No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
From Uncertainty to Tenacity: Investigating User Strategies and Continuance Intentions in AI-Powered ChatGPT with Uncertainty Reduction Theory
International Journal of Human-Computer Interaction
Abstract
The introduction of ChatGPT in academia has raised significant concerns, particularly regarding issues like plagiarism and the ethical use of generative text for academic purposes. Existing literature has predominantly focused on ChatGPT adoption, leaving a notable gap in addressing the strategies users employ to mitigate these emerging challenges. To bridge this gap, this research utilizes the Uncertainty Reduction Theory (URT) to formulate user strategies for reducing uncertainty. These strategies include both interactive and passive approaches. Concurrently, the study identifies key sources of uncertainty, which include concerns related to transparency, information accuracy, and privacy. Additionally, it introduces the concepts of seeking clarification and consulting peer feedback as mediating roles to facilitate reduced uncertainty. We tested these hypotheses with a sample of Indonesian users (N = 566) using structural equation modeling via Smart-PLS 4.0 software. The results confirm that interactive Uncertainty Reduction Strategies (URS) are more effective in reducing uncertainty when using ChatGPT compared to passive URS. Transparency concerns, information accuracy, and privacy concerns are identified as factors that increase the level of uncertainty. In contrast, consulting peer feedback is the most effective strategy for reducing uncertainty compared to seeking clarification at the individual-system level. Insights from the mediating effects confirm that consulting peer feedback significantly mediates uncertainty sources to reduce uncertainty. The study discusses various strategies for the ethical use of ChatGPT by users in the educational context and contributes significantly to theoretical development.
... Format examines the organization and presentation of information, and accuracy and reliability address the correctness and dependability of the content provided. This comprehensive evaluation, accounting for the positive potentials and risks identified by Foroughi et al. [11]; Strzelecki [12]; Chang, Silalahi, and Lee [13]; and Menon and Shilpa [14], as well as the integrity concerns highlighted by D. Cotton, P. Cotton, and Shipway [15]; Bin-Nashwan, Sadallah, and Bouteraa [16]; Liu et al. [17], and Ansari, Ahmad, and Bhutta [18], seeks to offer an expansive perspective on ChatGPT's effectiveness and to elucidate its role in the academic sector. Through this investigation, the study is aimed at significantly advancing the conversation surrounding the deployment of AI in education and underpinning its practical applications with robust empirical insights. ...
... While numerous studies have applied UIS in various contexts, there is a noticeable gap in research explicitly focusing on UIS concerning AI-powered tools in education, mainly the quality of information generated by ChatGPT. The need to explore this area has become increasingly clear, as Chang, Silalahi, and Lee [13] have pointed out the potential for such information to create uncertainty. Additionally, Fu et al. [24] have raised concerns that information from ChatGPT could lead to misinformation and potentially harm users' knowledge and decision-making abilities, especially in educational settings. ...
... In this study, which aims to assess user satisfaction with information generated by AI systems like ChatGPT based on IQ dimensions, applying IQT is both timely and crucial. The release of generative AI tools like ChatGPT raises concerns about ensuring the quality of dynamically generated content [13]. As a result, traditional IQ dimensions like accuracy, relevance, and completeness must be reassessed to confirm that these AI systems are effectively meeting users' information needs. ...
Incorporating AI tools like ChatGPT into higher education has been beneficial, yet the extent of user satisfaction with the quality of information provided by these tools, known as user information satisfaction (UIS) and information quality (IQ) theory, remains underexplored. This study introduces a UIS model specifically designed for ChatGPT’s application in the educational sector based on multidimensions of IQ theory. Drawing from established UIS and IQ theory, we crafted a model centered around seven essential factors that influence the effective use of ChatGPT, aiming to guide educators and learners in overcoming common challenges such as plagiarism and ensuring the ethical use of AI. Data was collected from Indonesian university participants (N=508) and analyzed using structural equation modeling with Smart-PLS 4.0. The results reveal that completeness, precision, timeliness, convenience, and information format are the most influential factors driving user satisfaction with ChatGPT. Interestingly, our research indicated that the accuracy and reliability of the information, typically deemed paramount, were not the primary concerns in the academic use of ChatGPT. Our findings recommend a cautious approach to integrating ChatGPT in higher education. We advocate for strategic use that recognizes its innovative potential while acknowledging its limitations, ensuring responsible and effective application in educational contexts. This balanced perspective is crucial for integrating AI tools into the academic fabric without compromising educational integrity or quality.
