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Drawing parallels from the TV series Suits, this paper investigates the role of emotional intelligence (EQ) in fostering positive workplace culture, specifically within academic libraries. While the high-octane world of corporate law might seem disparate from the calm corridors of academic libraries, the interpersonal dynamics and challenges faced are strikingly similar. Central to this discussion is the recurring motif in Suits: the power of dialogue. Through characters like Harvey Specter and Donna Paulsen, the show emphasizes that open communication can be the key to resolution, even in high-pressure environments. Moreover, with the introduction of "The Donna," a unique AI tool, Suits provides a lens to examine the interplay between technology and EQ, raising questions about the true essence of human communication and its irreplaceability. This paper explores these themes, offering practical strategies for academic libraries to bolster EQ, enhance user experience, and ensure technology complements, rather than replaces, genuine human interaction. [ABSTRACT FROM AUTHOR]

Grounded theory is a widely used scientific method for generating theories from qualitative data analysis. However, it is often time-consuming and requires professional training. Generative artificial intelligence, such as ChatGPT, excels in understanding and analyzing text, making it a valuable tool for qualitative research. This research proposes a novel approach to guide ChatGPT using the grounded theory method for qualitative data analysis and to design rigorous metrics for evaluating its performance. Using risk analysis as a case study, we compare ChatGPT's results with those obtained through manual methods. Our findings show that, with expert guidance, ChatGPT can effectively perform the grounded theory method, achieving results comparable to those of human analysts. To maximize its potential, researchers should properly guide ChatGPT in performing required tasks, rigorously evaluate its outputs, and ensure high-quality results. This approach can significantly enhance the efficiency and quality of qualitative data analysis. [ABSTRACT FROM AUTHOR]

ChatGPT and generative artificial intelligence (Gen-AI) are transforming firms and supply chains. However, the empirical literature reporting the benefits, challenges, and outlook of these nascent technologies in operations and supply chain management (OSCM) is limited. This study surveys current projects and perceptions of these technologies in US (n = 119) and UK (n = 181) supply chains. We found that projects range from proof-of-concept to full implementation, with a main focus on operational gains, such as improved customer satisfaction, cost minimisation, and process efficiencies. The main challenges concern data, technological and organisational issues. Expected benefits are dominated by cost savings and enhanced customer experience, but also include increased automation and sustainability. Industries were found to cluster around six groups according to perceived benefits and implementation challenges. Our findings contribute to the emerging literature on Gen-AI use in OSCM, and to management practice by mapping the benefits, challenges, outlook, and maturity level of Gen-AI projects in supply chains. [ABSTRACT FROM AUTHOR]

In this article, we provide a brief overview of generative artificial intelligence (GenAI) and large language models (LLMs). We then propose eight critical questions that libraries should ask when exploring this technology and its implications for their communities. We argue that libraries have a unique role in facilitating informed and responsible use of GenAI, as well as safeguarding and promoting the values of access, privacy, and intellectual freedom. [ABSTRACT FROM AUTHOR]

ChatGPT's capability to generate original content on any topic represents a concern for academic institutions, since students can plagiarise the AI-created content with a low probability of being caught. While prior research on academic misconduct emphasized the combined effects of perceived costs and benefits in explaining students' decisions to cheat, the low detectability of ChatGPT-based plagiarism significantly reduces the cost of being caught, making rational choice theory less powerful in explaining academic misconduct in the AI era. Considering the effects of both rational decision-making and moral considerations, this study shows that individuals experiencing moral disengagement are more likely to engage in ChatGPT-based plagiarism. Other significant predictors include perceived benefits, punishment severity, and informal sanctions. Furthermore, moral disengagement enhances the effects of formal sanctions on ChatGPT-based plagiarism. The results have implications for professors, academic administrators, and plagiarism detection software designers to enforce academic integrity in the ChatGPT era. [ABSTRACT FROM AUTHOR]

ChatGPT, which launched only a year ago, is the fastest-growing website in the world today. When generative AI software such as ChatGPT generates ideas for people, they often generate false ideas. This occurrence has been called 'AI Hallucination'. It can include generating false text output that is extremely believable to completely gibberish. This source of potential misinformation has significant potential implications for the travel and tourism industry. Using survey responses from 900 consumers, this empirical study contributes to theorizing and examination of how consumers' awareness of AI Hallucination potential combines with existing concepts from the Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB) when it comes to the decision to use generative AI platforms such as ChatGPT for tourism planning. This research also examines if the consumers are actually able to discern AI Hallucination and why they select to use AI technologies over other tourism information sources, such as aggregated peer review websites like TripAdvisor, government tourism websites, or social media influencers. The results indicate that many consumers chose error-filled AI tourism itineraries over other options because they trust the AI to be more impartial and customized than the other sources. [ABSTRACT FROM AUTHOR]

Since its launch in November 2022, ChatGPT has pioneered a new era in AI, globally acclaimed for its content creation and language understanding. This advancement is reshaping industries like hospitality, offering innovative applications but also raising ethical and efficiency challenges. In the context of New Zealand's hotel industry, renowned for its vibrant and inclusive 'Kiwi' hospitality culture, the idea of incorporating generative AI offers a novel perspective. While its application could potentially enhance service efficiency and help to alleviate staff shortages, integration with the country's deeply rooted cultural values demands a carefully considered approach. This study adopted a qualitative methodology using semi-structured interviews with hotel managers and AI experts in New Zealand. The findings revealed that generative AI holds promises for cost savings, work efficiency and meeting specific social group demands. Concerns have been raised, however, relating to the ability of AI to handle complex interactions, incorporate a sense of Kiwi culture, respond appropriately to service contingency events, maintain data privacy and meet the generational service preferences of guests. The absence of clear AI legislation has led to cautious interest among hotel managers, restrained by concerns around legality, privacy and service quality. [ABSTRACT FROM AUTHOR]

