Evoking non-repertory verbal behavior across operant classes : the effects of motor echoic sign language training within the context of a motivating operation

The individual effects that echoic, mand, and sign language training procedures have on the acquisition of verbal behavior have been widely demonstrated, but more efficient strategies are still needed. This study combined all three treatment strategies into one treatment intervention in order to investigate the joint effects they may have on verbal behavior. Six participants took part in the study. Intervention totaled 1 hour/day for 5 days/week until mastery criterion for motor echoic behavior was achieved. Although motor echoic behavior were solely targeted for acquisition, significant increases in spontaneous motor mands were noted in all treatment participants. Additionally, 4 treatment participants also demonstrated significant gains in vocal echoics and spontaneous vocal mands. No significant increases were noted for the control participant. Results suggest that the aforementioned procedure may provide more efficient results as a first-step to teaching a functional repertoire of verbal behavior to developmentally delayed children.

The differential effects of *American and British trial proceedings on juror decision-making

Seven basic elements differentiate British from American trial procedures: confining attorneys to their tables; dealing with objections outside the presence of the jury; resolving disagreements between attorneys prior to objections being made; presenting the defense opening statement at the close of the prosecution case; the judge directly questions witnesses and has a wider latitude in controlling the evidence; and the judge gives a summation of all the evidence presented to the jury (Fulero & Turner, 1997). The present experiment examined the influence of these different courtroom procedures, judges' non-verbal behavior, and evidence strength on juror decision-making. Using models of persuasion to understand how the varying elements may effect juror decision-making, it was predicted that trials following American courtroom procedures would be more distracting for jurors and as such, they would be more likely to rely on the peripheral cue of the judge's expectations for trial outcome as expressed in his nonverbal behavior. In trials following British procedures jurors should be less distracted and better able to scrutinize the strength of the evidence that in turn should minimize the influence of the judge's nonverbal behavior. Two hundred forty-five participants viewed a mock civil trial in which courtroom procedure, judge's nonverbal behavior, and evidence strength were varied. Analyses suggest that courtroom procedure and evidence strength influenced the direction of participants' verdicts, but that judge's nonverbal behavior did not have a direct impact on verdict preference. Judge's nonverbal behavior appeared to influence other measures related to verdict. Participants were more confident in their verdicts when they agreed with judge's nonverbal behavior and when they viewed British courtroom procedures. Participants were more likely to return estimates of the defendant's liability that reflected judge's nonverbal behavior and a congruency with evidence strength. Participants also recalled more facts in the British conditions than in the American conditions. These findings are interpreted as indicating the importance of the impact of trial procedures and of nonverbal influence. ^

Two -way direction of influence in mother-infant interaction as denoted by concurrent reciprocal learning processes

This series of 5 single-subject studies used the operant conditioning paradigm to investigate, within the two-way influence process, how (a) contingent infant attention can reinforce maternal verbal behaviors during a period of mother-infant interaction and under subsequent experimental manipulation. Differential reinforcement was used to determine if it is possible that an infant attending to the mother (denoted by head-turns towards the image of the mother plus eye contact) increases (reinforces) the mother's verbal response (to a cue from the infant) upon which the infant behavior is contingent. There was also (b) an evaluation during the contrived parent-infant interaction for concurrent operant learning of infant vocal behavior via contingent verbal responding (reinforcement) implemented by the mother. Further, it was noted (c) whether or not the mother reported being aware that her responses were influenced by the infant's behavior. Findings showed: the operant conditioning of the maternal verbal behaviors were reinforced by contingent infant attention; and the operant conditioning of infant vocalizations was reinforced by contingent maternal verbal behaviors. No parent reported (1) being aware of the increase in their verbal response reinforced during operant conditioning of parental behavior nor a decrease in those responses during the DRA reversal phase, or (2) noticing a contingency between infant's and mother's response. By binomial 1-tail tests, the verbal-behavior patterns of the 5 mothers were conditioned by infant reinforcement (p < 0.02) and, concurrently, the vocal-response patterns of the 5 infants were conditioned by maternal reinforcement (p < 0.02). A program of systematic empirical research on the determinants of concurrent conditioning within mother-child interaction may provide a way to evaluate the differential effectiveness of interventions aimed at improving parent-child interactions. The work conducted in the present study is one step in this direction. ^

Think Before You Speak: Increasing a Student’s Appropriate Verbal Responses During Classroom Instruction

This study compared the effects of two intervention packages on increasing the appropriate verbal responses of a 7th-grade student. The interventions were determined by the results of a functional assessment of behavior. An alternating interventions design was used. Both intervention packages were successful in increasing the target behavior.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^