... According to Uncertainty Reduction Theory, individuals strive to enhance understanding and reduce uncertainty prevalent in unprecedented situations with potentially detrimental consequences regarding employment, privacy, and ethical norms (Ambartsoumean & Yampolskiy, 2023). The likeliness to adopt favorable behaviors towards engaging with new technology grows in proportion to users' confidence based on obtaining sufficient information to achieve mastery, lessening the risk in the face of high uncertainty (Chang et al., 2024;Singh & Chandra, 2023). Trust acts as a mediator between negative emotions of fear and behavioral outcomes such as the willingness to use AI (Montag et al., 2023). ...
This conceptual study explores the dynamics shaping the public perception of artificial intelligence (AI). In addition to the expanding role of AI in daily life and the adoption of platforms such as the ChatGPT, this systematic conceptual research explores the psychological and ethical dimensions influencing societal acceptance or rejection of AI. Central to this inquiry are factors such as personal experiences with AI, perceived self-efficacy, job threat perceptions, and the pivotal role of trust in technology. Utilizing cognitive appraisal theory and uncertainty reduction theory, this study explores how positive interactions and high self-efficacy foster acceptance of AI. In contrast, fear, fuelled by uncertainties and ethical concerns, leads to resistance. This research further extends the current knowledge in practice and education in psychology and offers valuable insights for policymakers and technologists. The study provides practical recommendations to facilitate more informed, ethical, and psychologically attuned integration of AI into society.
In this study, we present a brief narrative review focused on ChatGPT, a state-of-the-art conversational agent developed using OpenAI’s Generative Pretrained Transformer (GPT) framework. Distinctive for its ability to generate text of high quality in real-time, ChatGPT has emerged as a leader among artificial intelligence chatbots, garnering interest from both commercial and scholarly circles. Our review explores the technological underpinnings of ChatGPT, examines its inherent features that support its performance, and analyzes existing research on its applications and impacts across several domains. Through this assessment, we delineate ChatGPT’s strengths and limitations, offering informed recommendations for future investigations in this burgeoning research field.
Over the past few decades, healthcare sector has developed along parallel paths with trendy technology. Modern practices of artificial intelligence strategies have led to improved diagnosis, the development of effective treatments, telemedicine, and the development of patient monitoring devices. Many applications have emerged that help doctors and healthcare workers, most notably Chatbot. It is a program that utilises artificial intelligence techniques to conduct conversations in real-time. This program is able to simulate that you are a natural person writing or talking to another Internet user, which is the application. This article discusses the matter of Chatbot technology in developing electronic healthcare services and helping patients communicate electronically to obtain information that supports them in improving their health condition.
Present-day power users of AI-powered social chatbots encounter various uncertainties and concerns when forming relationships with these virtual agents. To provide a systematic analysis of users' concerns and to complement the current West-dominated approach to chatbot studies, we conducted a thorough observation of the experienced uncertainties users reported in a Chinese online community on social chatbots. The results revealed four typical uncertainties: technical uncertainty, relational uncertainty, ontological uncertainty, and sexual uncertainty. We further conducted visibility and sentiment analysis to capture users' response patterns toward various uncertainties. We discovered that users' identification of social chatbots is dynamic and contextual. Our study contributes to expanding, summarizing, and elucidating users' experienced uncertainties and concerns as they form intimate relationships with AI agents.
Information source accuracy and trustworthiness are vital in undergraduates’ education in terms of how they seek teacher feedback and educational content. Nowadays, the infusion of technologies into education has led to convenient and easy access to learning materials in electronic libraries and web-based platforms or search engines. Undergraduates are expected to make rapid use of ground-breaking technologies to sift for academic information over the internet. With the advent of ChatGPT, it is estimated that undergraduates might rely on it for academic information. The theoretical study gauges the potential impact of ChatGPT on the information-seeking behavior of undergraduates and what it means for classroom engagement. To do this, we utilized the inquiry-based learning theory which emphasizes the active participation of learners in discovering new information. The study is one of the first to contribute to the ongoing discussions on the impact of large language models (LLMs) such as ChatGPT on education.KeywordsChatGPTchatbotsinformation-seeking behaviorinquiry-based learningnatural language processing
This study aimed to investigate the decision-making abilities of ChatGPT-3, an artificial intelligence (AI) system, in ethical dilemmas, with a focus on understanding the implications of ethical considerations in AI development. Utilizing a within-subject design, participants were presented with three ethical dilemmas, each involving conflicts between various values. These scenarios were also run through ChatGPT-3 for comparison. Notable differences were found between the decision-making processes of humans and ChatGPT-3, especially in situations where moral choices were distinctly labeled as good or evil and directed towards a promising outcome. The implications of these findings are significant, offering insights to inform AI development by stressing the importance of incorporating ethical theories and processes in AI systems. This is a crucial step towards the goal of designing AI models that are more ethically aware. Furthermore, this study draws attention to the ethical impacts of AI usage, aiding policymakers and regulators in making educated decisions about the part AI should play in decision-making and regulation in ethically important contexts.
