre of gravity and spectral slope. This study shows that a windowed correlation procedure better captures the dynamic nature of speech synchrony than a single measure across a whole conversation. This method also enables points of concurrent synchrony between prosodic parameters to be detected. Moreover, the synchrony of the prosodic parameters was considered in relation to levels of agreement and disagreement in the four dyads. Results show only one parameter in one dyad to be significantly correlated with agreement/disagreement.
Social-psychological processes in humans will play an important role in long-term human-robot interactions. This study investigates people's perceptions of social presence in robots during (relatively) short interactions. Findings indicate that males tend to think of the robot as more human-like and accordingly show some evidence of "social facilitation" on an arithmetic task as well as more socially desirable responding on a survey administered by a robot. In contrast, females saw the robot as more machine-like, exhibited less socially desirable responding to the robot's survey, and were not socially facilitated by the robot while engaged in the arithmetic tasks. Various alternative accounts of these findings are explored and the implications of these results for future work are discussed.
Tutorial Dialog has been shown to be effective in supporting both individual as well as group learners. However, unlike the
case with individual learners, teams of learners often ignore and abuse the automated tutors. Both theory and empirical work
in the area of small group communication argue that group participants display both task as well as socio-emotional behaviors
during interactions. However, in connection with automated conversational agents, the effects of socio-emotional behaviors
are much less well understood, especially in the case of multi-party interactions. In this paper, we will describe an evaluation
of a socially capable conversational tutor that supports teams of three (or more) learners in a design task. This tutor is
evaluated in comparison with a socially neutral baseline agent and human capability “gold standard” tutors demonstrating that
the socially capable tutor achieves significantly higher learning gains than the neutral, purely task focused tutor and learning
gains not significantly different from the human capability “gold standard” tutors.
In this paper we examine whether the student-to-tutor con- vergence of lexical and speech features is a useful predictor of learn- ing in a corpus of spoken tutorial dialogs. This possibility is raised by the Interactive Alignment Theory, which suggests a connection between convergence of speech features and the amount of semantic alignment between partners in a dialog. A number of studies have shown that users converge their speech productions toward dialog systems. If, as we hy- pothesize, semantic alignment between a student and a tutor (or tutor- ing system) is associated with learning, then this convergence may be correlated with learning gains. We present evidence that both lexical convergence and convergence of an acoustic/prosodic feature are use- ful features for predicting learning in our corpora. We also nd that our measure of lexical convergence provides a stronger correlation with learning in a human/computer corpus than did a previous measure of lexical cohesion.
One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for 8 standard statistical tests: (1) the difference between independent means, (2) the significance of a product-moment correlation, (3) the difference between independent rs, (4) the sign test, (5) the difference between independent proportions, (6) chi-square tests for goodness of fit and contingency tables, (7) 1-way analysis of variance (ANOVA), and (8) the significance of a multiple or multiple partial correlation.
Progress in science often comes from discovering invariances in relationships among variables; these invariances often correspond to null hypotheses. As is commonly known, it is not possible to state evidence for the null hypothesis in conventional significance testing. Here we highlight a Bayes factor alternative to the conventional t test that will allow researchers to express preference for either the null hypothesis or the alternative. The Bayes factor has a natural and straightforward interpretation, is based on reasonable assumptions, and has better properties than other methods of inference that have been advocated in the psychological literature. To facilitate use of the Bayes factor, we provide an easy-to-use, Web-based program that performs the necessary calculations.
This study analyzed senior dental students' perceptions prior to extramural rotations for comfort and future willingness to treat patients with special needs and other vulnerable groups. The sample included 690 University of Iowa senior dental students who graduated from 1992 through 2004. These students completed a questionnaire concerning twelve vulnerable population groups. Logistic regression models were performed, using student comfort and future willingness to treat each group as the dependent variable. There was a wide percentage of range of comfort with these groups, yet there was no individual group that more than 60 percent of these students were willing to treat in their future practices. Generally, prior experience with the group had a positive impact on comfort level. When gender was included in the regression models, male students were more likely to express comfort. In all instances except one, experience had a positive influence on perceived future willingness to treat the associated group. However, younger graduates had a greater willingness to treat. When controlling for other variables within the future willingness to treat models, comfort was statistically significant only for HIV+/AIDS and non-English speaking groups. This study provides insight about comfort with and perceived future willingness to treat special needs and other vulnerable patient groups.
