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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]

Since ChatGPT's release in November 2022, artificial intelligence has come into the spotlight. Inspiring both fascination and fear, chatbots have stirred debates among researchers, developers, and policy makers. The concerns range from concrete and tangible ones—which include replication of existing biases and discrimination at scale, harvesting personal data, and spreading misinformation—to more existential fears that their development will lead to machines with human-like cognitive abilities. Understanding how chatbots work and the human labor and data involved can better help evaluate the validity of concerns surrounding these systems, which although innovative, are hardly the stuff of science fiction. [ABSTRACT FROM AUTHOR]

This in-depth exploration delves into the transformative possibilities of integrating ChatGPT into the realm of dance education. Examining its roles as a learning ally, creative mentor, knowledge transmitter, and perceptual guide within the unique context of dance instruction, the study navigates through the Technological Pedagogical Content Knowledge (TPACK) framework. It showcases how ChatGPT can elevate teaching efficiency, provide real-time feedback on dance movements, kindle artistic curiosity, and extend emotional support to students. While emphasizing its positive impact, the study also acknowledges potential risks, underscoring the irreplaceable role of educators in guiding students on effective ChatGPT utilization, ensuring it complements the nuanced aspects of dance education. The supporting framework presented highlights the dynamic synergy between ChatGPT, educators, and students, promising a more engaging and enriched dance education experience. [ABSTRACT FROM AUTHOR]

AbstractAccording to the technology acceptance model, people’s acceptance of new technology is influenced by their perception of its usefulness and ease of use. We expand the research agenda by identifying the fear of missing out (FOMO) as a potential factor shaping people’s attitudes toward ChatGPT. We predicted that FOMO experiences, characterized by strong desires to stay connected with other people’s lives, would be linked to more AI-related supportive attitudes. In Study 1 (N = 209), university students with more frequent experiences of FOMO showed more favorable attitudes toward ChatGPT. Study 2 (N = 126) found that participants with a greater FOMO were more likely to choose an invitation letter purportedly authored by ChatGPT, despite it being composed by a human, which provided a behavioral choice confirmation of the observed relationship. Study 3 (N = 186) replicated the findings in a tourism context by employing non-student populations. Study 4 (N = 150) explored the propensity for participants to engage with ChatGPT in personal music selection process and obtained the same effect. Together, these findings suggest that the FOMO bias may exert an additional influence on the endorsement of new technologies, which highlights the important role of emotion in technology acceptance. [ABSTRACT FROM AUTHOR]

AbstractPublic attitudes are essential for technology promotion and policy formulation. The present study investigated the Chinese public’s knowledge of ChatGPT, as well as examined the roles played by Big-Five personality traits, social perception, and AI anxiety in shaping the public’s attitudes toward ChatGPT using the questionnaire method. Results showed that: (1) Nearly, 1/3 of teachers surveyed did not know ChatGPT at all, and all of them were primary and secondary school teachers. (2) The level of knowledge about ChatGPT was significantly related to gender, educational level, teaching stage (in teacher samples), and major (in student samples). (3) The public’s positive attitude is higher significantly than the negative attitude. (4) Social perception positively predicted positive attitudes and negatively predicted negative attitudes. Moreover, a notably higher predictive power for positive attitudes compared to negative attitudes was demonstrated by social perception. There is an equally predictive effect of competence perception and warmth perception on attitudes, without any domain effect observed. (5) AI anxiety only positively predicted negative attitudes but did not impact positive attitudes. In explaining negative attitudes, AI anxiety exhibited a higher explanatory power compared to the Big-Five personality traits, primarily correlating with neuroticism. The findings indicate that it’s inappropriate to consider attitude evaluation toward AI as a single dimension. There are relatively independent components for positive and negative attitudes toward AI. The roles played by other predictive variables in attitudes are discussed. [ABSTRACT FROM AUTHOR]

L’objectif de cet article est d’analyser l’utilisation des adjectifs évaluatifs dans le cadre des recherches quantitatives et qualitatives fondées sur le corpus du discours juridictionnel français. Dans cette analyse, nous adopterons l’approche Appraisal (Martin & White 2005) qui s’intéresse aux marques linguistiques laissant entrevoir la présence subjective du sujet parlant dans le texte. Notre corpus comprend 100 arrêts de la Cour de cassation de 2018 à 2022 inclus. Nous utiliserons la plateforme AnaText pour l’analyse quantitative et ChatGPT pour l’analyse qualitative. Cette recherche nous permettra d’identifier les adjectifs évaluatifs les plus souvent utilisés par les juges et d’indiquer les cibles et la polarité de l’argumentation judiciaire.This article aims to analyse the use of evaluative adjectives in quantitative and qualitative research based on the corpus of French jurisdictional discourse. In this analysis, we adopt the Appraisal approach (Martin & White 2005), which focuses on linguistic marks that reveal the subjective presence of the speaker in the text. Our corpus comprises 100 judgments of the Court of Cassation from 2018 to 2022 inclusive. We use the AnaText platform for quantitative analysis and ChatGPT for qualitative analysis. This research allows us to identify the evaluative adjectives most often used by judges and to indicate the targets and polarity of judicial argumentation. [ABSTRACT FROM AUTHOR]