Purpose
The purpose of this paper is to identify the factors determining students’ attitude toward using newly emerged artificial intelligence (AI) tool, Chat Generative Pre-Trained Transformer (ChatGPT), for educational and learning purpose based on technology acceptance model.
Design/methodology/approach
The recommended model was empirically tested with partial least squares structural equation modeling using 375 student survey responses.
Findings
The study revealed that students have a favorable view of the instructional use of ChatGPT. Usefulness, social presence and legitimacy of the tool, as well as enjoyment and motivation, contribute to a favorable attitude toward using this tool in a learning environment. However, perceived ease of use was not found to be a significant determinant in the adoption and utilization of ChatGPT by the students.
Practical implications
This research is intended to benefit enterprises, academic institutions and the global community by offering light on how students perceive the ChatGPT service in an educational setting. Furthermore, the application enhances confidence and interest among learners, leading to improved literacy and general awareness. Eventually, the outcome of this research will help AI developers to improve their product and service delivery, as well as benefit regulators in regulating the usage of AI-based bots.
Originality/value
Due to its novelty, the current research on AI-based ChatGPT usage in the education sector is rather restricted. This study provides the adoption aspects of ChatGPT, a new AI-based technology for students, thereby contributing significantly to the existing research on the adoption of advanced education technologies. In addition, the literature lacks research on the adoption of ChatGPT by students for educational purposes; this study addresses this gap by identifying adoption determinants of ChatGPT in education.
This paper presents an in-depth study of ChatGPT, a state-of-the-art language model that is revolutionizing generative text. We provide a comprehensive analysis of its architecture, training data, and evaluation metrics and explore its advancements and enhancements over time. Additionally, we examine the capabilities and limitations of ChatGPT in natural language processing (NLP) tasks, including language translation, text summarization, and dialogue generation. Furthermore, we compare ChatGPT to other language generation models and discuss its applicability in various tasks. Our study also addresses the ethical and privacy considerations associated with ChatGPT and provides insights into mitigation strategies. Moreover, we investigate the role of ChatGPT in cyberattacks, highlighting potential security risks. Lastly, we showcase the diverse applications of ChatGPT in different industries and evaluate its performance across languages and domains. This paper offers a comprehensive exploration of ChatGPT’s impact on the NLP field.
This article aims to provide a review of existing research on the use of OpenAI ChatGPT in education using bibliometric analysis and systematic literature review. We explored published articles to observe the leading contributors to this field, the important subtopics, and the potential study in the future. We discovered that there is already a rise in the quantity of articles published on this subject between 2022 and 2023. We also map the research clusters using network analysis. The results obtained found a total of 93 articles. The analysis conclude that keywords such as “challenge,” “teaching,” and “knowledge,” have not been thoroughly researched This article contributes to the literature discussing the use of artificial intelligence in education and can be useful for academics and policymakers in education.
ChatGPT, an artificial intelligence large language model, took the world by storm in November 2022. Its launch was met with excitement, and it garnered over 1 million users within the first five days of its release, surpassing social media giants like Facebook, Instagram, Twitter and even the top search engine, Google. Having been trained on volumes of data, ChatGPT has displayed the ability to produce human-like responses to questions. Concerns have been raised among members of the academic and research community regarding the ethical usage of ChatGPT and language models in education and academic/scientific research. This paper examines the development and rise of ChatGPT and similar AI tools, their pros and cons, their impact on academic research and possible intellectual property conflicts. It concludes that ChatGPT and language models are here to stay and makes recommendations for its ethical usage to prevent and detect plagiarism and protect intellectual property rights.
ABSTRACT
Purpose: The advent of ChatGPT, one of the most advanced chatbots building on OpenAI's Large Language Models, may transform the ways in which language is learned, taught, and assessed in the contemporary world wrought by technological innovation. Against this backdrop, this study aims to generate empirical insights into the extent to which ChatGPT is perceived and leveraged by EFL learners beyond the classroom. Design/Methodology: This quantitative cross-sectional investigation draws upon the technology acceptance model (TAM) as developed by Davis (1989) to conceptualize EFL learners' attitudes, intentions, and actual behaviors of using ChatGPT in their informal digital learning of English. A total of 405 EFL learners answered the revised TAM questionnaire with scales including Perceived Ease of Use, Perceived Usefulness, Attitude, Behavioral Intention, and Actual Use. Findings: The results of structural equation modeling analyses indicated that while Perceived Ease of Use fails to predict learners' Attitude directly, it can leave an impact on Attitude through the full mediator Perceived Usefulness. It was also found that learners who take positive attitudes toward the usefulness of ChatGPT tend to demonstrate a higher level of Behavioral Intention, which positively and strongly predicts their actual use of this latest AI-powered tool in English learning outside the classroom. Originality/value: This study provides empirical evidence that supports the potential of ChatGPT as a powerful language-learning tool that EFL learners should utilize to participate creatively and productively in the ecological CALL shaped by constantly emerging AI technologies.
