Conversation Partners Research Articles

Navigating platformized generative AI: Examining early adopters’ experiences through the lens of data reflectivity

Following the widely noticed launch of ChatGPT 3.5 in November 2022, an unprecedented number of users have started to experiment with generative AI for communication purposes. Prior studies have shown how users are commodified by platforms, and the unprecedented development of generative AI raises hence once again questions of platform dynamics vs user agency. In this study, we argue that platformized generative AI (GenAI) actively ‘talks back’ to their users, prompting them to act accordingly. Theoretically, we develop the concept of data reflectivity as a critical lens, showing that users exhibit reflective practices. These allow them to reflect upon their own role in relation to platformized GenAI and thus alter their patterns of action. The empirical case study, carried out in Spring 2023, draws on a survey with 60 early adopters and 14 subsequent semi-structured interviews, collected in an NGO operating in Southeast Asia. The thematic analysis shows that users relate to platformized GenAI in three distinct but related ways: (1) as a happy helper to organize and systematize knowledge and information; (2) as a creative tool to generate ideas; and (3) as a conversation partner for personal and life-related matters. In conclusion, we discuss the findings critically in relation to overall platform dynamics and the notion of systems ‘speaking back’ and further suggest that future research should aim to bring the two research fields of datafication and user studies even closer together.

Problem-based learning analysis in strengthening college students’ interpersonal communication skill

This study seeks to analyse the incorporation of problem-based learning (PBL) in strengthening students' interpersonal communication skills, as well as the level of proficiency of students' interpersonal communication skills and the obstacles they face in acquiring them. This study was a crosssectional survey conducted in May 2023 with 315 college students enrolled in six English Study Programs at six universities in three Indonesian provinces. The questionnaires and interviews were used for recording data, which was then analysed using Jeffreys's amazing statistics program (JASP). Based on the data collected, it can be shown that the interpersonal communication profiles of 315 participants can be classified as falling within the medium category (average score=3.26). The primary challenge encountered by participants in developing their interpersonal communication skills is attributed to difficulties arising from the accent of their conversation partner, as indicated by a mean score of 4.6. The result mandates that educators provide an appropriate and effective learning method. PBL is an effective alternative as its principles, syntax, implementation stages, orientation, and benefits are capable of helping students overcome interpersonal communication challenges. PBL model is intended to provide students with the skills needed for problem-solving, increasing logical thinking, collaboration, and communication.

Frankenstein's Monster in the Metaverse: User Interaction With Customized Virtual Agents.

Enabled by the latest achievements in artificial intelligence (AI), computer graphics as well as virtual, augmented, and mixed reality (VR/AR/MR), virtual agents are increasingly resembling humans in both their appearance and intelligent behavior. This results in enormous potential for agents to support users in their daily lives, for example in customer service, healthcare, education or the envisioned all-encompassing metaverse. Today's technology would allow users to customize their conversation partners in the metaverse - as opposed to reality - according to their preferences, potentially improving the user experience. On the other hand, there is little research on how reshaping the head of a communication partner might affect the immediate interaction with them. In this paper, we investigate the user requirements for and the effects of agent customization. In a two-stage user study ($N=30$), we collected both self-reported evaluations (e.g., intrinsic motivation) and interaction metrics (e.g., interaction duration and number of tried out items) for the process of agent customization itself as well as data on how users perceived the subsequent human-agent interaction in VR. Our results indicate that users only wish to have full customization for agents in their personal social circle, while for general services, a selection or even a definite assignment of pre-configured agents is sufficient. When customization is offered, attributes such as gender, clothing or hair are subjectively more relevant to users than facial features such as skin or eye color. Although the customization of human interaction partners is beyond our control, customization of virtual agents significantly increases perceived social presence as well as rapport and trust. Further findings on user motivation and agent diversity are discussed in the paper.