Based on the coping theory and coping model of user adaptation, this research explores the impact of users’ ChatGPT technostress on cognitive appraisal, coping process, and behaviour. A survey using Amazon’s Mechanical Turk was developed to collect data on 10 occupations that may be replaced by ChatGPT in the U.S., with a total of 277 actual ChatGPT users. This study employs the software SmartPLS4.2 to evaluate the measurement model and the structural model. The results show that concerns over coolness and posthuman capabilities significantly affect users’ challenge appraisal of ChatGPT, whereas privacy, ethics, and security concerns significantly impact users’ threat appraisal of ChatGPT. Challenge and threat appraisals have a significantly positive impact on users’ problem-focused coping and emotion-focused coping, which themselves significantly predict users’ continuous use of ChatGPT. Mindfulness negatively moderates the influence on emotion-focused coping and continued use intention after ChatGPT adoption. The main theoretical contributions of this research include investigating users’ ChatGPT technostress and coping process by professional workers who may be replaced by ChatGPT. The evidence regarding the moderating role of mindfulness presented herein is novel, because the relationship between coping strategies and continued behaviour intention has not been previously examined. [ABSTRACT FROM AUTHOR]

Healthcare educators are exploring ways to integrate Large Language Models (LLMs) into the curriculum. At the same time, they are concerned about the negative impact on students' cognitive development. There is concern that the students will not learn to think and problem-solve by themselves and instead become dependent on LLMs to find answers. In addition, the students could start accepting the LLM generated responses at face value. The Illusion of Explanatory Depth (IoED) is a cognitive bias where humans believe they understand complex phenomena in more depth than they do. This illusion is caused when people rely on external sources of information rather than deeper levels of internalized knowledge. This illusion can be exposed by asking follow-up in depth questions. Using the same approach, specifically iterative prompting, can help students interact with LLM's while learning actively, gaining deeper levels of knowledge, and exposing the LLM shortcomings. The article proposes that educators encourage use of LLMs to complete assignments using a template, that promotes students' reflections on their interactions with LLMs, using iterative prompting. This process based on IoED, and iterative prompting will help educators integrate LLMs in the curriculum while mitigating the risk of students becoming dependent on these tools. Students will practice active learning and experience firsthand the inaccuracies and inconsistencies in LLM responses. [ABSTRACT FROM AUTHOR]

Aim: This study aimed to evaluate the real-life performance of clinical vignettes and multiple-choice questions generated by using ChatGPT. Methods: This was a randomized controlled study in an evidence-based medicine training program. We randomly assigned seventy-four medical students to two groups. The ChatGPT group received ill-defined cases generated by ChatGPT, while the control group received human-written cases. At the end of the training, they evaluated the cases by rating 10 statements using a Likert scale. They also answered 15 multiple-choice questions (MCQs) generated by ChatGPT. The case evaluations of the two groups were compared. Some psychometric characteristics (item difficulty and point-biserial correlations) of the test were also reported. Results: None of the scores in 10 statements regarding the cases showed a significant difference between the ChatGPT group and the control group (p >.05). In the test, only six MCQs had acceptable levels (higher than 0.30) of point-biserial correlation, and five items could be considered acceptable in classroom settings. Conclusions: The results showed that the quality of the vignettes are comparable to those created by human authors, and some multiple-questions have acceptable psychometric characteristics. ChatGPT has potential in generating clinical vignettes for teaching and MCQs for assessment in medical education. [ABSTRACT FROM AUTHOR]

In the design field, persona is widely used to help design teams understand their target users. However, existing persona tools have limitations such as insufficient interactivity, inability to arouse designers' empathy, and inability to finely segment users. We developed Vivid-Persona, which is a customisable persona tool offering an interactive and immersive experience. Designers can set the demographics and scenarios of the target user to customise a persona. The tool generates a realistic image of the persona using a Diffusion model. Embedded with the ChatGPT and SadTalker models, the persona can engage in real-time video chats with designers. The persona is augmented with facial expressions, based on the analysis of the emotions in utterances. A user study showed that Vivid-Persona effectively solves the problem of user segmentation, significantly enhancing the designer's perception of persona in terms of authenticity, clarity, empathy and willingness to use, as well as the quality of the output design solutions. [ABSTRACT FROM AUTHOR]

The present research aims to highlight the underlying factors that drive students' adoption of the ChatGPT chatbot in higher education. This study extends the meta-UTAUT framework by including additional exogenous factors of anthropomorphism, trust, design novelty, and institutional policy. Empirical examination with Structural Equation Modelling among 355 students in Dutch higher education institutions revealed attitude and behavioural intention as significant positive predictors of students' ChatGPT use behaviour. Institutional policy negatively moderated the effect of behavioural intention on use behaviour. Behavioural intention was significantly and positively influenced by attitude, performance expectancy, social influence, and facilitating conditions. Anthropomorphism, design novelty, trust, performance expectancy, and effort expectancy were unveiled as significant positive antecedents of attitude. The central theoretical contributions of this research include investigating students' use behaviour instead of behavioural intention, establishing attitude as a core construct, underlining additional antecedents of attitude, and highlighting the importance of institutional policy. The present study contributes to prior research on technology adoption, especially in the area of artificial intelligence in education. The findings yield valuable insights for chatbot designers, product managers, and higher education policy writers. [ABSTRACT FROM AUTHOR]

What do golems, talismans, and Artificial Intelligence (AI) share? How would Ibn Sīnā have classified ChatGPT? Must AI be de-mythologized, or can mythos help us navigate a strange new world? Why does AI seem occult, and is ChatGPT a pricey talisman? These questions offer insight into theological concerns about AI, including (1) human exceptionalism, (2) creating new beings, (3) objects knowing, and (4) metaphors other than a demon or demigod. This article examines AI through a classical Islamicate occult paradigm to better grasp what it is, metaphysically speaking, and how developments in AI might outmode some post-Enlightenment worldviews. [ABSTRACT FROM AUTHOR]