ChatGPT is an emerging technology that revolutionizes organizational practices, fundamentally altering how individuals in organizations search for, generate, and utilize information within the workplace. The effective functioning of many organizations heavily relies on data and information. ChatGPT has streamlined the process of working with data and information, making it more accessible for organizations and the individuals involved. However, the adoption of ChatGPT also presents challenges across various domains, including social, economic, and legal considerations. This study conducts a comprehensive literature review to explore multiple perspectives on integrating ChatGPT into organizational management. It examines various aspects, such as the development of ChatGPT, its practical uses, ethical implications, governance mechanisms, regulations and policies. This study aims to guide managers and stakeholders in effectively incorporating ChatGPT into their organizational processes. This study provides a detailed examination of ChatGPT's impact on organizational management, offering valuable insights to practitioners and scholars alike, aiming to navigate the complexities and harness the benefits of this transformative technology. By understanding the implications and leveraging the potential of ChatGPT, organizations can enhance their operations and decision-making processes.
ChatGPT can revolutionize education by enhancing student engagement and making learning more personalized. Drawing on UTAUT2, this study investigated determinants of intention to use ChatGPT for educational purposes. Data were gathered from 406 Malaysian students and analyzed using a hybrid approach including "partial least squares" (PLS) and "fuzzy-set qualitative comparative analysis" (fsQCA). PLS showed that performance expectancy, effort expectancy, hedonic motivation , and learning value significantly influence the intention to use ChatGPT. Furthermore, we found that personal innovativeness and information accuracy negatively moderate the associations between ChatGPT use and its determinants. While PLS demonstrated that social influence, facilitating conditions, and habit do not affect ChatGPT use, fsQCA revealed that all factors might affect the intention to use ChatGPT. fsQCA suggested that eight combinations of factors may lead to high ChatGPT use. The results hold various implications for ChatGPT developers, instructors, and universities and provide insights for accelerating ChatGPT adoption.
ChatGPT, an AI-based chatbot, was released to provide coherent and useful replies based on analysis of large volumes of data. In this article, leading scientists, researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research seeks to improve our knowledge of ChatGPT capabilities and its use in the education sector, identifying potential concerns and challenges. Our preliminary evaluation concludes that ChatGPT performed differently in each subject area including finance, coding and maths. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported hallucinations within Generative AI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial.
The field of Natural Language Processing (NLP) has seen significant advancements in recent years, thanks in large part to the development of powerful language models such as ChatGPT. ChatGPT, short for Chat Generative Pre-trained Transformer, is a large-scale neural language model developed by OpenAI that is capable of generating human-like responses to natural language input. With its impressive performance on a range of language tasks, ChatGPT has quickly become one of the most widely used language models in NLP research and application.
The preceding paragraph showcases ChatGPT’s capabilities, as it was composed and formatted entirely using artificial intelligence (AI).
Clearly, ChatGPT holds tremendous power when it comes to writing-based tasks. ChatGPT, and similar large language model technologies, have the potential to be disruptive technologies, significantly affecting not just academic libraries but higher education as a whole. In this article, we aim to explore some of these potential issues and propose a few possibilities for how we, as information professionals, may be able to help address them as they emerge.
This study investigates the implications of ChatGPT, an AI-powered language model, for students and universities by examining the perceptions of scholars and students. The responses of seven scholars and 14 PhD students from four countries – Turkey, Sweden, Canada and Australia – are analysed using a thematic content analysis approach. Nine key themes emerge from the findings. According to their frequency
of recurrence, these themes are: “Evolution of learning and education systems”, “changing role of educators”, “impact on assessment and evaluation”, “ethical and social considerations”, “future of work and employability”, “personalized learning”, “digital literacy and AI integration”, “AI as an extension of the human brain”, and “importance of human characteristics”. The potential benefits of AI in education as well as the challenges and barriers that may arise from its integration are discussed in the context of existing literature. Based on these findings, suggestions for future research include further exploration of the ethical implications of AI for education, the development of strategies to manage privacy concerns, and the investigation of how educational institutions can best prepare for the integration of AI technologies. The
paper concludes by emphasizing the importance of understanding the potential opportunities and challenges associated with AI in higher education and the need for continued research in this area.
