Quality Of Interaction Research Articles

Investigating students’ programming behaviors, interaction qualities and perceptions through prompt-based learning in ChatGPT

ChatGPT has proven to facilitate computer programming tasks through the strategic use of prompts, which effectively steer the interaction with the language model towards eliciting relevant information. However, the impact of specifically designed prompts on programming learning outcomes has not been rigorously examined through empirical research. This study adopted a quasi-experimental framework to investigate the differential effects of prompt-based learning (PbL) versus unprompted learning (UL) conditions on the programming behaviors, interaction qualities, and perceptions of college students. The study sample consisted of 30 college students who were randomly assigned to two groups. A mixed-methods approach was employed to gather multi-faceted data. Results revealed notable distinctions between the two learning conditions. First, the PbL group students frequently engaged in coding with Python and employed debugging strategies to verify their work, whereas their UL counterparts typically transferred Python code from PyCharm into ChatGPT and posed new questions within ChatGPT. Second, PbL participants were inclined to formulate more complex queries independently, prompted by the guiding questions, and consequently received more precise feedback from ChatGPT compared to the UL group. UL students tended to participate in more superficial-level interactions with ChatGPT, yet they also obtained accurate feedback. Third, there were noticeable differences in perception observed before and after the ChatGPT implementation, UL group reported a more favorable perception in the perceived ease of use in the pre-test, while the PbL group experienced an improvement in their mean scores for perceived usefulness, ease of use, behavioral intention to utilize, and a significant difference regarding the attitude towards utilizing ChatGPT. Specifically, the use of structured output and delimiters enhanced learners’ understanding of problem-solving steps and made learning more efficient with ChatGPT. Drawing on these outcomes, the study offers recommendations for the incorporation of ChatGPT into future instructional designs, highlighting the structured prompting benefits in enhancing programming learning experience.

The Impact of AI Techniques on Human-AI Interaction Quality in Project Management: A Mixed-Methods Study

Artificial intelligence (AI) is changing how organizations work through its integration with project management. This study looks at how AI approaches affect the quality of human-AI interaction in project management settings. The main research issue focuses on figuring out how various AI approaches affect the quality of interactions. A mixed-methods approach was used in the study, integrating qualitative case studies with quantitative questionnaires. Forty-five (45) respondents, comprising project managers and developers from various organizations in Lagos State, Nigeria, were among the participants. While qualitative interviews probed participant experiences, quantitative data offered numerical insights. It was revealed that image-based AI increases engagement by providing visual signals, while speech-based AI improves social presence and trust. Additionally, performance, communication, and trust are all related. This implies that open communication promotes trust, which influences the project's success. By being transparent and adapting AI implementation to the specifics of each project, project managers and AI engineers can foster confidence and regularly assess the efficacy of AI.

Penerapan 3Magic Words Melalui Bimbingan Kelompok Metode Sosiodrama Untuk Meningkatkan Interaksi Sosial

This research aims to increase students' social interactions through the application of 3 Magic Words ("sorry," "please," "thank you") in group guidance using the sociodrama method. The research subjects were six class X APHP students at SMKN 3 Madiun in the odd semester 2024-2025. Using a Counseling Guidance Action Research approach with qualitative descriptive methods, the research results show an increase in the use of 3 Magic Words after implementing sociodrama. In the first cycle, although students were still awkward, there was improvement. In the second cycle, more complex scenarios made the use of the 3 Magic Words more consistent, creating a more harmonious and collaborative classroom atmosphere. Sociodrama has proven to be effective in encouraging the use of the 3 Magic Words, which ultimately improves the quality of social interactions.

Blended Learning to Enhance Productive Skills

Blended learning, an educational strategy that blends traditional face-to-face teaching with online learning components, provides a dynamic way to improve productive skills like speaking and writing. This hybrid model takes advantage of the qualities of both in-person interactions and digital resources, allowing students to benefit from the rapid feedback and personal engagement of classroom settings while having access to various flexible online tools. Blended learning promotes more personalized and effective communication skill development by incorporating interactive digital platforms, virtual practice opportunities, and automated feedback mechanisms. This technique fits various learning styles and paces and gives a more comprehensive, adaptable educational experience. Finally, blended learning fosters enhanced mastery of productive skills, giving learners the confidence and aptitude to communicate in varied circumstances successfully.

Quality control for single-cell analysis of high-plex tissue profiles using CyLinter.