The conversational AI emergence technologies like ChatGPT, Claude AI, and Gemini AI are transforming the hospitality and tourism industries. While existing research explores theoretical applications, a critical gap exists in understanding real-world implementation challenges, prompting strategies, and operational impacts of ChatGPT and other AI applications. This study investigates AI integration patterns, prompt optimization techniques (e.g. Input-Output, Chain-of-Thought, and Tree-of-Thought approach), and implementation strategies through a mixed-methods approach. We conducted a bibliometric analysis of 80 studies using R-Biblioshiny, followed by surveys and interviews with stakeholders, including guests/travelers, managers, and academics. Our empirical analysis measures personalization, user satisfaction, operational efficiency, and research productivity. The results demonstrate that while generative AI can enhance customer experiences and operational efficiency, success depends on selecting appropriate prompting methodologies, ethical considerations, workforce development, and community impact. This research provides an integrated framework for responsible AI adoption while identifying critical areas for future research. [ABSTRACT FROM AUTHOR]

The article explores how platforms like Google and ChatGPT, which claim omniscience and wisdom-like attributes, prompt philosophical questions. It revisits religious perspectives on omniscience and their influence on the pursuit of wisdom. The article suggests that while Google may offer compartmentalized omniscience based on user preferences, ChatGPT's factual accuracy challenges its characterization as omniscient. Nonetheless, ChatGPT can still help humans progress toward wisdom, by integrating the co-creation of knowledge between humans and the unfolding of divine knowledge from Process Thought and Buddhist epistemology insights. Notably, instead of offering definitive answers, the paper is written with a sense of deep humility to encourage ongoing inquiry and investigation. [ABSTRACT FROM AUTHOR]

AbstractIntroductionMethodsResultsConclusionSHORT CONDENSATIONArtificial intelligence (AI) has many applications in health care. Popular AI chatbots, such as ChatGPT, have the potential to make complex health topics more accessible to the general public. The study aims to assess the accuracy of current long-acting reversible contraception information provided by ChatGPT.We presented a set of 8 frequently-asked questions about long-acting reversible contraception (LARC) to ChatGPT, repeated over three distinct days. Each question was repeated with the LARC name changed (e.g., ‘hormonal implant’ vs ‘Nexplanon’) to account for variable terminology. Two coders independently assessed the AI-generated answers for accuracy, language inclusivity, and readability. Scores from the three duplicated sets were averaged.A total of 264 responses were generated. 69.3% of responses were accurate. 16.3% of responses contained inaccurate information. The most common inaccuracy was outdated information regarding the duration of use of LARCs. 14.4% of responses included misleading statements based on conflicting evidence, such as claiming intrauterine devices increase one’s risk for pelvic inflammatory disease. 45.1% of responses used gender-exclusive language and referred only to women. The average Flesch readability ease score was 42.8 (SD 7.1), correlating to a college reading level.ChatGPT offers important information about LARCs, though a minority of responses are found to be inaccurate or misleading. A significant limitation is AI’s reliance on data from before October 2021. While AI tools can be a valuable resource for simple medical queries, users should be cautious of the potential for inaccurate information.ChatGPT generally provides accurate and adequate information about long-acting contraception. However, it occasionally makes false or misleading claims. [ABSTRACT FROM AUTHOR]

The widespread use of large language models, such as ChatGPT, has changed the learning behaviours of undergraduate students, raising issues of academic dishonesty. This study investigates the factors that influence the ethical use of ChatGPT among undergraduates using the recently proposed Theory of Reasoned Goal Pursuit. Through a qualitative elicitation procedure, 26 salient beliefs were identified, representing procurement and approval goals, advantages and disadvantages, the social influence, and factors facilitating and hindering ethical use of ChatGPT. A subsequent, two-wave quantitative survey provided promising evidence for the theory, revealing that positive attitudes and subjective norms emerged as key antecedents of motivation to use ChatGPT ethically. Likewise, motivation and perceived behavioural control were strong predictors of intentions to do so. The study discusses the implications for future research regarding this timely issue. It emphasizes the potential of these findings in developing effective interventions that encourage ethical use of large language models within tertiary education. Additionally, it highlights the usefulness of the TRGP in investigating educational-related intentions and behaviours. [ABSTRACT FROM AUTHOR]

The aim of the present study has been to analyze the relationship between the frequency of using ChatGPT for academic purposes and the level of plagiarism, as well as to determine if this relationship is moderated by a series of student-centered variables, such as their academic performance, workload, time management, amotivation, hypercompetitiveness, cheating culture, and unawareness of the consequences of plagiarism. For this purpose, a total of 507 Spanish university students participated, responding to a series of scales to measure the previously mentioned constructs. The results reveal, first, that there is a correlation between the frequency of using ChatGPT for academic purposes and plagiarism, but the causality between these variables is almost nonexistent, regardless of moderating variables. Likewise, it is observed that cheating culture and amotivation did turn out to be significant variables in predicting plagiarism. These results confirm that a higher frequency of using ChatGPT for academic purposes does not necessarily lead to a higher likelihood of plagiarism, as ChatGPT can be used academically for responsible purposes. Furthermore, it is certain personal variables of university students, such as being involved in a cheating culture or experiencing amotivation, that cause the likelihood of plagiarism to increase. [ABSTRACT FROM AUTHOR]

This paper utilizes neutralization theory to understand cheating with AI-assisted programs among university students. Using data collected from undergraduate students across the United States, we explore how criminological concepts and demographics predict the number of times someone cheated over the past year as well as the likelihood of using AI-assisted tools to cheat. We find agreement with cheating neutralization techniques, general cyber-neutralization techniques, and the presence of deviant peers positively associate with all cheating outcomes, while sense of guilt is inversely associated. Low self-control is positively associated with use of AI-assisted misconduct, but not the number of times students cheated. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) has rapidly emerged as a pivotal force in a multitude of sectors. This research explores the growing convergence of AI tools, such as ChatGPT, in the field of academic writing, with a focus on 136 postgraduate students from China. These students were randomized into groups that utilized AI-integrated tools in both online and offline environments. The study involved designing hybrid instructional modules that blend online and offline elements. Furthermore, an extensive questionnaire was used to evaluate the advancements of postgraduate students in domains such as digital readiness, writing self-efficacy, student engagement, and academic emotional health. The results from this investigation highlight significant improvements in several facets of postgraduate involvement, including behavioral, emotional, and cognitive engagement, as well as writing self-efficacy. The study also probes the impact of digital readiness on academic involvement, revealing a positive association with student engagement, writing self-efficacy, and academic sentiments. By augmenting students’ technical proficiency, digital literacy, and acclimation to digital tools and platforms, educational institutions can bolster academic engagement, amplify writing confidence, and foster favorable academic emotion. [ABSTRACT FROM AUTHOR]