Communication behavior and space utilization of office workers in a research facility's activity‐based workplace

AbstractThis study explores the pre‐ and post‐renovation differences in communication behaviors of office workers at a construction company's research facility that had carried out renovations to promote open innovation through internal and external interactions. We conducted an analysis by combining both objective survey of conversation time, conversation partners, and stay location information using sensing terminals and subjective evaluations by office workers using a questionnaire survey. As the work style transitioned from fixed seats pre‐renovation to activity‐based working post‐renovation, the attendance rate analysis around each worker's personal workspace throughout the measurement period decreased from 74% to 60%, and the tendency to use various places in the office increased. Additionally, the number of conversation partners increased by 1.9 times on average and inter‐department conversation rate increased from 46% to 53% when activity‐based working was performed post‐renovation. However, while the introduction of activity‐based working significantly increased the level of communication satisfaction among workers in other departments, it tended to decrease the level of communication satisfaction within a department. This study maintains that organizational and operational efforts must sustain and promote intra‐departmental communication when activity‐based working is introduced and confirms that the introduction of activity‐based working was effective in promoting interaction between office workers.

Examining generative AI–mediated informal digital learning of English practices with social cognitive theory: a mixed-methods study

Abstract This study explores the integration of generative artificial intelligence (GenAI) in informal digital learning of English (IDLE) practices, focusing on its potential to enhance language learning outcomes and addressing the technological challenges language teachers face in utilising AI-based tools to facilitate second language acquisition. Based on the research context of IDLE and holistic learning ecology and drawing on the theoretical frameworks of technological pedagogical and content knowledge and social cognitive theory, we performed a mixed-methods investigation with an empirical experiment to assess the effectiveness of GenAI followed by semi-structured interviews. The results suggest that the GenAI-mediated IDLE practices effectively improve college students’ oral proficiency in English from both technological and humanistic perspectives. However, results also indicate that the GenAI conversational partner alone is not adequate to provoke continuous extramural GenAI-mediated IDLE practices. We discuss the theoretical and pragmatic significance of GenAI-mediated IDLE in educational equity and reformation.

Qualitative Analysis of Responses in Estimating Older Adults Cognitive Functioning in Spontaneous Speech: Comparison of Questions Asked by AI Agents and Humans.

Artificial Intelligence (AI) technology is gaining attention for its potential in cognitive function assessment and intervention. AI robots and agents can offer continuous dialogue with the elderly, helping to prevent social isolation and support cognitive health. Speech-based evaluation methods are promising as they reduce the burden on elderly participants. AI agents could replace human questioners, offering efficient and consistent assessments. However, existing research lacks sufficient comparisons of elderly speech content when interacting with AI versus human partners, and detailed analyses of factors like cognitive function levels and dialogue partner effects on speech elements such as proper nouns and fillers. This study investigates how elderly individuals' cognitive functions influence their communication patterns with both human and AI conversational partners. A total of 34 older people (12 men and 22 women) living in the community were selected from a silver human resource centre and day service centre in Tokyo. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), and participants engaged in semi-structured daily conversations with both human and AI partners. The study examined the frequency of fillers, proper nouns, and "listen back" in conversations with AI and humans. Results showed that participants used more fillers in human conversations, especially those with lower cognitive function. In contrast, proper nouns were used more in AI conversations, particularly by those with higher cognitive function. Participants also asked for explanations more often in AI conversations, especially those with lower cognitive function. These findings highlight differences in conversation patterns based on cognitive function and the conversation partner being either AI or human. These results suggest that there are differences in conversation patterns depending on the cognitive function of the participants and whether the conversation partner is a human or an AI. This study aims to provide new insights into the effective use of AI agents in dialogue with the elderly, contributing to the improvement of elderly welfare.

Motives and risks of self-disclosure to robots versus humans

The extent to which people self-disclose depends on the valence and intimacy of that information. We developed a 16-item measure that features both dimensions to assess participants’ inclination to self-disclose to humans and robots across three studies, i.e., the VISS scale. We hypothesized that participants would prefer a human over a robot conversation partner, independent of the valence and intimacy of the topic. Using the VISS, participants reported equal willingness to self-disclose to a human and a robot. However, in one out of three studies, participants were more willing to self-disclose positive topics that are low in intimacy (PTLI) to a fellow human, whereas in two out of three studies, they were less prone to self-disclose negative topics that are high in intimacy (NTHI) to a human compared to a robot. Two out of three studies provide a plausible explanation for these differences: participants indicated more motives to self-disclose PTLI to a human than to a robot, with relationship development being one central motive that was more strongly indicated in relation to a human. Furthermore, participants perceived more risks to self-disclose NTHI to a human than to a robot, with the risk of rejection being most prevalent for a human.