AbstractIntroductionMethodResultsConclusionMultiple-choice questions (MCQs) are frequently used for formative assessment in medical school but often lack sufficient answer explanations given time-restraints of faculty. Chat Generated Pre-trained Transformer (ChatGPT) has emerged as a potential student learning aid and faculty teaching tool. This study aims to evaluate ChatGPT’s performance in answering and providing explanations for MCQs.Ninety-four faculty-generated MCQs were collected from the pre-clerkship curriculum at a US medical school. ChatGPT’s accuracy in answering MCQ’s were tracked on first attempt without an answer prompt (Pass 1) and after being given a prompt for the correct answer (Pass 2). Explanations provided by ChatGPT were compared with faculty-generated explanations, and a 3-point evaluation scale was used to assess accuracy and thoroughness compared to faculty-generated answers.On first attempt, ChatGPT demonstrated a 75% accuracy in correctly answering faculty-generated MCQs. Among correctly answered questions, 66.4% of ChatGPT's explanations matched faculty explanations, and 89.1% captured some key aspects without providing inaccurate information. The amount of inaccurately generated explanations increases significantly if the questions was not answered correctly on the first pass (2.7% if correct on first pass vs. 34.6% if incorrect on first pass, p < 0.001).ChatGPT shows promise in assisting faculty and students with explanations for practice MCQ’s but should be used with caution. Faculty should review explanations and supplement to ensure coverage of learning objectives. Students can benefit from ChatGPT for immediate feedback through explanations if ChatGPT answers the question correctly on the first try. If the question is answered incorrectly students should remain cautious of the explanation and seek clarification from instructors. [ABSTRACT FROM AUTHOR]

AbstractChatGPT, as the pioneer of advanced generative AI tools, has triggered scholarly discussions about the potential use of such AI technologies in interdisciplinary fields. With a focus on the surge of AI-related preprints since the introduction of ChatGPT by OpenAI, the study investigated what the surge implies for AI literature, particularly in terms of credibility and quality. A scoping review was initially conducted to study the characteristics of the AI-related preprints in the Web of Science (WoS) database and also in five (5) preprint platforms (ArXiv, MedRxiv, SocArxiv, SSRN, and Research Square). The publication date range was set at January 01, 2023 to September 08, 2023. This was followed up by an interpretive phenomenological analysis (IPA) of the perceptions of experts in the AI field about the preprints. Employing a scoping review of AI-related preprints across six databases and a qualitative analysis of 15 AI experts’ opinions, our study reveals concerns about the research accuracy, quality, and credibility of preprints, and advocates for a robust evaluation and high-quality assurance process to promote open science objectives during their dissemination. Specifically, 45,918 AI-related preprints were found in the six preprint databases or repositories across different fields. The nine themes from the IPA showed that preprints can be of value. However, experts advocated for the safe and responsible use of AI-related preprints, involving such tenets as maintaining ethical integrity and high-quality work on the part of authors and establishing sound AI-content guidelines from publishers and editors. Future studies are recommended to investigate the impact of preprints on decision-making processes in educational research and practice. [ABSTRACT FROM AUTHOR]

Generative AI platforms such as ChatGPT have found prominence in recent times with their ability to generate texts, images, etc. Several questions pertaining to ethical and legal issues surrounding ChatGPT have arisen. In this paper, I discuss the nature and background of generative AI, situating its development in the historical context of AI. I then discuss my primary research questions: is sufficient attention paid in the literature on ethics of AI to the principle of beneficence and is there theoretical clarity on its meaning? I highlight that while there is great deal of discussion on what harms can arise from generative AI and how to stop them, there is very little discussion on what amounts to AI-for-good, particularly in the literature of AI ethics and regulation. To the extent that such discussion exists, it pushes ahead with suggesting specific solutions, without fully addressing the underlying question of what makes their prescriptions beneficent. I demonstrate that the principle of beneficence as understood in biomedical ethics and human rights frameworks has limited utility for the ethics of generative AI. These gaps in the AI regulation are prominent, as they can derail long term progress of generative AI and the realization of its full potential. [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]