In early 2023, as the release of Artificial Intelligence (AI) tools such as ChatGPT became more widespread, concerns arose in the higher education sector regarding how students might use generative AI (gen-AI), not only for writing critical essays, but for producing creative works. Multiple gen-AI tools appeared specifically targeting the application to writing screenplays. This prompted the question: what are the ethical and pedagogical implications of integrating gen-AI within the context of teaching and learning screenwriting within the academy? The research design for this project applied a practice-based approach to script development, embedding critical reflection on the iterative process of engaging with gen-AI to write a short screenplay. The gen-AI was also prompted to self-critique the story it generated. The research identified ethical concerns regarding equitable access to technology, the potential for bias and theft of works used to train the AI. The study also found that engaging with gen-AI privileged analytical thinking over emotional engagement with the creative process. The findings suggest that creative confidence and an awareness of one’s own creative process are critical to effectively engage with gen-AI. [ABSTRACT FROM AUTHOR]

AbstractPurposeMaterials and methodsResultsConclusionSelf-testing has been proven to significantly improve not only simple learning outcomes, but also higher-order skills such as clinical reasoning in medical students. Previous studies have shown that self-testing was especially beneficial when it was presented with feedback, which leaves the question whether an immediate and personalized feedback further encourages this effect. Therefore, we hypothesised that individual feedback has a greater effect on learning outcomes, compared to generic feedback.In a randomised cross-over trial, German medical students were invited to voluntarily answer daily key-feature questions via an App. For half of the items they received a generalised feedback by an expert, while the feedback on the other half was generated immediately through ChatGPT. After the intervention, the students participated in a mandatory exit exam.Those participants who used the app more frequently experienced a better learning outcome compared to those who did not use it frequently, even though this finding was only examined in a correlative nature. The individual ChatGPT generated feedback did not show a greater effect on exit exam scores compared to the expert comment (51.8 ± 22.0% vs. 55.8 ± 22.8%; p = 0.06).This study proves the concept of providing personalised feedback on medical questions. Despite the promising results, improved prompting and further development of the application seems necessary to strengthen the possible impact of the personalised feedback. Our study closes a research gap and holds great potential for further use not only in medicine but also in other academic fields. [ABSTRACT FROM AUTHOR]

Is ChatGPT a good teacher? Or could it be? As understanding is widely acknowledged as one of the fundamental aims of education, the answer to these questions depends on whether ChatGPT fosters or could foster the acquisition of understanding in its users. In this paper, I tackle this issue in two steps. In the first part of the paper, I explore and analyze the set of skills and social-epistemic virtues that a teacher must exemplify to perform her job well – in those contexts in which epistemic aims are at play and in which understanding plays a pivotal role. In the second part of the paper, I put my conception of good teacher to test and deal with the question whether, and to which extent, the software ChatGPT is (or could serve as, if suitably modified or fine-tuned) a good teacher for its users. I close with some final reflections that point to further directions of research. [ABSTRACT FROM AUTHOR]

Museum education plays a pivotal role in enriching the visitor experience by promoting learning and engagement across all age groups. This article introduces a framework that envisions the integration of technology, particularly natural language processing (NLP) models like ChatGPT, as a transformative force in the field of museum education. The framework examines the strengths and weaknesses of ChatGPT, its diverse applications, and the potential advantages and drawbacks it presents, with a particular emphasis on science museums as an illustrative example. This framework revolves around the identification of key stakeholders in museum education, including visitors, educators, curators, and administrators. It delves into the myriad ways ChatGPT can be employed to address various aspects and functions within museum education. These applications encompass tasks such as responding to visitor queries, offering tailored recommendations, and facilitating constructive dialogues between visitors and museum personnel. The insights gained from this exploration hold the promise of positively impacting both the theoretical underpinnings and practical implementations of museum education in the foreseeable future. [ABSTRACT FROM AUTHOR]

AbstractThe affordances of ChatGPT in language learning and teaching have gained increasing traction. While studies began to investigate the potential of ChatGPT as a feedback provider, little attention was given to ChatGPT’s potential impact on students’ writing performance and the ideal L2 writing self vis-à-vis the established automated writing evaluation systems (AWE). To address these gaps, a sequential explanatory mixed methods design was adopted. One hundred and fifty second-year university students from three writing classes in a Chinese public university were recruited and randomly divided into a ChatGPT group, an AWE group, and a control group. After an eleven-week intervention, the ANCOVA results showed that while the ChatGPT group scored significantly higher than the AWE group and the control group in post-writing performance as measured by their writing score, in terms of students’ ideal L2 writing self, the ChatGPT group performed significantly lower than the AWE group with a medium effect size. Qualitative analysis of students’ reflection papers revealed students’ (over)reliance on the tool and the accompanying loss of creativity and agency. Pedagogical implications as well as directions for future research are also discussed. [ABSTRACT FROM AUTHOR]