"Look Who's Talking": Language Patterns in Autistic and Non-Autistic Youth Across Different Conversation Partners.

Autistic individuals have varying levels of verbal fluency which can impact social outcomes. Although 70-75% of autistic individuals have functional language, findings regarding language patterns (syntax and semantics) in autistic adolescents remain inconclusive. Additionally, previous studies of language complexity use narrative samples, which do not capture autistic language in conversation. The current study examined language patterns in autistic (n = 20) and non-autistic (n = 17) youth aged 9-16 years during a conversation with a familiar versus unfamiliar adult. The study aimed to address gaps in the literature regarding autistic youth's language patterns, particularly in conversation, and the impact of speaking partners. Recordings of the conversation task were transcribed using SALT software conventions to yield measures of language production. Average length of communication units was higher among autistic compared to non-autistic youth, and among all youth when talking with familiar compared to unfamiliar partners. Youth speech also reflected greater linguistic diversity with familiar interlocutors, with no differences between autistic and non-autistic youth. Additionally, familiar interlocutors used more speech elicitation strategies (i.e., questions, prompts) than unfamiliar interlocutors across groups and interlocutors speaking with autistic youth used more speech elicitation strategies. These findings identify important similarities and differences between autistic and non-autistic youth and interlocutor speech that provide a better understanding of language patterns in autism. Importantly, this study can increase understanding and enhance support of autistic youth by highlighting that some aspects of autistic youth's language patterns in the context of conversation may be currently underestimated.

Self-views converge during enjoyable conversations

Based on current research, it is evident that the way people see themselves is shaped by their conversation partners. Historically, this literature focuses on how one individual's expectations can shape another person's self-views. Given the reciprocal nature of conversation, we wondered whether conversation partners' self-views may mutually evolve. Using four-person round-robin conversation networks, we found that participants tended to have more similar self-views post-conversation than pre-conversation, an effect we term "inter-self alignment." Further, the more two partners' self-views aligned, the more they enjoyed their conversation and were inclined to interact again. This effect depended on both conversation partners becoming aligned. These findings suggest that the way we see ourselves is coauthored in the act of dialogue and that as shared self-views develop, the desire to continue the conversation increases.

Phubbing responses in real-time: rapid recovery from a single phub and declining affect with repeated phubs

ABSTRACT People tend to feel negatively when they are ignored by a conversation partner attending to their phone (i.e. ‘phubbing’). We investigated how quickly people recover in an experiment where participants provided intensive real-time ratings of their mood during a simulated conversation with a partner who engaged in either no phubbing, a single phub, or repeated phubbing. Drawing on ostracism theories, we hypothesized and found that a single phub induces negative affect, d ≈ 0.40, and people begin recovering immediately. However, repeated phubbing causes increasingly negative affect, d ≈ 1.20, with a pattern of partial recovery between phubs. People quickly feel bad, but recover within seconds, unless repeated phubbing interrupts the recovery, and produces increasingly negative affect.

AI-CiciBot as Conversational Partners in EFL Education, focusing on Intelligent Technology Adoption (ITA) to Mollify Speaking Anxiety

This study examines the role of AI-CiciBot as a conversational partner in mitigating speaking anxiety among Indonesian EFL (English as a Foreign Language) students. The aim is to explore the integration of intelligent technology adoption (ITA) into classrooms to enhance language learning and reduce anxiety during speaking activities. The primary gap addressed in this research is the lack of technology-based solutions for oral language practice in Indonesia, where traditional curricula emphasize reading and writing over speaking. This study aims to fill the gap by introducing AI-CiciBot, a novel AI-powered conversational tool that provides a supportive, low-pressure environment for students to practice speaking English. The study uses a mixed-methods approach, combining quantitative data from pre-test and post-test scores and qualitative insights from student interviews. The research tools include a questionnaire and an AI-CiciBot platform for speaking practice. IBM SPSS Statistics analyzed the data, focusing on students' speaking performance and anxiety levels before and after using AI-CiciBot. Findings in this study show a significant improvement in students' speaking skills and a reduction in anxiety. The mean score for pre-tests was 49.17, which increased to 90.47 in post-tests, indicating AI-CiciBot's effectiveness. Interviews revealed that students initially hesitant to engage in speaking activities due to fear of judgment became more confident and willing to participate after practicing with the AI bot. This study contributes to the field of EFL education by demonstrating the potential of AI-driven tools like AI-CiciBot to address speaking anxiety and improve oral proficiency. It also highlights the importance of ITA in encouraging students to embrace AI-based learning solutions. To maximize learning outcomes, future research should investigate the long-term impact of AI-CiciBot on students' speaking proficiency and its integration with human instructors.