The adoption and usage of ChatGPT among students are influenced by various factors, including individual characteristics such as age, gender, and experience with technology use. However, studies on the moderating roles of gender, age, and experience in predicting students’ behavioural intention and usage of ChatGPT are limited. This study employed the Unified Theory of Acceptance and Use of Technology (UTAUT2) model to examine the predictors of Higher Education (HE) students’ behavioural intention and usage of ChatGPT. The study employed a descriptive cross-sectional survey design with an adapted instrument to collect data from 486 students. Using the Partial Least Squares Structural Equation Modelling approach, the results showed that hedonic motivation, performance expectancy, effort expectancy, and social influence were significant predictors of students’ behavioural intention, whereas behavioural intention and facilitating conditions had significant influence on students’ actual use of ChatGPT. Age and gender were found to moderate the relationship between facilitating conditions and the use of ChatGPT. Lastly, experience moderated the relationship between habit and the use of ChatGPT, and the relationship between hedonic motivation and behavioural intention. These findings have implications for the design and implementation of ChatGPT in higher education towards enhancing students’ engagement and learning outcomes. [ABSTRACT FROM AUTHOR]

AbstractIntroductionMethodsResultsDiscussionConclusionsEfficient and complete medical charting is essential for patient care and research purposes. In this study, we sought to determine if Chat Generative Pre-Trained Transformer could generate cogent, suitable charts from recorded, real-world poison center calls and abstract and tabulate data.De-identified transcripts of real-world hospital-initiated poison center consults were summarized by Chat Generative Pre-Trained Transformer 4.0. Additionally, Chat Generative Pre-Trained Transformer organized tables for data points, including vital signs, test results, therapies, and recommendations. Seven trained reviewers, including certified specialists in poison information and board-certified medical toxicologists, graded summaries using a 1 to 5 scale to determine appropriateness for entry into the medical record. Intra-rater reliability was calculated. Tabulated data was quantitatively evaluated for accuracy. Finally, reviewers selected preferred documentation: original or Chat Generative Pre-Trained Transformer organized.Eighty percent of summaries had a median score high enough to be deemed appropriate for entry into the medical record. In three duplicate cases, reviewers did change scores, leading to moderate intra-rater reliability (kappa = 0.6). Among all cases, 91 percent of data points were correctly abstracted into table format.By utilizing a large language model with a unified prompt, charts can be generated directly from conversations in seconds without the need for additional training. Charts generated by Chat Generative Pre-Trained Transformer were preferred over extant charts, even when they were deemed unacceptable for entry into the medical record prior to the correction of errors. However, there were several limitations to our study, including poor intra-rater-reliability and a limited number of cases examined.In this study, we demonstrate that large language models can generate coherent summaries of real-world poison center calls that are often acceptable for entry to the medical record as is. When errors were present, these were often fixed with the addition or deletion of a word or phrase, presenting an enormous opportunity for efficiency gains. Our future work will focus on implementing this process in a prospective fashion. [ABSTRACT FROM AUTHOR]

This research paper employs an exploratory framework to evaluate the potential of ChatGPT as an Automated Writing Evaluation (AWE) tool in teaching English as a Foreign Language (EFL) in Thailand. The main objective is to investigate how well ChatGPT can assess students’ writing using prompts and pre-defined rubrics compared to human raters. Moreover, the study examines its strengths and weaknesses as an assessment tool by analysing the teachers’ reflections during the assessment process. Quantitative analyses revealed significant relationships between trial accounts in comparison with the human ratings. Qualitative analysis unearths patterns in the feedback, shedding light on ChatGPT’s strengths and its limitations as an AWE tool. ChatGPT displays substantial promise as an AWE tool, offering distinct features such as human-like interface, consistency, efficiency, and scalability. Nonetheless, educators must be cognisant of its limitations. This study recognises that the strategic use of ChatGPT could enhance the evaluation process among teachers and foster the development of EFL students’ written communication skills. [ABSTRACT FROM AUTHOR]

Professional trainers play an important role in helping new recruits adapt to the workplace. In general hospitals, training courses for clinical teachers still adopt the lecture method. Such a teacher training approach focuses on the way of delivering knowledge and skills, while the training for their teaching of case handling as well as their self-worth and self-confidence could be insufficient. In order to cope with this problem, the present study proposed a ChatGPT-based training mode (ChatGPT-TM) for professional development. To verify its effects, we conducted an experiment in a “Using ChatGPT in Case Teaching” course for clinical teachers in hospitals, and explored their learning achievement, self-worth, self-confidence, and learning perceptions using the ChatGPT training mode (ChatGPT-TM) and the conventional training mode (C-TM). The results showed that the ChatGPT-TM could effectively enhance clinical teachers’ learning achievement in case teaching, self-worth, and self-confidence in comparison with the C-TM. The main contribution of this study is that it revealed that ChatGPT could allow clinical teachers to carry out reflection, verify references, and integrate theory and practice, which improved their learning achievement, made them realize their self-worth, and increased their self-confidence in performing professional training tasks. [ABSTRACT FROM AUTHOR]