Tumors are complex assemblies of cellular and acellular structures patterned on spatial scales from microns to centimeters. Study of these assemblies has advanced dramatically with the introduction of high-plex spatial profiling. Image-based profiling methods reveal the intensities and spatial distributions of 20-100 proteins at subcellular resolution in 103-107 cells per specimen. Despite extensive work on methods for extracting single-cell data from these images, all tissue images contain artifacts such as folds, debris, antibody aggregates, optical aberrations and image processing errors that arise from imperfections in specimen preparation, data acquisition, image assembly and feature extraction. Here we show that these artifacts dramatically impact single-cell data analysis, obscuring meaningful biological interpretation. We describe an interactive quality control software tool, CyLinter, that identifies and removes data associated with imaging artifacts. CyLinter greatly improves single-cell analysis, especially for archival specimens sectioned many years before data collection, such as those from clinical trials.

Design and development of an ai-driven communication model for stimulating memory recall in patients with Alzheimer’s and other neurodegenerative diseases

This study presents the development and evaluation of an AI-driven communication tool designed to stimulate memory recall in patients with Alzheimer’s disease and other neurodegenerative disorders. The tool integrates machine learning algorithms, including Random Forest and Long Short-Term Memory (LSTM) networks, with mass communication theories to deliver personalized and adaptive communication strategies. The AI models were trained and tested on patient interaction data, enabling the tool to dynamically adjust its prompts based on real-time cognitive states. Performance metrics such as accuracy, precision, and AUC-ROC were used to assess model efficacy, with the Random Forest model achieving the highest performance across all metrics. Clinical trials demonstrated significant improvements in memory recall and emotional engagement in patients using the AI tool compared to standard cognitive stimulation therapy. Caregivers also reported higher satisfaction with the tool's usability and impact on patient interaction quality. These findings highlight the potential of AI-driven, personalized communication tools to revolutionize Alzheimer's care, offering scalable, adaptive interventions that improve cognitive and emotional health. Academically, this work advances the integration of AI and health communication, emphasizing culturally sensitive and patient-centered approaches. In healthcare, it presents a promising non-pharmacological intervention that can be easily scaled for widespread use, potentially reducing caregiver burden and improving patient outcomes.

A Meta-Analytic Review of Personality and Teacher-Student Relationships.

This meta-analysis provides the first comprehensive synthesis of associations between student and teacher personality traits and the quality of teacher-student relationships. Fifty-five studies met the eligibility criteria, contributing a total of 238 effect sizes. We used multivariate meta-analysis with robust variance estimation (RVE) to model the dependency of effect sizes. Student prosocial behavior (ρ = 0.59) and proactive personality (ρ = 0.48) were the strongest predictors of positive teacher-student relationship quality. All Big Five traits of students, except neuroticism, showed significant positive associations, with all correlations exceeding 0.4 when holding constant with all other moderators. Teacher agreeableness (ρ = 0.31) and conscientiousness (ρ = 0.29) yielded modest associations. Students with less emotional stability or aggressive behaviors were more likely to experience negative teacher-student relationships, such as conflict and dependency. Our findings highlight the critical role of student personality in explaining the quality of teacher-student interactions. Multiple traits appear equally important, as indicated by comparable effect sizes. The literature is relatively limited when it comes to teacher personality. We were unable to examine teacher traits in relation to teacher-student conflict and dependency, but, overall, agreeable and conscientious teacher behaviors appeared to be important for favorable interactions, whereas teacher neuroticism may undermine the quality of such interactions.

A Study of Factors That Affect Chinese Tertiary EFL Learners’ Willingness to Communicate in Class

Classroom interaction characterizes communicative language teaching. Effective classroom interaction promotes second language acquisition (SLA) and serves as an important means of using the language especially for students in a foreign language context. Willingness to communicate (WTC) has received constant attention since its application to the SLA field in the 1990s. Students’ WTC ensures the quantity and quality of classroom interaction. By analyzing the data from an end-of-year questionnaire in an ordinary Chinese college English class, the present study aims to examine Chinese non-English major students’ general attitudes towards classroom communication activities and two major categories of factors, namely Teacher Factors and Task Factors, that influence students’ WTC in English classes from students’ perspective. The results show that the factors affecting WTC in college English classrooms are multidimensional, with Teacher’ s Emotions (being patient, encouraging, guiding, positive, happy, lively, passionate, trust), Teacher’ s Professional qualities (content selection, class organization, pronunciation, wait-time) and Task Content (usefulness, degree of difficulty, interest) having relatively greater effects. At the end of the paper, direction for future research is given. Second/foreign language teachers are advised to conduct further classroom research and actively regulate these factors for a more interactive English class and thus improve students’ class participation and learning efficiency.