Programming education gains importance in high schools as the digital age progresses. However, the openness and adaptability of programming languages present unique challenges for instructional practices compared to other subjects. While traditional instructional tools offer limited support, ChatGPT, a groundbreaking Generative Artificial Intelligence, has shown impressive capabilities in natural language processing and knowledge generation. This study explored whether ChatGPT can transcend existing limitations and improve programming education through a quasi-experimental approach with post-hoc interviews in high school classrooms. A total of 153 students participated, and the results from MANCOVA and ANCOVA analyses revealed that students using ChatGPT reported lower levels of flow experience, self-efficacy, and learning achievement compared to those utilizing conventional methods. Post-hoc interviews further revealed that students felt ChatGPT's effectiveness in facilitating their programming learning fell short of their initial expectations. These findings highlight the need to carefully consider the complexity of programming learning tasks and students' cognitive, affective, and interactive dimensions when integrating AI technologies into education. We discuss the implications and provide thorough pedagogical strategies, specifically the guidance–practice–transformation (G–P–T) mode, to maximize the potential of AI tools and support high school programming education, emphasizing the balance of technological innovation with learning best practices. [ABSTRACT FROM AUTHOR]

In the rapidly evolving landscape of technology, the emergence of Chat Generative Pre-trained Transformer (ChatGPT) marks a pivotal milestone in the realm of Artificial Intelligence (AI). However, little research has reported the predictors of people's intentions to use ChatGPT. This pioneering study empirically examines user adoption through the lens of the Technology Acceptance Model (TAM) using a convenience sampling method. The study surveyed 784 ChatGPT users in China, of whom 58.93% were males. The results have revealed several key findings: (1) perceived usefulness, perceived ease of use, behavioral intention, and use behavior were positively correlated with each other; (2) behavioral intention acted as a mediating factor in the relationship between perceived usefulness and use behavior, as well as the relationship between perceived ease of use and use behavior; (3) perceived usefulness and behavioral intention played a chain-mediated role between perceived ease of use and use behavior; (4) the relationship between behavioral intention and use behavior exhibited greater strength among females compared to males; (5) the association between behavioral intention and use behavior was found to be stronger among urban users in comparison to their rural counterparts; (6) the connections between perceived ease of use and perceived usefulness, perceived ease of use and behavioral intention, and behavioral intention and use behavior were observed to be stronger among individuals with higher educational backgrounds relative to those with lower educational backgrounds. These findings provide crucial nuanced insights to advance the practical application of ChatGPT, emphasizing the need for enhanced usability and ease of use. However, this study exclusively captured usage behaviors within the Chinese user base. Future investigations could encompass diverse demographics across multiple countries, enabling cross-cultural comparisons. [ABSTRACT FROM AUTHOR]

In the ever-evolving domain of artificial intelligence (AI), understanding how users interact with AI-driven solutions, like ChatGPT, has become vital. The purpose of this research is to explore factors influencing user satisfaction and their willingness to subscribe to ChatGPT's superior services. Employing partial least squares structural equation modeling, the study examines responses from 554 ChatGPT users. The results reveal that perceived intelligence and service quality of ChatGPT significantly influence perceived usefulness, knowledge management, and overall user satisfaction. Interestingly, while perceived usefulness notably augments user satisfaction, it doesn't directly drive willingness to subscribe to paid services. Similarly, knowledge management boosts satisfaction but doesn't affect payment readiness. Importantly, user satisfaction substantially encourages willingness to pay for advanced features. Personal innovativeness contributes to willingness to pay, but it doesn't modify the impacts of perceived usefulness, knowledge management, or satisfaction on payment readiness. Finally, perceived risk negatively impacts willingness to pay. These findings illuminate the intricate mechanisms governing user-AI interactions and factors determining their readiness for premium subscriptions. This research lays groundwork for future scholarly investigations of AI-user dynamics. [ABSTRACT FROM AUTHOR]

AbstractThe rapid emergence of generative artificial intelligence (GAI) models like ChatGPT has sparked significant interest in their application for language learning, particularly for second language (L2) writing. Given the urgent need for effective tools in Chinese grammar checking to assist L2 learners, this study evaluated the impact of both model version (ChatGPT-3.5 vs 4.0) and prompt language (Chinese vs English) on the effectiveness of automated corrective feedback (ACF) for L2 Chinese writing. Utilizing a dataset of 153 erroneous single-sentence examples from a Routledge-published textbook on Chinese, we assessed error corrections and corrective feedback generated by both ChatGPT versions under different language prompts. Three experienced language teachers evaluated the output corrections for grammaticality, fluency, minimal alterations, and over-correction, and the output feedback for correctness, understandability, and detail. Findings revealed that although both model versions produced grammatically correct and fluent corrections, ChatGPT-4.0 demonstrated superior performance in generating more accurate, detailed, and understandable corrective feedback compared to ChatGPT 3.5. The results suggest that model version significantly influences ChatGPT’s effectiveness as a multilingual ACF tool, more so than prompt language. This study highlights the potential of advanced GAI, such as ChatGPT-4.0, in enhancing language instruction and error correction for languages beyond English. It advocates for further research on the application of such models in diverse linguistic and educational contexts. [ABSTRACT FROM AUTHOR]

This study investigated the application of the Kolb model to assess the efficacy of ChatGPT in enhancing English grammar learning. Data were gathered through interviews and observations. By analysing data across the Kolb model’s stages - concrete experience, reflective observation, abstract conceptualisation, and active experimentation - both the strengths and weaknesses of ChatGPT become apparent. The results indicated that while ChatGPT encourages interactive learning and enthusiasm among students, there is a prevailing doubt regarding its accuracy, underscoring the necessity of maintaining a critical mindset towards AI-generated content. Participants emphasised ChatGPT’s supportive role in education, aiding in the understanding and applying grammar concepts. However, concerns regarding ChatGPT’s occasional inaccuracies and struggles to understand contextual nuances are observed. The study highlights the importance of human involvement in AI tools and the need for students to develop technological literacy. Furthermore, it proposes a pedagogical model effectively utilising ChatGPT in English grammar education [ABSTRACT FROM AUTHOR]