Older people are often targeted by fraudsters due to their unique characteristics and vulnerabilities. Being a victim of exploitation can lead to negative emotional and financial consequences. The purpose of this commentary is to present ChatGPT’s potential to provide accessible information and support, helping older consumers protect themselves when confronted with exploitation, address the limitations of ChatGPT and propose solutions to overcome these limitations. Integrating tailored human and technological solutions, such as helplines, AI chatbots, and involving older adults in development, is crucial. By providing adequate training and support, the goal of ensuring accessibility for all users can be achieved. [ABSTRACT FROM AUTHOR]

AbstractThe rapid emergence of Generative Artificial Intelligence (GAI) heralds a significant shift, opening new frontiers in how education is delivered. This groundbreaking wave of technological advancement is poised to redefine traditional learning, promising to enhance the educational landscape with unprecedented levels of personalized learning and accessibility. Despite GAI’s progressive infiltration into various educational strata, limited empirical research exists on its impact on students’ learning performance. Drawing on the Theory of Planned Behavior (TPB) and Behavioral Reasoning Theory (BRT), this study investigates the determinants affecting students’ use of ChatGPT and its influence on learning performance. The data were collected from 357 university students and were analyzed using the PLS-SEM technique. The results supported the role of ChatGPT in positively affecting students’ learning performance. In addition, the results showed that reasons for and against adoption are pivotal in shaping students’ attitudes. ChatGPT use is found to be significantly affected by attitudes, subjective norms, and perceived behavioral control. Besides the theoretical contributions, the findings offer various implications for stakeholders and underscore the necessity for educational institutions to foster a conducive environment for GAI adoption, addressing ethical and technical concerns to optimize learning experiences. [ABSTRACT FROM AUTHOR]

This paper responds to the prevalent discourse on the ‘lack of English proficiency’ among EMI teachers in contexts where English is used as an additional language. It explores how AI-powered tools, particularly ChatGPT, enable EMI teachers in Taiwan to leverage their expertise and teach in English with more confidence. This study first describes the training of an EMI PD programme. Then it reports on the challenges and strategies, and the extended and innovative use by EMI teachers after the training. By reporting on the experiences of three EMI teachers, this study shows how collaborating with ChatGPT contributes to developing an empowered EMI teacher identity. This study fills a research gap, shedding light on the transformative potential of collaborating with ChatGPT to transform content teachers’ identities into an EMI teacher identity. [ABSTRACT FROM AUTHOR]

Upon rapid evolution, ChatGPT can now generate content that is linguistically accurate and logically sound, while sidestepping ethical, social and legal concerns. This research seeks to investigate whether ChatGPT will employ different pragmatic strategies in its responses to (im)polite questions. In our experiment, this AI-powered tool was instructed to answer 200 self-made questions over four (im)politeness levels, and the 200 responses were collected to go through linguistic and sentiment analysis. Triangulated data, together with typical examples, show that ChatGPT tends to give shorter and less positive answers to less polite questions, appearing to be less responsive when confronted with more blunt and offensive inquiries. This, to some extent, resembles how human beings react when treated impolitely. A tentative explanation may be that, given its nature as a large language model, ChatGPT mirrors human interaction in various scenarios, and draws on prevalent human communication tendencies. Thus, interacting with ChatGPT is more of a human-society interaction than human-machine communication in the real sense. Our research sheds light on the coined “human-machine pragmatics”, i.e. how humans can best communicate with computers for the best informative and affective outcomes. The implications for language education are also discussed in the end. [ABSTRACT FROM AUTHOR]

The custom GPT is the latest powerful feature added to ChatGPT. Non-programmers can create and share their own GPTs ("chat bots"), allowing Health Professions Educators to apply the capabilities of ChatGPT to create administrative assistants, online tutors, virtual patients, and more, to support their clinical and non-clinical teaching environments. To achieve this correctly, however, requires some skills, and this 12-Tips paper provides those: we explain how to construct data sources, build relevant GPTs, and apply some basic security. [ABSTRACT FROM AUTHOR]