Maksim Percakapan dalam Program Acara I-Talk di Insert Live

This study aims to describe the form and function of conversational maxims in the I-Talk program on Insert Live. The inappropriateness of the speaker's speech in responding to the presenter's speech and the lack of communication strategies carried out by the presenter in talking to the speaker are the background for the researcher to choose the speech between Maria Christy and Amanda Caesa in the I-Talk program to be studied. This study uses a descriptive research type with a qualitative approach, because it can explain simply and clearly based on the focus of the study. The data in this study are the speech between Maria Christy and Amanda Caesa in the I-Talk program on Insert Live which contain conversational maxims, and the data sources are obtained from the I-Talk program on the Insert Live platform. The data collection technique in this study uses the free listening technique and the note-taking technique. The data analysis technique in this study uses data reduction, data presentation, and conclusion drawing techniques. The results of this study are the form and function of conversational maxims in the I-Talk program. The forms of conversational maxims found are the maxim of quantity, the maxim of quality, the maxim of relevance, and the maxim of implementation. The conversational maxim functions found are assertive, directive, and expressive functions. The maxim of quantity is the most frequently found in this study, because Maria Christy and Amanda Caesa provide informative speech or information and do not exceed what is needed. The assertive function is the most frequently found in this study, because Maria Christy and Amanda Caesa provide speech that functions to state, ask, and explain as an effective communication strategy between speakers and conversation partners in the I-Talk event on Insert Live.

AI in the L2 Classroom: Serving Language Educators through Professional Development

The spread of generative AI has been praised and criticized for engendering new possibilities and limitations for language education. While educators have praised AI’s ability to serve as a conversation partner, generate novel ideas for lesson plans, and offer tailored feedback, many instructors and scholars have voiced concerns related to AI’s biases and its impact on student learning and academic integrity. Responding to a need for further training and dialogue about AI, members of the Davis Language Center organized a professional development event in which instructors, students, and instructional technologists shared their perspectives and strategies for AI-mediated language education. The event also included guided practice on using these tools for pedagogical purposes, including writing effective prompts, interacting with AI tools, and engaging in an iterative, reflective process. Through our planning process, we discovered that balancing scheduled asynchronous tasks with focused synchronous check-ins was crucial for ensuring accountability, clear communication, and timely progress, ultimately helping us coordinate and achieve our event planning goals effectively. We report on insights from organizing and participating in the event, highlighting several advantages of using AI in language education, critical issues, and questions for further inquiry. Leveraging lessons learned at this event, we offer suggestions for coordinating trainings about AI-enhanced language education.

Urologist communication is a primary factor leading to erectile dysfunction treatment postprostatectomy.