ChatGPT is an AI tool that has sparked debates about its potential implications for education. We used the SWOT analysis framework to outline ChatGPT's strengths and weaknesses and to discuss its opportunities for and threats to education. The strengths include using a sophisticated natural language model to generate plausible answers, self-improving capability, and providing personalised and real-time responses. As such, ChatGPT can increase access to information, facilitate personalised and complex learning, and decrease teaching work-load, thereby making key processes and tasks more efficient. The weaknesses are a lack of deep understanding, difficulty in evaluating the quality of responses, a risk of bias and discrimination, and a lack of higher-order thinking skills. Threats to education include a lack of understanding of the context, threatening academic integrity, perpetuating discrimination in education, democratising plagiarism, and declining high-order cognitive skills. We provide agenda for educational practice and research in times of ChatGPT.
The need of the hour is to encourage research on topics with newness and novelty. In this context, this article discusses multidimensional benefits and potential pitfalls of using artificial intelligence‐based Chat Generative Pre‐trained Transformer (ChatGPT), and provides numerous ideas for future research in consumer studies and marketing in the context of ChatGPT. ChatGPT provides algorithm‐generated conversational responses to text‐based prompts. Since its launch in the late 2022, ChatGPT has generated significant debate surrounding its hallmarks, benefits and potential pitfalls. On the one hand, ChatGPT can offer enhanced consumer engagement, improved customer service, personalization and shopping, social interaction and communication practice, cost‐effectiveness, insights into consumer behaviour and improved marketing campaigns. On the other hand, potential pitfalls include concerns about consumer well‐being, bias, misinformation, lack of context, privacy concerns, ethical considerations and security. The article concludes by outlining a potential future research agenda in the area of ChatGPT and consumer studies. Overall, this article provides valuable insights into the benefits and challenges associated with ChatGPT, shedding light on its potential applications and the need for further research.
ChatGPT is an artificial intelligence (AI)-based conversational large language model (LLM). The potential applications of LLMs in health care education, research, and practice could be promising if the associated valid concerns are proactively examined and addressed. The current systematic review aimed to investigate the utility of ChatGPT in health care education, research, and practice and to highlight its potential limitations. Using the PRIMSA guidelines, a systematic search was conducted to retrieve English records in PubMed/MEDLINE and Google Scholar (published research or preprints) that examined ChatGPT in the context of health care education, research, or practice. A total of 60 records were eligible for inclusion. Benefits of ChatGPT were cited in 51/60 (85.0%) records and included: (1) improved scientific writing and enhancing research equity and versatility; (2) utility in health care research (efficient analysis of datasets, code generation, literature reviews, saving time to focus on experimental design, and drug discovery and development); (3) benefits in health care practice (streamlining the workflow, cost saving, documentation, personalized medicine, and improved health literacy); and (4) benefits in health care education including improved personalized learning and the focus on critical thinking and problem-based learning. Concerns regarding ChatGPT use were stated in 58/60 (96.7%) records including ethical, copyright, transparency, and legal issues, the risk of bias, plagiarism, lack of originality, inaccurate content with risk of hallucination, limited knowledge, incorrect citations, cybersecurity issues, and risk of infodemics. The promising applications of ChatGPT can induce paradigm shifts in health care education, research, and practice. However, the embrace of this AI chatbot should be conducted with extreme caution considering its potential limitations. As it currently stands, ChatGPT does not qualify to be listed as an author in scientific articles unless the ICMJE/COPE guidelines are revised or amended. An initiative involving all stakeholders in health care education, research, and practice is urgently needed. This will help to set a code of ethics to guide the responsible use of ChatGPT among other LLMs in health care and academia.
The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of using ChatGPT in higher education, and discusses the potential risks and rewards of these tools. The paper also considers the difficulties of detecting and preventing academic dishonesty, and suggests strategies that universities can adopt to ensure ethical and responsible use of these tools. These strategies include developing policies and procedures, providing training and support, and using various methods to detect and prevent cheating. The paper concludes that while the use of AI in higher education presents both opportunities and challenges, universities can effectively address these concerns by taking a proactive and ethical approach to the use of these tools.
Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts.
ChatGPT-3 is a powerful language model developed by OpenAI that has the potential to revolutionize the way weinteract with technology. This model has been trained on a massive amount of data, allowing it to understand andgenerate human-like text with remarkable accuracy. One of the most exciting possibilities of ChatGPT-3 is its potentialto improve natural language processing (NLP) and natural language understanding (NLU) in a wide range ofapplications. In particular, ChatGPT-3 can be used to power chatbots, virtual assistants, and other conversationalinterfaces. These types of systems are becoming increasingly important as more and more people use voice and text tointeract with technology, we list ChatGpt role in each of the follwoing sections
ChatGPT Cybersecurity Medical data Digitization Intro to ChatGPT ChatGPT is a large language model developed by OpenAI. It is trained on a dataset of conversational text and can be used to generate human-like responses to prompts in a variety of languages and formats. It can be used for tasks such as chatbots, language translation, and text completion. The role of ChatGPT is to generate human-like text based on a given prompt or context. It can be used in a variety of applications such as chatbots, language translation, text completion, and question answering. Additionally, it can be fine-tuned for specific tasks such as generating product descriptions or summarizing articles. It can also be used to generate creative writing such as poetry and stories. It can be integrated into a wide range of industries from customer service to entertainment, to research.