The recent popularity of ChatGPT and artificial intelligence chatbots presents both challenges and opportunities for incorporating this modern technology in the classroom. This paper introduces an activity that uses ChatGPT to help students practice their role playing sales skills. The benefits of using this AI chatbot for role play training include allowing students to practice when it's convenient and have the ability to react to a chatbot taking on personas of different buyer types. Survey results demonstrate the effectiveness of this training method for both role play training and general familiarity with ChatGPT. [ABSTRACT FROM AUTHOR]

ChatGPT presents a significant disruption in the ways of knowing that highlight the value of control and mastery of knowledge as a quest for certainty. ChatGPT, as a step toward Artificial General Intelligence (AGI) lets us surface Schön's prescient insight on the crisis of confidence in professionals. Instead of hastily asking questions about how to cope with the advances in artificial intelligence from the gaze of deficit and improvement, however, we resort to the nonrepresentational epistemologies that highlights reflection as seeing as. How might we reconceptualize a professional knowledge model that encourages ethical commitment to enacting practices that deploy relational forces within high-pressure, time-constrained professional environments? We attempt to answer the question by proposing a theory that cultivates conditions for experimenting with experiential encounters with others and creatively activating potentials, which we call generative knowing. Doing so, we suggest how compassionately disruptive condition mobilizes professional learners to engage the machinic creativity that collapses semiotic chains and effectuates diverse imaginations of the future of becoming-with ChatGPT. [ABSTRACT FROM AUTHOR]

This discussion article examines the potential integration of Generative Artificial Intelligence (Gen-AI), including advanced Large-Language Models like the popular platform ChatGPT into subject English education. Following the significant public and academic attention in response to these technologies through 2023, this paper considers the transformative potential and challenges posed by Gen-AI in educational settings. Central to the discussion is the exploration of how English teachers can leverage Gen-AI to enrich student learning beyond the obvious domain of writing skills. Instead, the article foregrounds the necessity for students' understanding of Gen-AI as an essential component of digital literacy. While acknowledging ethical concerns such as plagiarism, equity, and access, the paper presents an argument for the productive use of Gen-AI in the classroom to augment reading, viewing, and interpretation lessons. Avoiding an evangelical or dystopian view of AI, this discussion piece explores the time-critical and urgent issue of how, when, and why English can engage with the technology. [ABSTRACT FROM AUTHOR]

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 workload, 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. [ABSTRACT FROM AUTHOR]

Creativity has long been viewed as the bastion of human expression. With the advent of generative artificial intelligence (AI), there is an emerging notion of artificial creativity that contests traditional perspectives of artistic exploration. This paper explores the complex dynamics of this evolution by examining how generative AI intertwines with and transforms the art world. It presents a comprehensive analysis of the challenges posed by generative AI in art, from questions of authenticity and intellectual property to ethical dilemmas and impacts on conventional art practices. Simultaneously, it investigates the revolutionary opportunities generative AI offers, including the democratization of art creation, the expansion of creative boundaries, and the development of new collaborative and economic models. The paper posits that the integration of generative AI in art is not just a technological advancement but a significant cultural shift, which necessitates a reevaluation of our understanding of art and the artist. It concludes with a forward-looking perspective, advocating for a collaborative approach to harness the potential of this technology in enriching human creativity and ensuring the vibrant evolution of the art world in the era of AI-driven generation. [ABSTRACT FROM AUTHOR]

AbstractThis column shows that Filipino instructors and administrators collectively acknowledge AI as a transformative tool with the potential to enhance teaching, streamline administrative tasks, and boost research productivity. They highlight AI’s benefits in facilitating learning with specific examples, but recognize its limitations, particularly in contextualizing experiences. While they positively regard AI tools at work, they have some concerns such as cheating, data fabrication, and potential decline in creativity and critical thinking. Hence, they emphasize the necessity of regulatory policies and ethical guidelines governing AI use in higher education. They also report whether their home institutions have created AI policies. This column advocates for Philippine educational institutions to reassess their stance on AI’s increasing presence. [ABSTRACT FROM AUTHOR]

This study investigates the utilisation and perceptions of artificial intelligence (AI) applications among mathematics and science teachers in enhancing students’ learning experience in mathematics classrooms. One prominent AI application this research seeks to explore, given its recent rise in popularity and usage, is ChatGPT. The study aims to explore the frequency and purpose of ChatGPT usage, its potential for student engagement, and its implementation’s perceived effectiveness, benefits, and challenges. A sample of 109 respondents was surveyed to gather insights into the usage patterns and perceptions of ChatGPT. The findings shed light on how teachers utilise ChatGPT, including generating examples, assessing difficulty, providing explanations, supporting problem-solving, and test preparation. Additionally, the study reveals that ChatGPT shows promise in enhancing student engagement and understanding. However, respondents highlighted challenges such as accuracy, connectivity, and language limitations. These findings contribute to our understanding of the role of AI technologies, specifically ChatGPT, in mathematics and science educational settings and provide valuable insights for the effective integration of AI in teaching and learning practices in various course contents and topics. [ABSTRACT FROM AUTHOR]