Studies have shown insufficient utilization of care for patients with erectile dysfunction (ED) after radical prostatectomy (RP). The aim of this study was to evaluate variables associated with barriers to seeking and receiving ED treatment. In this multicenter prospective cross-sectional study, the functional outcomes of 936 patients were assessed 10 to 15years after RP. A total of 525 patients with ED or incontinence were asked about their treatment experiences or lack thereof. The data were analyzed using the chi-square test, t test, and multivariate logistic analyses. Patients answered validated questionnaires regarding information sources, communication with their partner and urologist, and barriers to ED treatment. Of the 525 patients, 80 were not available to survey. A total of 304 patients answered the survey (response: 68.0%). A total of 246 patients had ED and were included in this study. The mean age at surgery was 64.4 ± 6.1years, and the mean age at the time of this survey was 77.1 ± 6.2years. The mean follow-up duration was 12.7 ± 1.5years. Forty-six percent (n = 114 of 246) of the patients had never received ED treatment. The most important conversation partners regarding the ED were the partner (69% [n = 169 of 246]) and the urologist (48% [n = 118 of 246]). Patients who never received ED treatment were less likely to have conversations with their urologist (34% vs 60%; P < .001), had less support (51% vs 68%; P = .01), and had less interest in sex from their partner (20% vs 40%; P = .001). Communication with other groups (general practitioners, other physicians, family, friends, and the Internet) had no influence on ED treatment utilization. The most relevant barrier to receiving ED treatment was the belief that treatment would not help (65%). No interest in sex from their partner (odds ratio, 3.9) and no conversation with their urologist about ED (odds ratio, 2.9) were found to be independent predictors of not receiving ED treatment. Urologists should have enhanced awareness of how to approach patients directly about their ED and actively offer them treatment options. These results should be further validated in a multicenter, prospective study. Response bias may have affected the results. Furthermore, the current cohort was relatively old. This study revealed that no interest in sex from one's partner and insufficient communication with a urologist were relevant barriers to insufficient utilization of ED treatment after RP.

Fear of positive evaluation and social affiliation in social anxiety disorder and major depression

Fear of positive evaluation (FPE) is posited as a core feature of social anxiety disorder (SAD); however, little is known about its role in interpersonal functioning. We examined relationships between FPE and responses to a standardized social affiliation paradigm designed to facilitate positive social connection with an unacquainted conversation partner (trained confederate). The sample included adults with SAD (N = 52), major depressive disorder (MDD; N = 23), comorbid SAD and MDD (N = 36), and non-psychiatric controls (N = 33). Participants completed measures assessing FPE, affect, safety behaviors, and desire for future interaction. Confederates and observers rated participant behavior and their own desire for future interaction. FPE was most elevated in the SAD and comorbid groups, followed by the MDD group, and then non-psychiatric controls. In the full sample, FPE was associated with greater self-reported anxiety and safety behavior use, lower self-reported positive affect and desire for future interaction, lower observer-rated desire for future interaction and approach behaviors, and greater observer-rated anxious behaviors. Within-group correlations revealed that associations were weaker in the SAD only and comorbid groups (cf. control and MDD only groups); however, post-hoc moderation analyses indicated that the relationships between FPE and the outcomes of interest largely held across varying levels of social anxiety and depression severity. Findings underscore the potential role of FPE as a transdiagnostic factor relevant to understanding interpersonal functioning in social anxiety and depression.

Fast frequency modulation is encoded according to the listener expectations in the human subcortical auditory pathway

Abstract Expectations aid and bias our perception. For instance, expected words are easier to recognise than unexpected words, particularly in noisy environments, and incorrect expectations can make us misunderstand our conversational partner. Expectations are combined with the output from the sensory pathways to form representations of auditory objects in the cerebral cortex. Previous literature has shown that expectations propagate further down to subcortical stations during the encoding of static pure tones. However, it is unclear whether expectations also drive the subcortical encoding of subtle dynamic elements of the acoustic signal that are not represented in the tonotopic axis. Here, we tested the hypothesis that subjective expectations drive the encoding of fast frequency modulation (FM) in the human subcortical auditory pathway. We used fMRI to measure neural responses in the human auditory midbrain (inferior colliculus) and thalamus (medial geniculate body). Participants listened to sequences of FM-sweeps for which they held different expectations based on the task instructions. We found robust evidence that the responses in auditory midbrain and thalamus encode the difference between the acoustic input and the subjective expectations of the listener. The results indicate that FM-sweeps are already encoded at the level of the human auditory midbrain and that encoding is mainly driven by subjective expectations. We conclude that the subcortical auditory pathway is integrated in the cortical network of predictive processing and that expectations are used to optimise the encoding of fast dynamic elements of the acoustic signal.