ChatGPT, the cutting-edge language model developed by OpenAI, is one of the most exciting advancements in the field of artificial intelligence. With its ability to generate human-like text and respond to complex questions, ChatGPT has already made a significant impact and is poised to continue its rapid progression in the coming years. As we look to the future of ChatGPT and large language models, there are many exciting possibilities and open opportunities for this technology to enhance our lives and change the way we interact with technology
Today, cybersecurity is considered one of the most noteworthy topics that are circulated frequently among companies in order to protect their data from hacking operations. The emergence of cyberspace contributed to the growth of electronic systems. It is a virtual digital space through which interconnection is established between computers and smartphones connected within the Internet of Things environment. This space is critical in building a safe digital environment free of threats and cybercrime. It is only possible to make a digital environment with the presence of cyberspace, which contains modern technologies that make this environment safe and far from unauthorized individuals. Cybersecurity has a wide range of challenges and obstacles in performance, and it is difficult for companies to face them. In this report, the most significant practices, sound, and good strategies will be studied to stop cybercrime and make a digital environment that guarantees data transfers between electronic devices safely and without the presence of malicious software. This report concluded that the procedures provided by cybersecurity are required and must be taken care of and developed.
This study investigated the impacts of risk perceptions in online travel communities on source credibility and community engagement using the uncertainty reduction theory. Through a quasi-experimental design, this study found that the impact of risk perception varies by the type and level of risk. Functional risk had a positive impact on source credibility; financial risk had a negative impact. Source credibility did not impact community engagement except in high-risk scenarios which is a different result compared to past published studies. The results of this study indicate that online community interactions provide a means of mitigating perceived functional risk but do not alleviate financial risk perceptions. ARTICLE HISTORY
With the development of deep connections between humans and Artificial Intelligence voice‐based assistants (VAs), human and machine relationships have transformed. For relationships to work it is essential for trust to be established. Although the capabilities of VAs offer retailers and consumers enhanced opportunities, building trust with machines is inherently challenging. In this paper, we propose integrating Human–Computer Interaction Theories and Para‐Social Relationship Theory to develop insight into how trust and attitudes toward VAs are established. By adopting a mixed‐method approach, first, we quantitatively examine the proposed model using Covariance‐Based Structural Equation Modeling on 466 respondents; based on the findings of this study, a second qualitative study is employed to reveal four main themes. Findings show that while functional elements drive users' attitude toward using VAs, the social attributes, being social presence and social cognition, are the unique antecedents for developing trust. Additionally, the research illustrates a peculiar dynamic between privacy and trust and it shows how users distinguish two different sources of trustworthiness in their interactions with VAs, identifying the brand producers as the data collector. Taken together, these results reinforce the idea that individuals interact with VAs treating them as social entities and employing human social rules, thus supporting the adoption of a para‐social perspective.
Consumer robots are technically evolving and have a growing presence in our daily lives with enhanced interactive capabilities. While there is insightful literature on robot adoption, so far, research has done less to examine the post-adoption interaction of human-consumer robots. Drawing on trust in technology model and psychological ownership theory, this study proposes a conceptual dual model to explain robot users' post-adoption behaviours, while considers the moderating roles of anthropomorphism and social presence. We empirically corroborated our model by asking from 403 current robot owners to illustrate theoretical paths to their post-adoption behaviours including cognitive absorption and intention to explore. This study contributes to the extant literature of human-robot interaction by proposing a theoretically grounded and empirically tested framework that contextualizes psychological ownership theory, uncertainty reduction theory, and trust in technology model. We also highlight the implications for practitioners to leverage trust and psychological ownership mechanisms together for encouraging users to actively engage with robots.