Machine learning has been widely used in design activities, enabling more informed decision-making. However, high-performance machine learning models, often referred to as ‘black-box', result in a lack of explainability regarding predictions. The absence of explainability erodes the trust between designers and these models and hinders human-machine collaboration for desirable design decisions. Explainable AI focuses on creating explanations that are accessible and comprehensible to stakeholders, thereby improving explainability. A recent advancement in the field of explainable AI involves leveraging domain-specific knowledge via knowledge graph. Additionally, the advent of large language models like ChatGPT, acclaimed for their ability to output domain knowledge, perform complex language processing, and support seamless end-user interaction, has the potential to expand the horizons of explainable AI. Inspired by these developments, we propose the novel hybrid method that synergizes ChatGPT and knowledge graph to augment post-hoc explainability in design context. The outcome is the generation of more contextual and meaningful explanations, with the added possibility of further interaction to uncover deeper insights. The effectiveness of the proposed method is illustrated through a case study on customer segmentation. [ABSTRACT FROM AUTHOR]

Developing countries face challenges in AI integration into learning initiatives. With the widespread use of ChatGPT, many concerns were expressed. Thus, it is crucial to investigate students' attitudes toward ChatGPT and the factors influencing their decision to continue using it in the future. We used a mixed-methods triangulation design based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and collected data based on convenience sampling from N = 195 engineering students in developing countries through semi-structured surveys with open-ended questions. Quantitative analysis included descriptive statistics and logistic regression, while thematic analysis was used for the qualitative part. Most students (89.69%) use ChatGPT, with all the elements of the UTAUT framework being strong predictors of their intention to continue. Most have continuous internet access and feel comfortable using technology. High-frequency usage, perceived benefits, and peer encouragement positively influence students' intention to continue using ChatGPT. However, concerns about accuracy, privacy, and laziness negatively correlate with usage intention. Address personal, institutional, and governmental concerns to integrate ChatGPT safely in educational systems, ensuring equitable access and preparing for future e-learning initiatives. [ABSTRACT FROM AUTHOR]

The lived experience of students in their interaction with ChatGPT is underexplored. We conducted qualitative, semi-structured interviews with management students, who recently graduated, to explore their lived experiences and perceptions of using ChatGPT during their studies. Insights gained from the thematic analysis indicate positive perceptions of individual use of ChatGPT. Perceptions were mixed in relation to peers’ use of ChatGPT, especially during group work, where members’ “inappropriate” use of ChatGPT can lead to academic misconduct affecting all group members. Three themes emerged from our analysis: immediacy, equity, and integrity. The use of ChatGPT is driven by its immediate reassurance and validation properties, and for its potential to augment performance and creativity. Participants expressed concerns regarding equitable access to software and the risk of devaluing future degrees in the eyes of employers. Integrity was seen and articulated as problematic in the absence of institutional transparency and clear policy. These findings inform our discussion and recommendations – for the use of ChatGPT by students; for learning and teaching at module and programme level; and for policy development. The study contributes to the growing body of literature related to ChatGPT in higher education and emphasises the need to focus on student voice first. [ABSTRACT FROM AUTHOR]

AbstractThis systematic review explores the limitations and opportunities associated with ChatGPT's application across various fields. Following a rigorous screening process of 485 studies identified through searches in Scopus, Web of Science, ERIC, and IEEE Xplore databases, 33 high-quality empirical studies were selected for analysis. The review identifies five key limitations: accuracy and reliability concerns, limitations in critical thinking and problem-solving, multifaceted impacts on learning and development, technical constraints related to input and output, and ethical, legal, and privacy concerns. However, the review also highlights five exciting opportunities: educational support and skill development, workflow enhancement, information retrieval, natural language interaction and assistance, and content creation and ideation. While this review provides valuable insights, it also highlights some gaps. Limited transparency in the studies regarding specific ChatGPT versions used hinders generalizability. Additionally, the extent to which these findings can be transferred to more advanced models like ChatGPT-4 remains unclear. By acknowledging both limitations and opportunities, this review offers a foundation for researchers, developers, and practitioners to consider when exploring the potential and responsible application of ChatGPT and similar evolving AI tools. [ABSTRACT FROM AUTHOR]