LLaVA-docent: Instruction tuning with multimodal large language model to support art appreciation education

Despite the development of various AI systems to support learning in various domains, AI assistance for art appreciation education has not been extensively explored. Art appreciation, often perceived as an unfamiliar and challenging endeavor for most students, can be more accessible with a generative AI enabled conversation partner that provides tailored questions and encourages the audience to deeply appreciate artwork. This study explores the application of multimodal large language models (MLLMs) in art appreciation education, with a focus on developing LLaVA-Docent, a model designed to serve as a personal tutor for art appreciation. Our approach involved design and development research, focusing on iterative enhancement to design and develop the application to produce a functional MLLM-enabled chatbot along with a data design framework for art appreciation education. To that end, we established a virtual dialogue dataset that was generated by GPT-4, which was instrumental in training our MLLM, LLaVA-Docent. The performance of LLaVA-Docent was evaluated by benchmarking it against alternative settings and revealed its distinct strengths and weaknesses. Our findings highlight the efficacy of the MMLM-based personalized art appreciation chatbot and demonstrate its applicability for a novel approach in which art appreciation is taught and experienced.

Parents of Children with Disabilities: Strengths and Frailty of Human Faith Journeys

Although studies have been conducted regarding the faith journeys of people with disabilities, little is known of those nurturing and accompanying them, their parents. The faith journeys of parents of children with disabilities are a critical yet underattended source of theological insight. In this qualitative research study, we interview and study the perspective of seven married parents of children with disabilities who actively participate in ministry at their local faith communities or a national arena. While these criteria limit the number of parents caring for children with disability, they gave us greater insight into the challenges and graces received throughout their faith journeys, the role of their immediate family, their faith communities, and the universal Church. Five emerging themes were identified reflecting the rich yet complex strengths and frailty of their faith journeys. This study intends to amplify the stories of parents of children with disabilities becoming key conversation partners. Their hope-in-tension narratives inform and challenge the understanding of Christian anthropology, the centrality of faith, and the vocation of marriage, and in turn lead to concrete pastoral recommendations in three critical dimensions: ecclesiological, catechetical, and ministerial.

Estimation of the Cognitive Functioning of the Elderly by AI Agents: A Comparative Analysis of the Effects of the Psychological Burden of Intervention.

In recent years, an increasing number of studies have begun to use conversational data in spontaneous speech to estimate cognitive function in older people. The targets of spontaneous speech with older people used to be physicians and licensed psychologists, but it is now possible to have conversations with fully automatic AI agents. However, it has not yet been clarified what difference there is in conversational communication with older people when the examiner is a human or an AI agent. This study explored the psychological burden experienced by elderly participants during cognitive function assessments, comparing interactions with human and AI conversational partners. Thirty-four participants, averaging 78.71 years of age, were evaluated using the Mini-Mental State Examination (MMSE), the Visual Analogue Scale (VAS), and the State-Trait Anxiety Inventory (STAI). The objective was to assess the psychological impact of different conversational formats on the participants. The results indicated that the mental strain, as measured by VAS and STAI scores, was significantly higher during the MMSE sessions compared to other conversational interactions (p < 0.01). Notably, there was no significant difference in the mental burden between conversations with humans and AI agents, suggesting that AI-based systems could be as effective as human interaction in cognitive assessments.

Influence of Positive/Negative Emotions Towards Autobiographical Memories on Impressions of the Conversation and Conversation Partner During Nostalgic Memory Sharing

ABSTRACTWe investigated the effects of positive/negative emotions towards autobiographical memories on impressions of the conversation and conversation partner during memory sharing in a reminiscence therapy setting. Fifty‐six older (Mage = 69.3) and 60 younger (Mage = 20.7) participants' net emotional tendency (positive/negative) towards autobiographical memories and depressive symptoms were evaluated using validated rating scales. Positive/positive and positive/negative age‐matched random pairs shared a nostalgic memory through free conversation. Participants with a negative emotional tendency towards autobiographical memories in positive/negative pairs tended to feel less “easy” about the conversation. Participants with a positive emotional tendency towards autobiographical memories in positive/negative pairs had a more negative impression of their partners. Our data provide insight into the relationship between net emotional tendency towards autobiographical memories and depression and suggest that an individual's net emotional tendency towards autobiographical memories potentially affects the outcome of group reminiscence therapy.