This paper describes the experiences from the iterative design of a fetch-and-carry-robot, to be used by motion-impaired people in an office environment. A user-centered approach was chosen, involving several steps of information elicitation to inform the design. We describe the main elements of the design process, the communication and interaction components of the final prototype system, and an evaluation of the system in the form of a longitudinal study. Results from this study confirmed that continuous testing with users is extremely important in the design process for service robots. The trials have also revealed that interaction design for robots should not focus only on the individual user, but that other members in the environment can be seen "secondary users" or "bystanders" who tend to relate to the robot actively in various ways. We conclude that these social and collaborative issues should be studied in future research.
The theory of accommodation is concerned with motivations underlying and consequences arising from ways in which we adapt our language and communication patterns toward others. Since accommodation theory's emergence in the early l970s, it has attracted empirical attention across many disciplines and has been elaborated and expanded many times. In Contexts of Accommodation, accommodation theory is presented as a basis for sociolinguistic explanation, and it is the applied perspective that predominates this edited collection. The book seeks to demonstrate how the core concepts and relationships invoked by accommodation theory are available for addressing altogether pragmatic concerns. Accommodative processes can, for example, facilitate or impede language learners' proficiency in a second language as well as immigrants' acceptance into certain host communities; affect audience ratings and thereby the life of a television program; affect reaction to defendants in court and hence the nature of the judicial outcome; and be an enabling or detrimental force in allowing handicapped people to fulfil their communicative potential. Contexts of Accommodation will appeal to researchers and advanced students in language and communication sciences, as well as to sociolinguists, anthropologists, sociologists and psychologists.
Pedagogical agents have the potential to provide not only cognitive support to learners but socio-emotional support through social behavior. Socio-emotional support can be a critical element to a learner’s success, influencing their self-efficacy and motivation. Several social behaviors have been explored with pedagogical agents including facial expressions, movement, and social dialogue; social dialogue has especially been shown to positively influence interactions. In this work, we explore the role of paraverbal social behavior or social behavior in the form of paraverbal cues such as tone of voice and intensity. To do this, we focus on the phenomenon of entrainment, where individuals adapt their paraverbal features of speech to one another. Paraverbal entrainment in human-human studies has been found to be correlated with rapport and learning. In a study with 72 middle school students, we evaluate the effects of entrainment with a teachable robot, a pedagogical agent that learners teach how to solve ratio problems. We explore how a teachable robot which entrains and introduces social dialogue influences rapport and learning; we compare with two baseline conditions: a social condition, in which the robot speaks socially, and a non-social condition, in which the robot neither entrains nor speaks socially. We find that a robot that does entrain and speaks socially results in significantly more learning.
Teachable robots are a form of social robot for education, where learners engage in conversation to teach the robot like they would a peer. Part of the popularity of social robots is their ability to utilize social channels of communication to foster productive social experiences, interactions which help individuals grow and develop. Teachable robots have potential to utilize social channels of communication to create social experiences which can help learners develop self-efficacy, an individual's belief in their ability to succeed. In this paper, we present a fully autonomous robot for middle school math; we iterate through three design phases and analyze responses to identify how to better foster productive social experiences for self-efficacy. We report six design recommendations; for example, for low self-efficacy individuals, an ideal design should incorporate problem-solving statements and positivity to foster social experiences of mastery and social persuasion.
The CoWriter activity involves a child in a rich and complex interaction where he has to teach handwriting to a robot. The robot must convince the child it needs his help and it actually learns from his lessons. To keep the child engaged, the robot must learn at the right rate, not too fast otherwise the kid will have no opportunity for improving his skills and not too slow otherwise he may loose trust in his ability to improve the robot' skills. We tested this approach in real pedagogic/therapeutic contexts with children in difficulty over repeated long sessions (40-60 min). Through 3 different case studies, we explored and refined experimental designs and algorithms in order for the robot to adapt to the troubles of each child and to promote their motivation and self-confidence. We report positive observations, suggesting commitment of children to help the robot, and their comprehension that they were good enough to be teachers, overcoming their initial low confidence with handwriting.