Despite high expectations for the growth of Fintech, it has not reached the expected growth in the real world. As Fintech is innovative but inherently unpredictable, customers are still hesitant to adopt and use Fintech, which ultimately affects its growth. To achieve the sustainable development and growth of Fintech, an in-depth investigation of Fintech continuance intentions is required. To investigate continuous-use behavior in a Fintech context, this study focuses on two relevant issues: uncertainty and information technology (IT) quality. Uncertainty is more critical in Fintech than in traditional e-banking transactions because Fintech transactions are complicated and less predictable. IT quality is also crucial to Fintech success because IT plays a key role in Fintech transactions. This study mainly explores the relationship between uncertainty and IT quality, both of which significantly affect Fintech continuance intentions. For the purpose, we integrated an IT quality–based perspective with a trust-based model to investigate Fintech continuance intentions. Our results demonstrate that system quality is negatively related to perceived risk, whereas information quality is positively related to trust. Service quality is the most important quality factor for controlling uncertainty and encouraging continued use of Fintech. We found a more extended role of IT in Fintech than in other digital services. This study provides Fintech providers with the practical guidance in the design and implementation of Fintech innovation, thereby achieving the sustainable development of Fintech.
Background
The transition from medical student to hospital-based first year junior doctor (termed “intern” in Australia) is known to be challenging, and recent changes in clinical learning environments may reduce graduate preparedness for the intern workplace. Although manageable challenges and transitions are a stimulus to learning, levels of burnout in junior medical colleagues are concerning. In order to prepare and support medical graduates, educators need to understand contemporary junior doctor perspectives on this transition.
Methods
Final-year University of Queensland medical students recruited junior doctors working in diverse hospital settings, and videorecorded individual semi-structured interviews about their transition from medical student to working as a junior doctor. Two clinical academics (NS and JT) and an intern (ZT) independently conducted a descriptive analysis of interview transcripts, and identified preliminary emerging concepts and themes, before reaching agreement by consensus on the major overarching themes.
Results
Three key themes emerged from the analysis of 15 interviews: internship as a “steep learning curve”; relationships and team; and seeking help. Participants described the intern transition as physically, mentally and emotionally exhausting. They learned to manage long days, administrative and clinical tasks, frequent interruptions and time pressures; identify priorities; deal with criticism without compromising key relationships; communicate succinctly; understand team roles (including their own status within hospital hierarchies); and negotiate conflict. Participants reported a drop in self-confidence, and difficulty maintaining self-care and social relationships. Although participants emphasised the importance of escalating concerns and seeking help to manage patients, they appeared more reluctant to seek help for personal issues and reported a number of barriers to doing so.
Conclusion
Findings may assist educators in refining their intern preparation and intern training curricula, and ensuring that medical school and intern preparation priorities are not seen as competing. Insights from non-medical disciplines into the organisational and relational challenges facing junior doctors and their health-care teams may enhance inter-professional learning opportunities. Workplace support and teaching, especially from junior colleagues, is highly valued during the demanding intern transition.
The increasing ubiquity of Artificial Intelligence (AI) chatbots across a variety of sectors has sparked a burgeoning interest in deciphering the determinants that govern their adoption and usage. This study aims to examine the pivotal factors that influence the practical usage of the AI chatbot, ChatGPT, among a sample of university students. Leveraging the theoretical framework of planned behavior, the research model scrutinizes the interplay between knowledge application, perceived intelligence, usability, attitude, subjective norms, perceived behavioral control, trust, behavioral intention, and actual usage. Data procured from a survey of university students were examined through the lens of structural equation modeling. The outcomes reveal that knowledge application, perceived intelligence, and usability have a positive impact on attitudes towards ChatGPT. Perceived intelligence also influences knowledge application, usability, and trust. Concurrently, attitude and subjective norms notably affect behavioral intention. Contrary to expectations, perceived behavioral control did not significantly influence behavioral intention. Trust emerged as a crucial factor steering behavioral intention, which in turn, positively correlates with the actual usage of ChatGPT. These insights enrich the academic discourse on AI chatbot adoption and provide practical implications for AI developers, educators, and policy makers, striving to enhance user engagement with AI systems in educational contexts.
ChatGPT is an AI tool that assisted in writing, learning, solving assessments and could do so in a conversational way. The purpose of the study was to develop a model that examined the predictors of adoption and use of ChatGPT among higher education students. The proposed model was based on a previous theory of technology adoption. Seven predictors were selected to build a model that predicted the behavioral intention and use behavior of ChatGPT. The partial-least squares method of structural equation modeling was used for data analysis. The model was found to be reliable and valid, and the results were based on a self-reported data of 534 students from a Polish state university. Nine out of ten proposed hypotheses were confirmed by the results. Habit was found to be the best predictor of behavioral intention, followed by performance expectancy and hedonic motivation. The dominant determinant of use behavior was behavioral intention, followed by personal innovativeness. The research highlighted the need for further examination of how AI tools could be adopted in learning and teaching.
Emerging technologies such as artificial intelligence (AI) have raised global interest in how they could revolutionize healthcare delivery. The recent development of Chat Generative Pre-Trained Transformer (ChatGPT) by Open AI has received much public
attention and opened many possibilities for the medical field, like generating patient discharges, medical imaging, the acquisition of data, and information analysis in audit and research. While more research is needed to understand its capabilities and limitations fully, early results suggest that ChatGPT could be a valuable tool for delivering patient care in rheumatology. This article explored ChatGPT's benefits and potential implications for rheumatology practice.