AbstractThis inquiry unveiled the potential of ChatGPT as a viable alternative to traditional citation generator. Findings showed the substantial potential and reliability of the chatbot as a citation formatting tool. Notably, the study revealed ChatGPT’s remarkable accuracy in configuring reference citations for journal articles and books across a range of styles, including APA 7, MLA 9, IEEE, and Harvard. Furthermore, the tool demonstrated proficiency in organizing in-text citations for multiple references. Despite the commendable performance of ChatGPT, manual editing remains essential for the final verification of the references to ensure the utmost accuracy and credibility of sourced materials. [ABSTRACT FROM AUTHOR]

The public release of ChatGPT in November 2022 brought excitement and concerns regarding students' use of language models in higher education. However, little research has empirically investigated students' intention to adopt ChatGPT. This study developed a theoretical model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) with an additional construct- anxiety, to investigate university students' adoption intention of ChatGPT in two higher education contexts– the UK and Nepal. 239 and 226 questionnaires were deemed sufficient for data analysis for Nepal and the UK, respectively. We utilised the structural equation modelling technique to test the hypotheses. Our results reveal that performance expectancy, effort expectancy and social influence significantly impacted the adoption intention of ChatGPT for both countries. However, anxiety's impact varied between Nepal and the UK. Integrating UTAUT with a cross-country comparative approach provides insights into how ChatGPT's reception diverges between different higher education contexts. Our results also have implications for technology companies aiming to expand language models' availability worldwide. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) may be the new-new-norm in a post-pandemic learning environment. There is a growing number of university students using AI like ChatGPT and Bard to support their academic experience. Much of the AI in higher education research to date has focused on academic integrity and matters of authorship; yet, there may be unintended consequences beyond these concerns for students. That is, there may be people who reduce their formal social interactions while using these tools. This study evaluates 387 university students and their relationship to – and with – artificial intelligence large-language model-based tools. Using structural equation modelling, the study finds evidence that while AI chatbots designed for information provision may be associated with student performance, when social support, psychological wellbeing, loneliness, and sense of belonging are considered it has a net negative effect on achievement. This study tests an AI-specific form of social support, and the cost it may pose to student success, wellbeing, and retention. Indeed, while AI chatbot usage may be associated with poorer social outcomes, human-substitution activity that may be occurring when a student chooses to seek support from an AI rather than a human (e.g. a librarian, professor, or student advisor) may pose interesting learning and teaching policy implications. We explore the implications of this from the lens of student success and belonging. [ABSTRACT FROM AUTHOR]

The quantitative and qualitative performance analysis of ChatGPT-3.0, a large language model, is carried out on three important and highly competitive examinations held in India: civil services examination (CSE, prelims), graduate aptitude test in engineering (GATE), and joint entrance examination (JEE). These examinations cover general knowledge, current affairs, history, geography, Indian polity, economics, mathematics, physics, chemistry, engineering, and technology aspects at the undergraduate and graduate levels. The Accuracy, Concordance, and Insight (ACI) criteria is used to analyze the performance of ChatGPT. ChatGPT passed CSE without much specialized training and reinforcement, however, underperformed in GATE and JEE. Overall, the average accuracy rate of ChatGPT is 48.71%, with a 44.45% concordance for all explanations. However, the concordance for accurate explanations is found to be 91.87% with a high level of insights given in the explanations. Moreover, the average accuracy of ChatGPT improves to 77.69% after training. The results suggest that large language models have great potential to assist with education technology and act as an instructor for the preparation of technical, aptitude and general studies topics for competitive examinations. Drawing insights from the findings of the current research, some limitations in the present study and possible future research directions are suggested. [ABSTRACT FROM AUTHOR]

Large language models such as ChatGPT can be seen as a major threat to reliable assessment in higher education. In this point of departure, I argue that these tools are a major game changer for society at large. Many of the jobs we now consider highly skilled are based on pattern recognition that can much more reliably be carried by fine-tuned language models. We are therefore at a turning point in history and it affords a powerful opportunity to reconsider the value of higher education in the light of these tools. [ABSTRACT FROM AUTHOR]