Bayes factors have been advocated as superior to pp-values for assessing statistical evidence in data. Despite the advantages of Bayes factors and the drawbacks of pp-values, inference by pp-values is still nearly ubiquitous. One impediment to the adoption of Bayes factors is a lack of practical development, particularly a lack of ready-to-use formulas and algorithms. In this paper, we discuss and expand a set of default Bayes factor tests for ANOVA designs. These tests are based on multivariate generalizations of Cauchy priors on standardized effects, and have the desirable properties of being invariant with respect to linear transformations of measurement units. Moreover, these Bayes factors are computationally convenient, and straightforward sampling algorithms are provided. We cover models with fixed, random, and mixed effects, including random interactions, and do so for within-subject, between-subject, and mixed designs. We extend the discussion to regression models with continuous covariates. We also discuss how these Bayes factors may be applied in nonlinear settings, and show how they are useful in differentiating between the power law and the exponential law of skill acquisition. In sum, the current development makes the computation of Bayes factors straightforward for the vast majority of designs in experimental psychology.
This paper takes rapport (Spencer-Oatey 2000, 2002) as its central concern, since (im)politeness is typically associated in some way with harmonious/conflictual interpersonal relations. The paper discusses the factors that influence people's dynamic perceptions of rapport, and proposes that there are three key elements: behavioral expectations, face sensitivities, and interactional wants. The paper explores the components of these three elements and uses authentic discourse data to illustrate how people's judgments about rapport can be unpackaged in relation to these elements. The approach enables us to gain a deeper understanding of the factors that influence people's dynamic judgments of rapport, which is essential if we are to understand how and why problems of rapport occur.
The goal of this research was to use politeness theory to analyze the developing tutorial relationship between students and peer tutors in a university writing center. The study monitored two pairs of tutors and students over a period of six weeks, focusing on weeks one and six. Using partial transcripts of recorded sessions along with observation notes, the authors used discourse analysis to determine the significance of politeness in the functioning of the tutorial sessions. The authors concluded that in initial sessions, tutors use politeness strategies to shift between the collaborative role as peer and the authoritative role as tutor, relying more on negative politeness strategies, and after six weeks of recurring sessions, tutors rely less on negative politeness strategies and more on positive politeness strategies.
Persuasive Robotics is the study of persuasion as it applies to human-robot interaction (HRI). Persuasion can be generally defined as an attempt to change another's beliefs or behavior. The act of influencing others is fundamental to nearly every type of social interaction. Any agent desiring to seamlessly operate in a social manner will need to incorporate this type of core human behavior. As in human interaction, myriad aspects of a humanoid robot's appearance and behavior can significantly alter its persuasiveness - this work will focus on one particular factor: gender. In the current study, run at the Museum of Science in Boston, subjects interacted with a humanoid robot whose gender was varied. After a short interaction and persuasive appeal, subjects responded to a donation request made by the robot, and subsequently completed a post-study questionnaire. Findings showed that men were more likely to donate money to the female robot, while women showed little preference. Subjects also tended to rate the robot of the opposite sex as more credible, trustworthy, and engaging. In the case of trust and engagement the effect was much stronger between male subjects and the female robot. These results demonstrate the importance of considering robot and human gender in the design of HRI.
Given the recent advances in robot and synthetic character technology, many researchers are now focused on ways of establishing social relations between these agents and humans over long periods of time. Early studies have shown that the novelty effect of robots and agents quickly wears out and that people change their attitudes and preferences towards them over time. In this paper, we study the role of social presence in long-term human-robot interactions. We conducted a study where children played chess exercises with a social robot over a five week period. With this experiment, we identified possible key issues that should be considered when designing social robots for long-term interactions.