Chatbots’ ability to carry out focused, result-oriented online conversations with human end-users impacts user experience and user satisfaction. Using “Chatbots” as key identifiable examples utilized by Electronic Commerce (E-Commerce) firms in Customer Relationship Management (CRM), this study offers a user satisfaction model in the context of Artificial Intelligence (AI) enabled CRM in E-Commerce. The model is based on Expectation Confirmation Theory (ECT) and Uncertainty Reduction Theory (URT) within the Chatbot context. This model will allow us to investigate if chatbots can provide both businesses and consumers the opportunity to complete a journey from normal through abnormal to the new normal in situations similar to a covid pandemic.
There are enduring misconceptions in the marketing and management literature about the potential biasing effects of Common Method Variance (CMV). One belief is that the biasing effect of CMV is of greater theoretical than practical importance; another belief is that if CMV is a potential problem, it can be easily identified with the Harman one-factor test. In this article, we show that both beliefs are ill founded and need correction. To demonstrate our key points with greater generality, we use analytical derivations rather than empirical simulations. First, we examine the effects of CMV on correlations between observed variables as a function of measure unreliability and the sign and size of the “true” trait correlation. We demonstrate that, for negative trait correlations, CMV leads to a substantial upward bias in observed correlations (i.e., observed correlations are less negative than the trait correlation), and under certain conditions observed correlations may even have the wrong sign (assuming that the method loadings are both positive or both negative). We also show that, for positive trait correlations, the downward bias due to measurement unreliability does not always mitigate the upward bias due to CMV (again assuming that the method loadings are either both positive or both negative). Importantly, our results indicate that the inflationary effect of CMV is larger at lower levels of (positive) trait correlations, whereas the deflationary effect of unreliability is larger at higher levels of trait correlations. Second, we demonstrate analytically the serious deficiencies of the popular Harman one-factor test for detecting common method variance and strongly recommend against its use in future research.
Collaborative learning has great potential in the field of higher education because it promotes the joint construction of knowledge, as well as the development of skills related to the interaction that results in more essential learning processes. Based on a conceptual review of this type of learning, this work explores, from three concrete experiences, how a pedagogical model for virtual higher education can integrate it, and what its implications are. The study highlights among its conclusions the need for careful planning, an adequate dynamic to form collaborative groups, the relevance of student practices related to everyday use of technologies, the change of the teaching role, and autonomy in the management of learning.
Recognizing the recent MOOC movement in higher education, this study aims to examine credit-receiving university students' motivation to use K-MOOCs. In the hypothesized model, we posit three student-level variables, namely self-determination, perceived usefulness and perceived ease of use, and satisfaction as a mediating variable, and examine how these variables affect students' continuance intention to use K-MOOCs. This study hypothesizes: 1) perceived ease of use has a positive influence on perceived usefulness; 2) self-determination, perceived ease of use, and perceived usefulness has a positive influence on satisfaction; and 3) satisfaction has a positive influence on continuance intention to use K-MOOCs. The participants include 222 university students who took the K-MOOC course offered by a large-sized university in Korea. For data collection and analysis, we adapted the existing instruments to fit into our research goals and conducted structural equation modeling to investigate the relationships among the latent variables. The results indicate that both perceived ease of use and perceived usefulness had a positive influence on students' satisfaction with the K-MOOC course. Satisfaction with the K-MOOC course significantly had a positive influence on students' continuance intention to use. The perceived ease of use and the perceived usefulness, mediated by satisfaction, had indirect effects on the continuance intention to use K-MOOCs. Unexpectedly, students' self-determination did not have a significant influence on satisfaction with the K-MOOC course. The contribution of this study is that it provides empirical evidence regarding what factors are likely to influence credit-receiving students' continuance intention to use K-MOOCs and the motivational factors underlying students' intention to earn credits rather than intrinsic motivation.
Given the complexities involved in the sensing, navigational and positioning environment on board automated vehicles we conduct an exploratory survey and identify factors capable of influencing the users’ trust in such system. After the analysis of the survey data, the Situational Awareness of the Vehicle (SAV) emerges as an important factor capable of influencing the trust of the users. We follow up on that by conducting semi-structured interviews with 12 experts in the CAV field, focusing on the importance of the SAV, on the factors that are most important when talking about it as well as the need to keep the users informed regarding its status. We conclude that in the context of Connected and Automated Vehicles (CAVs), the importance of the SAV can now be expanded beyond its technical necessity, of making vehicles function, to a human factors area: calibrating users’ trust.