AbstractBackgroundMethodsResultsConclusionIntegrating Artificial Intelligence (AI) into public health education represents a pivotal advancement in medical knowledge dissemination, particularly for chronic diseases such as asthma. This study assesses the accuracy and comprehensiveness of ChatGPT, a conversational AI model, in providing asthma-related information.Employing a rigorous mixed-methods approach, healthcare professionals evaluated ChatGPT’s responses to the Asthma General Knowledge Questionnaire for Adults (AGKQA), a standardized instrument covering various asthma-related topics. Responses were graded for accuracy and completeness and analyzed using statistical tests to assess reproducibility and consistency.ChatGPT showed notable proficiency in conveying asthma knowledge, with flawless success in the etiology and pathophysiology categories and substantial accuracy in medication information (70%). However, limitations were noted in medication-related responses, where mixed accuracy (30%) highlights the need for further refinement of ChatGPT’s capabilities to ensure reliability in critical areas of asthma education. Reproducibility analysis demonstrated a consistent 100% rate across all categories, affirming ChatGPT’s reliability in delivering uniform information. Statistical analyses further underscored ChatGPT’s stability and reliability.These findings underscore ChatGPT’s promise as a valuable educational tool for asthma while emphasizing the necessity of ongoing improvements to address observed limitations, particularly regarding medication-related information. [ABSTRACT FROM AUTHOR]

Our study aims to consider the artificial intelligence (AI) writing tool ChatGPT and the extent to which it can be used in the legal profession. Despite the positive views on the AI tool, particularly the belief it will be beneficial in all aspects of life, there are views that contradict this. In particular, our article will aim to consider the stories of both success and failure when it comes to the use of the tool in the legal profession. [ABSTRACT FROM AUTHOR]

Generative artificial intelligence (AI) is gaining traction across various fields, yet its adoption within social work remains limited. This study explores the use of ChatGPT by social work educators to enhance teaching, research, and service activities. Six educators documented their use of ChatGPT in fall 2023 to explore AI integration in academia with a qualitative content analysis and quantitative assessments of usage frequency and perceived usefulness. The findings indicated that ChatGPT was considered useful in 85% of interactions, with the majority using ChatGPT for teaching support. Ethical and practical challenges are discussed, noting that AI tools like ChatGPT augment rather than replace human expertise. Social work academics are encouraged to reflect on AI use to enhance their work. [ABSTRACT FROM AUTHOR]

With the rapid evolution of artificial intelligence (AI), this study aims to examine the interplay among the perceived usability, perceived enjoyment, perceived responsiveness, and intention to continue using ChatGPT. Structural equation modeling (SEM) was used to investigate our proposed model. We recruited 446 ChatGPT users through an online survey conducted on the Connect platform, powered by CloudResearch. Perceived usability (β = 0.254) and enjoyment (β = 0.438) significantly influence satisfaction with ChatGPT. However, perceived responsiveness is not significantly related to perceived attachment or satisfaction. Furthermore, we established that perceived attachment (β = 0.405) and satisfaction (β = 0.447) are pivotal in shaping users' intentions to continue using ChatGPT, providing insights into human–AI interactions. The practical implications of our findings suggest that generative AI chatbots should be crafted with a focus on enjoyable, user-centered interfaces that foster long-term user satisfaction and engagement. AI developers should design AI conversation flows and chatbot personas to optimize the user experience. [ABSTRACT FROM AUTHOR]

Technologically assisted methods have been extensively utilized in positive psychology interventions (PPIs), which aim to elevate the happiness levels of the widespread and diverse general public, a population that traditional methodologies struggle to comprehend and impact. Nevertheless, the literature provides insufficient insights into the effectiveness of chatbot-based PPIs (Chat-PPIs). This study endeavors to fill this void by employing both retrieval-based and generative pre-trained transformer (GPT)-based chatbots and executing three randomized controlled trials involving 326 participants to investigate the hypothesized effectiveness mechanisms. The statistical analysis affirms the effectiveness of Chat-PPI. Moreover, our results indicate that personalized PPI recommendations, adaptive multi-round dialogues, and real-time feedback significantly augment the efficacy of Chat-PPI. Besides exploring and confirming the mechanisms behind Chat-PPI, this study also endorses the use of generative chatbots, which, although less controllable, provide more natural interaction that can boost the efficacy of Chat-PPI. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) such as GPT-3 and their derivative products such as ChatGPT have garnered significant attention for their remarkable ability to process texts and conduct human-like conversations. Guided by the Diffusion of Innovation theory, this study examines the early discussions about LLMs on Twitter, specifically about ChatGPT and GPT-3, during the first three months following the release of ChatGPT. By utilizing topic structural modeling and sentiment analysis on a sample of 42,273 #ChatGPT tweets and 17,639 #GPT3 tweets, we explore how laypeople and technical professionals differ in their attitudes in the early stage of the adoption of LLMs. Our findings suggest that the discussion surrounding ChatGPT and GPT-3 primarily revolves around relative advantage and compatibility, with the majority of #ChatGPT conversations demonstrating negative sentiment and #GPT3 discussions containing more positive topics. The Twitter discussion using #ChatGPT is highly business-oriented, while the discussion of #GPT3 covers a broader range of topics in terms of the characteristics, applications, and potential ethical concerns of LLMs. This study offers implications for government agencies and policymakers, suggesting that further research is needed to fully understand the potential applications and risks of LLMs. [ABSTRACT FROM AUTHOR]

This study offers lessons for P-12school leaders grappling with integrating artificial intelligence (AI) into learning, teaching, and schooling. The goal was to understand what leadership conversations were being had in the first year of the public's use of ChatGPT and what advice was given to school leaders. We collected all the articles from 12 popular U.S. practitioner magazines and journals in the first year of ChatGPT's release that focused on the intersection of AI and school leadership. We located 23 articles that directly provided suggestions and approaches for school leaders around AI in schools. [ABSTRACT FROM AUTHOR]

The community of inquiry framework examines the interplay between four kinds of presence (teaching, cognitive, social, and learner) to promote effective learning in online education. This paper investigates the impact of instructor participation (IP), a key component of teaching presence, on student discourse in discussion boards with automated grading. A content analysis of 1146 contributions on the Yellowdig discussion platform suggests that high IP enhances cognitive, social, and learner presence, but remains insufficient to deter the use of AI tools, such as ChatGPT. Overall, high IP adds considerable value by modeling desirable behaviors, encouraging effort, and promoting more thoughtful online student discourse. [ABSTRACT FROM AUTHOR]