This paper focuses on the motivational concerns that underlie the management of relations. In linguistics, the management of relations has been discussed extensively within politeness theory, and so the paper starts by identifying four key issues of controversy in politeness theory: (a) should ‘polite’ language use be explained in terms of face (e.g. Brown, Penelope, Levinson, Stephen C., 1987. Politeness. Some Universals in Language Usage, CUP, Cambridge. [Originally published as Universals in Language Usage: Politeness Phenomenon. In: Goody, Esther, (Ed.), Questions and Politeness: Strategies in Social Interaction. CUP, New York, 1978), conversational maxims (e.g. Leech, Geoffrey N., 1983. Principles of Pragmatics. Longman, London), and/or conversational rights (e.g. Fraser, Bruce, 1990. Perspectives on politeness. Journal of Pragmatics 14 (2), 219–236); (b) why are speech acts such as orders interpersonally sensitive — is it because they are a threat to our autonomy (Brown and Levinson, 1987 [1978]), or because of cost–benefit concerns (Leech, 1983); (c) is Brown and Levinson's concept of negative face too individually focused, and should a social identity component be included (Matsumoto, Yoshiko, 1988. Reexamination of the universality of face: politeness phenomena in Japanese. Journal of Pragmatics 12, 403–426); and (d) is face just a personal/individual concern or can it be a group concern (Gao, Ge, 1996. Self and other: a Chinese perspective on interpersonal relationships. In: Gudykunst, W.B., Ting-Toomey, S., Nishida, T. (Eds.), Communication in Personal Relationships Across Cultures, Sage, London. pp. 81–101.)? The paper then uses reports of authentic rapport sensitive incidents to throw light on these controversial issues and to find out the relational management concerns that people perceive in their everyday lives. It maintains that such data is important to politeness theory, because linguistic politeness needs to be studied within the situated social psychological context in which it occurs. The paper ends by presenting and arguing for a conceptual framework that draws a fundamental distinction between face and sociality rights, and that incorporates an independent/interdependent perspective, thus providing a more comprehensive framework for analysing the management of relations than is currently available.
The American Board of Internal Medicine (ABIM) has recommended a specific number of procedures be done as a minimum standard for ensuring competence in various medical procedures. These minimum standards were determined by consensus of an expert panel and may not reflect actual procedural comfort or competence.
To estimate the minimum number of selected procedures at which a majority of internal medicine trainees become comfortable performing that procedure.
Cross-sectional, self-administered survey.
A military-based, a community-based, and 2 university-based programs.
Two hundred thirty-two internal medicine residents.
Survey questions included number of specific procedures performed, comfort level with performing specific procedures, and whether respondents desired further training in specific procedures. The comfort threshold for a given procedure was defined as the number of procedures at which two thirds or more of the respondents reported being comfortable or very comfortable performing that procedure.
For three of seven procedures selected, residents were comfortable performing the procedure at or below the number recommended by the ABIM as a minimum requirement. However, residents needed more procedures than recommended by the ABIM to feel comfortable with central venous line placement, knee joint aspiration, lumbar puncture, and thoracentesis. Using multivariate logistic regression analysis, variables independently associated with greater comfort performing selected procedures included increased number performed, more years of training, male gender, career goals, and for skin biopsy, training in the community-based program. Except for skin biopsy, comfort level was independent of training site. A significant number of advanced-year house officers in some programs had little experience in performing selected common ambulatory procedures.
Minimum standards for certifying internal medicine residents may need to be reexamined in light of house officer comfort level performing selected procedures.
In the field of psychology, the practice of p value null-hypothesis testing is as widespread as ever. Despite this popularity, or perhaps because of it, most psychologists are not aware of the statistical peculiarities of the p value procedure. In particular, p values are based on data that were never observed, and these hypothetical data are themselves influenced by subjective intentions. Moreover, p values do not quantify statistical evidence. This article reviews these p value problems and illustrates each problem with concrete examples. The three problems are familiar to statisticians but may be new to psychologists. A practical solution to these p value problems is to adopt a model selection perspective and use the Bayesian information criterion (BIC) for statistical inference (Raftery, 1995). The BIC provides an approximation to a Bayesian hypothesis test, does not require the specification of priors, and can be easily calculated from SPSS output.
When robots coexisting with humans are designed, it is important to evaluate psychological influence of shape, size and motion of the robots on the humans. For this purpose, an evaluation system of human psychology for coexisting robots using virtual reality is discussed. Virtual (CG) robots are visually presented to a human subject using CAVE system. The subject answers questionnaire about his impression on the robots and their motions, and his psychological state is evaluated. In the present paper, whether humans have similar impressions and feelings for real and virtual robots is investigated. Real and virtual mobile manipulators reach for subjects and pass nearby them. In both situations, the same motion patterns by these robots are presented to the subjects and psychologically evaluated by questionnaire. As the comparison results of this experiment, the subjects had similar feelings for the real and virtual robots.
Redefine statistical significance
- D Boeck