The Service Experience Equity on Repatronage Intention within Public Transportation Services

In a highly competitive market, service providers are often expected to enhance their profitability by delivering superior service quality. This principle is evident among many public transportation providers in Malaysia, who strive to elevate the passenger experience through refined service offerings. The objective of this study is to examine the factors influencing repatronage intentions among public transportation users in Malacca, Malaysia, using the Service Experience Equity (SEE) framework. To demonstrate the causal connections between the variables, a regression analysis has been employed. The findings reveal that service atmosphere and personnel interactions significantly impact users' willingness to continue using these services. The study emphasizes the importance for management to prioritize customer experience by investing in service environment strategies that foster user engagement and discourage customer churn. It further underscores that both the overall service experience and the quality of employee-customer interactions are critical determinants of future patronage. Consequently, it is recommended that transportation service providers leverage these elements to create a competitive edge, thereby encouraging repeat usage and building long-term customer loyalty.

Starting Right, an evidence-based assessment of children in municipalities healthcare centers

Abstract During the last century, children’s health has evolved significantly, with mental health issues becoming a prominent public health concern. Childhood health problems profoundly impact quality of life (QoL), development, school functioning, and social interactions, affecting society broadly. In Norway, child and school health services offer free comprehensive care within the municipal primary health care system, prioritizing health promotion and prevention to address social health inequalities. The Norwegian Starting RightTM project recruits’ children aged 6 months to16 years and their parents, emphasizing early intervention and support to reduce health inequalities and promote well-being. In the Starting RightTM project, online proxy- and child-reported questionnaires are used to support public health nurses (PHNs) in assessing children’s health and development in routine follow- up. Parents and children receive an SMS text message asking them to answer an online questionnaire before attending their regular appointments in child or school health services. Validated instruments measure the development (ASQ, ASQ-SE), mental health (SDQ) and health-related quality of life (HRQoL), (KIDSCREEN -27). By mapping children and adolescents’ health and through discussions with PHNs, parents and children may be more involved in children’s health and development and may increase their Health Literacy. The primary objective of the proposed project is to develop child and school health services and improve children’s health and HRQoL. The ongoing project is the first to systematically assess development, health and HRQoL in children and adolescents in Norway through ordinary services, and to do so longitudinally. At present, >2000 children have been included. The large sample size combined with a broad multi- and interdisciplinary approach is unique from a national perspective. The upcoming workshop will showcase findings from this innovative study.

Technoference in infant feeding: the impact of maternal digital media use during breastfeeding on maternal attention and mother-infant interactions

IntroductionParents' sensitivity and responsiveness to their infants may be affected by the widespread availability and use of mobile devices. The present study examined the impact of maternal digital media use on maternal attention and the quality of mother-infant interaction during breastfeeding.MethodsMothers and infants (n = 25 dyads) participated in a within-subject experiment. Mothers breastfed their infants under one experimental and one control condition, counterbalanced across two laboratory visits. During the Digital Media condition, mothers watched a television show on a tablet. During the Control condition, mothers listened to classical music at ambient levels. Video records were later coded to assess maternal attention to the infant, tablet, or elsewhere and evaluate the quality of mother-infant interaction.ResultsThere were more disruptions in maternal attention to the infant during the Digital Media (M = 3.7, S.E. = 0.2 per minute) vs. Control condition (M = 1.7, S.E. = 0.2 per minute, p < 0.001). The proportion of the meal duration mothers spent focused on their infant was significantly lower during the Digital Media (M = 52.5%, S.E. = 3.9) vs. Control condition (M = 83.9%, S.E. = 4.0%, p < 0.001). Lower maternal attention to the infant was associated with lower maternal sensitivity to cues (p = 0.03) and cognitive growth fostering (p = 0.002), as well as lower infant clarity of cues (p = 0.001). Lower maternal attention was also associated with less socioemotional growth fostering (p < 0.001) and lower infant responsiveness to the mother (p < 0.001) regardless of whether digital media was present or absent, but during the Digital Media condition, mothers engaged in more socioemotional growth fostering (p = 0.004) and infants were more responsive to mothers (p = 0.03).DiscussionThe presence of digital media during infant feeding led to more interruptions to mothers' attention to their infants and the time mothers spent focused on digital media displaced time spent focused on their infants. The degree to which mothers were attentive to their infants vs. digital media was a more important predictor of most aspects of interaction quality than the mere presence of digital media.