AbstractGenerative artificial intelligence (genAI) tools like ChatGPT are becoming increasingly embedded in daily life. In the field of education in particular, concerns have emerged about how these tools might positively or negatively impact student learning. In the current study, I conduct a randomized field experiment exploring how policies on genAI impact undergraduate students’ beliefs, behaviors, and grades. Students enrolled in two sections of the same upper-level undergraduate research methods course were randomly assigned to a section that either permitted or prohibited genAI tools. At the end of the semester, students enrolled in the section permitting genAI tools had a more positive view of genAI in higher education. However, students enrolled in the section prohibiting these tools had a higher final grade. These results highlight the need for evidence-based guidelines on how to minimize the risks and maximize the benefits of genAI in higher education. [ABSTRACT FROM AUTHOR]

Clinical relevance: Worldwide, millions suffer from cataracts, which impair vision and quality of life. Cataract education improves outcomes, satisfaction, and treatment adherence. Lack of health literacy, language and cultural barriers, personal preferences, and limited resources may all impede effective communication. Background: AI can improve patient education by providing personalised, interactive, and accessible information tailored to patient understanding, interest, and motivation. AI chatbots can have human-like conversations and give advice on numerous topics. Methods: This study investigated the efficacy of chatbots in cataract patient education relative to traditional resources like the AAO website, focusing on information accuracy,understandability, actionability, and readability. A descriptive comparative design was used to analyse quantitative data from frequently asked questions about cataracts answered by ChatGPT, Bard, Bing AI, and the AAO website. SOLO taxonomy, PEMAT, and the Flesch-Kincaid ease score were used to collect and analyse the data. Results: Chatbots scored higher than AAO website on cataract-related questions in terms of accuracy (mean SOLO score ChatGPT: 3.1 ± 0.31, Bard: 2.9 ± 0.72, Bing AI: 2.65 ± 0.49, AAO website: 2.4 ± 0.6, (p < 0.001)). For understandability (mean PEMAT-U score AAO website: 0,89 ± 0,04, ChatGPT 0,84 ± 0,02, Bard: 0,84 ± 0,02, Bing AI: 0,81 ± 0,02, (p < 0.001)), and actionability (mean PEMAT-A score ChatGPT: 0.86 ± 0.03, Bard: 0.85 ± 0.06, Bing AI: 0.81 ± 0.05, AAO website: 0.81 ± 0.06, (p < 0.001)) AAO website scored better than chatbots. Flesch-Kincaid readability ease analysis showed that Bard (55,5 ± 8,48) had the highest mean score, followed by AAO website (51,96 ± 12,46), Bing AI (41,77 ± 9,53), and ChatGPT (34,38 ± 9,75, (p < 0.001)). Conclusion: Chatbots have the potential to provide more detailed and accurate data than the AAO website. On the other hand, the AAO website has the advantage of providing information that is more understandable and practical. When patient preferences are not taken into account, generalised or biased information can decrease reliability. [ABSTRACT FROM AUTHOR]

This research showcases the transformative potential of large language models (LLMs) for built environment auditing from street-view images. By empirically testing the performances of two multimodal LLMs, ChatGPT and Gemini, we confirmed that LLM-based audits strongly agree with virtual audits processed by a conventional deep learning-based method (DeepLabv3+), which has been widely adopted by existing studies on urban visual analytics. Unlike conventional field or virtual audits that require labor-intensive manual inspection or technical expertise to run computer vision algorithms, our results show that LLMs can offer an intuitive tool despite the user's level of technical proficiency. This would allow a broader range of policy and planning stakeholders to employ LLM-based built environment auditing instruments for smart urban infrastructure management. [ABSTRACT FROM AUTHOR]

Background: This study aimed to determine whether surgical multiple-choice questions generated by ChatGPT are comparable to those written by human experts (surgeons). Methods: The study was conducted at a medical school and involved 112 fourth-year medical students. Based on five learning objectives in general surgery (colorectal, gastric, trauma, breast, thyroid), ChatGPT and surgeons generated five multiple-choice questions. No change was made to the ChatGPT-generated questions. The statistical properties of these questions, including correlations between two group of questions and correlations with total scores (item discrimination) in a general surgery clerkship exam, were reported. Results: There was a significant positive correlation between the ChatGPT-generated and human-written questions for one learning objective (colorectal). More importantly, only one ChatGPT-generated question (colorectal) achieved an acceptable discrimination level, while other four failed to achieve it. In contrast, human-written questions showed acceptable discrimination levels. Conclusion: While ChatGPT has the potential to generate multiple-choice questions comparable to human-written ones in specific contexts, the variability across surgical topics points to the need for human oversight and review before their use in exams. It is important to integrate artificial intelligence tools like ChatGPT with human expertise to enhance efficiency and quality. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is increasingly proving to be capable of assisting humans in complex decision-making processes. ChatGPT has become a crucial tool for assessing mental health and emotional awareness and helping to predict outcomes. Social workers' use of ChatGPT in navigating ethical dilemmas remains relatively unexplored. In this study, ChatGPT is compared to the Israeli Ethics Committee's responses to assess its utility in aiding social workers' ethical decisions. We translated questions previously sent to the Israeli Ethics Committee and posed them to ChatGPT-4 twice, one month apart. A significant improvement was observed in ChatGPT's second round of responses, which were more comprehensive and emphasised ethical dilemma complexity. ChatGPT consistently highlighted conflicting obligations and professional boundaries, contributing to a more nuanced understanding of ethical issues. The Ethics Committee's responses provided clearer, more actionable guidance, and was more concerned with legal issues. ChatGPT's tendency to address a variety of considerations ensures its potential to enhance ethical decision-making awareness and its value as a tool for social workers but it is not yet capable of independently resolving ethical dilemmas. ChatGPT's promising progress in supporting ethical decision-making in social work has led to discussions regarding the ethical implications of AI implementation within therapeutic professions. [ABSTRACT FROM AUTHOR]