Study on the Design of a Non-Contact Interaction System Using Gestures: Framework and Case Study

The interaction patterns are constantly changing as the rapid development in technology. The non-contact interaction system using gestures is becoming important in human-computer interaction nowadays. This paper illustrates a design framework of a non-contact interaction system using gestures, which fully considers the approach to fit non-contact gestures into the system. The corresponding user requirements were investigated by surveys, and the universal design guide of non-contact gestures was summarized by statistical analysis. A case study was illustrated for key points of the developed design framework. The scheme, including interaction architecture, gesture definition, and user interface design, was described. The rapid prototyping was built. Evaluations, including eye-tracking measurements and tests of system usability, were implemented and analyzed by statistical methods to present suggestions of iterative design. The feasibility of the developed framework was verified. By statistical methods, the relationship between the interaction usability and the user’s perception for information was discussed, and the user’s perception for the display of dynamic and static gestures was analyzed. The results provide a clear approach to satisfy user’s preferences and improve the interaction quality for non-contact interaction systems using gestures, and furnish empirical grounding for sustainably devising similar interaction systems.

Black Caregiver Perspectives During a Developmental Diagnostic Interview.

Despite increasing autism prevalence rates across racial and ethnic groups, research has traditionally overlooked the influence of culture on developmental diagnostic conversations. Addressing this gap in research is crucial to understanding and mitigating potential disparities in diagnostic experiences, especially among Black caregivers. Black caregivers encounter frustration and discrimination during the diagnostic process, citing dismissiveness and a lack of cultural competence from healthcare providers. To address these issues, this study centers the perspectives of Black caregivers as they participate in a developmental diagnostic program for toddlers under three years of age. This retrospective qualitative study, conducted exclusively by a Black research team, involved nineteen Black caregivers of thirteen toddlers as they participated in semi-structured interviews conducted by a multidisciplinary clinical team. The research team employed a conceptual content analysis to examine caregivers' descriptions of their children's behaviors and characteristics, as well as the factors and experiences associated with their descriptions. Caregivers provided distinct descriptions of behaviors and characteristics in the categories of language and communication, learning, and temperament, associating them with situational and dispositional factors and experiences. The findings offer valuable insights for implementing culturally responsive diagnostic practices. Additionally, these results may enhance the quality of caregiver-provider interactions during developmental assessment, leading to earlier and more accurate diagnoses for Black children.

Redefining Teacher-Student Interaction in the Digital Era: A Case Study of Hybrid Learning Models in Primary Education

This study aims to explore the dynamics of teacher-student interactions in the context of hybrid learning in elementary schools. Data were collected through classroom observations, interviews with teachers, and analysis of digital platforms used through a case study approach. Findings indicate that although digital technology provides flexibility in time and space and a variety of interactive tools, student engagement in online sessions tends to be low. Non-verbal communication is also limited, affecting the quality of interpersonal interactions. Digital literacy is key; teachers who can utilize technology well can improve student interaction and engagement, and the challenge of unequal access to technology widens the gap in learning. The implications of this study emphasize the need to improve digital literacy for teachers and students, as well as solutions to overcome technological barriers to support effective hybrid learning in the future.

Affective Engagement with Metaphor in Introductory Statistics Education

Metaphor is a popular pedagogical tool to help learners understand unfamiliar concepts, but its affective and interactional qualities remain underexplored compared to its cognitive benefits. This study investigates how metaphor may enhance affective engagement within introductory statistics education for linguistics students. As previous research tends to rely on delayed and self-reported data, this study employs a mixed-methods approach that combines real-time physiological measures of engagement with feedback through surveys and interviews. It compares metaphorical and literal instructional styles for teaching simple linear regression, focusing on: i) differences in teacher and learner skin conductance levels, ii) teacher-learner synchrony through skin conductance concordance, iii) the relationship between physiological measures and affect-related survey responses, and iv) learner reflections on their experiences. Results show that the metaphorical style is associated with higher engagement levels and stronger teacher-learner synchrony, affirming the role of metaphors in enhancing collaborative learning when elaborated over time in spontaneous interactive fashion. However, the qualitative data reveal nuanced learner perceptions, highlighting the importance of clearly communicating the scope of metaphor use. This study contributes to understanding the interplay between affective and cognitive engagement in metaphorical learning, offering practical recommendations for its effective implementation in complex subjects like statistics.

Strategi Manajemen Konflik Dalam Meningkatkan Kinerja Dosen Di Perguruan Tinggi

This study aims to analyze effective conflict management strategies in improving the performance of lecturers in higher education. Workplace conflicts often affect productivity, teaching quality, and job satisfaction among lecturers. Using a descriptive qualitative approach, this research examines how strategies such as mediation, open communication, and collaboration can create a conducive working environment. Data were collected through in-depth interviews with lecturers and university leaders, as well as observations and document analysis. Data analysis was conducted using triangulation. The results show that effective conflict management strategies can improve lecturer productivity, enhance the quality of peer interactions, and foster workplace innovation. Well-managed conflicts not only reduce tension but also increase job satisfaction and motivation.

Trusting robots: a relational trust definition based on human intentionality

As robots are increasingly found in various aspects of human life, understanding how humans relate to and interact with robots is becoming more relevant. One important factor affecting the quality of human-robot interactions is trust, and in recent years there has been an increase in scientific interest in the nature of trust between humans and robots. However, it can be observed that a clear distinction between trust and its related constructs is not always made when examining trust in robots. To overcome these limitations, we propose a definition of trust in robots that clearly separates trust from its related constructs. To this end, we extend an established trust model for interpersonal trust, which we adapt to describe trust in HRI. The new definition describes trust as a particular way in which human trustor relates to a robot. By characterizing trust as an asymmetric relation with certain properties, the proposed definition adopts a perspective that focuses on the human trustor in describing trust. Furthermore, we argue that the proposed definition of trust is suitable for describing trust in all types of robots and for any form of human-robot interaction.

Perceived quality of parent-child interaction in parents of autistic children: relationship with parental education level.

Most autism research was conducted in Western, Educated, Industrialised, Rich and Democratic (WEIRD) countries. This study is the first to examine factors that were associated with perceived quality of parent-child interaction in non-WEIRD parents of autistic children. Ninety-one Chinese parents of autistic children (82 females, 9 males) completed an online survey which involved two sections. The first section included demographics questions about the parent and the family, including age, gender, educational level, and household income. It also assessed parents' perceived quality of parent-child interaction and their autistic traits. The second section included demographics questions about their autistic child, including age and gender, and assessed autistic traits and behavioural problems. Parent's education level was associated with and the only predictor of their perceived quality of parent-child interaction. The higher educational level in parents the higher quality of parent-child interaction was perceived by the parents. These findings underscored the significance of parents' education level as a unique predictor of perceived parent-child interaction quality among Chinese parents of autistic children, providing implications to corresponding education and social policies in China and other non-WEIRD countries.

Adverse Childhood Experiences in Parental History and how they Relate to Subsequent Observed Parent–Child Interaction: A Systematic Review

Abstract Background Adverse childhood experiences (ACEs) in parental history have been associated with higher self-reported rates of negative parenting behaviors and lower self-reported rates of positive parenting behaviors. Further research is needed to explore the association between parental ACEs and the observed parent–child interaction quality. Parent–child interactions are a potential pathway behind the continuity of ACEs across generations. Objective This review aimed to expand on existing literature by synthesizing evidence on the associations between parental ACEs and parent–child interactions, assessed through videotaped observations, the gold standard for interaction assessment. Methods A systematic literature search conducted in October 2022 in Medline, EMBASE, and PsycInfo identified twenty-four articles. The studies assessed parental childhood adversity and the quality of parent–child interaction across high- and low-risk samples. Results In 79% of studies, higher rates of childhood adversity were related to lower quality of observed parent–child interaction. Childhood abuse and neglect were linked to fewer positive and more negative parenting behaviors. Among household challenges, only witnessing family violence negatively impacted interaction quality. In 58% of studies, ACEs directly influenced interaction, while in 21% this effect was mediated by other factors. This pattern held across different sample types. Conclusions The evidence suggesting a relationship between parental ACEs and lower quality of parent–child interaction is robust, given the reliability and validity of observational measures. Considering the influence of the quality of parent–child interaction on a child’s development, interventions and prevention programs focusing on parent–child interaction should consider screening for parental ACEs.

Exploring the mechanism of sustained consumer trust in AI chatbots after service failures: a perspective based on attribution and CASA theories

In recent years, artificial intelligence (AI) technology has been widely employed in brand customer service. However, the inherent limitations of computer-generated natural language content occasionally lead to failures in human-computer interactions, potentially damaging a company’s brand image. Therefore, it is crucial to explore how to maintain consumer trust after AI chatbots fail to provide successful service. This study constructs a model to examine the impact of social interaction cues and anthropomorphic factors on users’ sustained trust by integrating the Computers As Social Actors (CASA) theory with attribution theory. An empirical analysis of 462 survey responses reveals that CASA factors (perceived anthropomorphic characteristics, perceived empathic abilities, and perceived interaction quality) can effectively enhance user trust in AI customer service following interaction failures. This process of sustaining trust is mediated through different attributions of failure. Furthermore, AI anxiety, as a cognitive characteristic of users, not only negatively impacts sustained trust but also significantly moderates the effect of internal attributions on sustained trust. These findings expand the research domain of human-computer interaction and provide insights for the practical development of AI chatbots in communication and customer service fields.