The development and application of Artificial Intelligence (AI) is one of the major socio-economic, political and environmental issues facing the world today. It has also become a major issue in tourism. This editorial posits that tourism research needs to engage with AI and related new technologies at more than the level of business applicability and consumer perception and use, as important as they are. Rather we argue that different orders of the effects of AI need to be engaged with in tourism studies if researchers are to make a substantial contribution to making tourism smart, i.e. fully understanding its impacts, advantages, disadvantages, and long-term implications for business, destinations, consumers, society and the environment. Then all orders of effect need to be examined. [ABSTRACT FROM AUTHOR]

This article explores the value of generative AI (genAI) tools for much-needed support for instructors in higher education in the realm of course design. Two authors detail their experiences partnering with two distinct tools, ChatGPT and Bard (now known as Gemini), for communication course development, emphasizing iterative collaboration with genAI. Benefits of genAI for creativity and innovation are balanced with challenges and ethical considerations, along with recommendations for faculty and institutions on leveraging genAI for innovative course design. [ABSTRACT FROM AUTHOR]

This activity prompts students to go beyond the often reductionist responses to new technologies (e.g. technological determinism) by creating a media literacy-focused infographic about the role, uses, ethical concerns, and/or impact of generative AI (e.g. ChatGPT). Sample topics have included the role of AI in specific industries (e.g. film, advertising, accounting, etc.) and media studies topics (e.g. online dating, celebrities, sports, communicating with the dead, etc.). The activity includes five one-week segments that culminate with a poster presentation session for the campus community. Successful completion of the assignment also provided students with a tangible portfolio item. Courses: This activity wasdevelopedfor an introductory course in media studies. It could be modified for any course level and applied to a variety of relevant courses in communication, and media studies, among others. Objectives: After the completion of this unit, students will have gained: (1)an understanding of the approaches to new technologies (e.g. technological determinism) and critical media literacy as guiding theoretical frameworks;(2) the ability to apply these frameworks to new media innovations and specific industries;(3) improved research, synthesis, and application skills; and(4) improved skills in strategic communication, message design, and public speaking. [ABSTRACT FROM AUTHOR]

AbstractWhile previous studies have compared English as a foreign language (EFL) students’ perceptions of teacher- and ChatGPT-generated feedback on their writing, there remains a gap in understanding how students incorporate feedback from these sources into their revisions. To address this, our study investigated how students use feedback from teachers and ChatGPT in the context of argumentative writing. Twenty Chinese undergraduate students participated in the study, composing argumentative essays, receiving feedback from both teachers and ChatGPT, and revising their essays accordingly. We analyzed their revisions to assess their engagement with the feedback and the appropriateness of their revisions. Additionally, we collected and analyzed their responses to a questionnaire that explored their perceptions and preferences regarding teacher feedback and ChatGPT feedback. The findings revealed that students displayed higher levels of engagement and achieved greater accuracy in their revisions when using teacher feedback. However, an intriguing pattern emerged, indicating that students effectively addressed language and content issues with teacher feedback but showed a particular inclination towards successfully integrating feedback on organization from ChatGPT. Furthermore, the questionnaire results indicated a general preference for teacher feedback while recognizing the unique strengths of ChatGPT feedback, particularly in relation to organization. These findings underscore the potential of using ChatGPT feedback as a complementary resource to teacher feedback. The study demonstrated how these two feedback sources can be synergistically aligned to enhance the overall quality of feedback in EFL writing, promoting a more integrated approach to improve the teaching efficacy of EFL writing. [ABSTRACT FROM AUTHOR]

The rapid adoption and evolution of generative artificial intelligence (AI) tools like ChatGPT and Gemini have impacted marketing education and practice. This paper introduces a prompt engineering assignment that utilizes generative AI to build critical thinking skills through the development of keyword research strategies, customer profiles, and presentation outlines. Using insights from students, educators, and marketers, the assignment is refined to include (a) reflections about the learning and application of the generative AI tools and (b) evaluations about the accuracy and potential for bias in the generated output. The assignment tasks align with marketing practice, and guidance is provided on how to adapt and update the assignment. [ABSTRACT FROM AUTHOR]

Guided by the scholarly understanding of generative artificial intelligence, this study explores technical writing students’ engagement with ChatGPT during their writing process. This study is informed by the classical five canons of rhetoric, along with the contemporary reinterpretations of the canons. Employing a qualitative analysis of interviews, this study argues that the students’ engagement with ChatGPT allows for reframing and expanding the notions of the writing process and rhetorical canons in the previous literature. [ABSTRACT FROM AUTHOR]

Written corrective feedback (WCF) is crucial in foreign language learning, helping learners identify and rectify writing errors. However, manual WCF can be time-consuming for educators. Artificial general intelligence (AGI), exemplified by ChatGPT, offers a promising solution via automated WCF, addressing learners’ intricate linguistic demands. While effective in English learning, the suitability of AGI-powered automated WCF for other languages with complex grammar remains uncertain due to the English-centric training of many large language models. This study examines the reliability and acceptance of ChatGPT-generated WCF within a German as a foreign language (GFL) context. Through a 200-essay analysis, we explore two questions: (1) How does ChatGPT-generated automated WCF compare to teacher-provided WCF? (2) How do GFL learners respond and interact with WCF from both sources? Our findings revealed different behavioral, cognitive, and affective engagements between ChatGPT-provided WCF and teacher-provided WCF. ChatGPT has greater potential for providing diverse lexical, grammatical, structural, and content feedback, facilitating GFL learning. However, students’ emotional perceptions of ChatGPT-generated WCF vary, sometimes even negative, hindering language learning. We further explored the advantages and challenges of integrating ChatGPT-generated WCF into foreign language learning. Our findings underscore the potential of integrating AI-powered automated WCF into foreign language learning and writing development. [ABSTRACT FROM AUTHOR]