To explore the use of ChatGPT by educators and students in a medical school setting. This study used the public version of ChatGPT launched by OpenAI on November 30, 2022 (). We employed prompts to ask ChatGPT to 1) generate a content outline for a session on the topics of cholesterol, lipoproteins, and hyperlipidemia for medical students; 2) produce a list of learning objectives for the session; and 3) write assessment questions with and without clinical vignettes related to the identified learning objectives. We assessed the responses by ChatGPT for accuracy and reliability to determine the potential of the chatbot as an aid to educators and as a "know-it-all" medical information provider for students. ChatGPT can function as an aid to educators, but it is not yet suitable as a reliable information resource for educators and medical students. ChatGPT can be a useful tool to assist medical educators in drafting course and session content outlines and create assessment questions. At the same time, caution must be taken as ChatGPT is prone to providing incorrect information; expert oversight and caution are necessary to ensure the information generated is accurate and beneficial to students. Therefore, it is premature for medical students to use the current version of ChatGPT as a "know-it-all" information provider. In the future, medical educators should work with programming experts to explore and grow the full potential of AI in medical education. [ABSTRACT FROM AUTHOR]

AbstractDrawing inspiration from Michail Bakhtin’s philosophy, this study introduces the Polyphonic Model, grounded in the Bakhtinian principles of dialogue and polyphony. These principles emphasise the multiplicity of perspectives and the dynamic, dialogic interplay of various subjective consciousnesses, reflecting the inherent diversity of human thought. This theoretical foundation informs our analytical tool and conceptual framework, enabling an exploration of the recursive and cyclical dialogues between AI and its stakeholders, including AI itself as a non-human participant. Distinctively, the Polyphonic Model’s strength lies not merely in its capacity to highlight the multiplicity of these voices – as many preceding models have – but in its emphasis on the recursive, cyclic nature of the dialogic relationships and a dynamic interchange that continuously reshapes both the AI and its users, especially evident in the temporal transformations. The exploration asserts AI itself as a non-human stakeholder, contributing to and being molded by the very discourses that seek to understand it. While analyzing seventeen diverse stakeholders using ChatGPT as an illustrative context, the exploration zeroes in on two: the non-human stakeholder, exemplified by ChatGPT 4, and its users. Through an innovative methodological approach – an interview with ChatGPT 4 and a sentiment analysis of tweets from its early adopters powered by a lexicon-based approach and a machine learning method, along with Latent Dirichlet Allocation (LDA) for topic modelling – this study examines the dialogic relationships between stakeholders. The findings solidify the Polyphonic Model’s potential not only as an analytical tool but also as a blueprint for the holistic evaluation of AI-powered products. The scope of this study is confined to the development and societal integration of ChatGPT, as a representative example of advanced language processing AI technologies. [ABSTRACT FROM AUTHOR]

AbstractThis essay concerns the pervasive “problem” of plagiarism in student writing, arguing against the easy adoption of technological policing “solutions” that may themselves contribute to an erosion of authentic learning and knowledge production. The paper critically examines the key tool, or weapon, in the war against plagiarism, namely the educational software Turnitin, and some of the discontent that has arisen in consequence of its widespread adoption in academic institutions. The second part of the essay examines practices of literary plagiarism, using the example of Shakespeare and Coetzee to question notions of originality. Both writers, one from the Renaissance, the other from contemporary literature, will serve as illustrative bookends for the English literary canon as a whole, exemplifying the close relationship between copying and creativity. These ideas are applied to the concept of a “knowledge commons,” which is indispensable to the idea of a good university, and which is being crowded out by inflated discourses of plagiarism and an overreach of plagiarism policing in the academy. Lastly, the essay briefly offers a few practical and pedagogic observations. [ABSTRACT FROM AUTHOR]

Many observed that the rise of GenAI is causing an ‘erosion of trust’ between students and teachers in higher education. Such distrust mainly stems from concerns about student cheating, which is believed to be massively facilitated by recent technological breakthroughs in GenAI. Despite anecdotal discussions, little empirical research has explored students’ experiences with trust in the GenAI age. This study engaged university students in concept mapping activities followed by interviews to investigate how they navigate trust-building with teachers in this AI-mediated assessment landscape. The findings highlight an absence of ‘two-way transparency’ – while students are required to declare their AI use and even submit chat records, the same level of transparency is often not observed from the teachers (e.g. ambiguities around teachers’ grading process of AI-mediated work). The transparency issue reinforces teacher-student power imbalances and top-down surveillance mechanisms, resulting in a low-trust environment where students feel unsafe to freely explore GenAI use. [ABSTRACT FROM AUTHOR]

AbstractThe integration of Artificial Intelligence (AI) technologies in the field of education has prompted significant advancements, particularly in the domain of assessment and grading. This research delves into the potential of large language models, specifically OpenAI's ChatGPT, in simulating human-like interactions and accurately grading student assessments. To accomplish its objectives, the study compares the grading performance of ChatGPT with that of human correctors in a sample of second-year university students. The research findings indicate only a moderate correlation between the grades assigned by ChatGPT and those of human correctors, suggesting nuanced capabilities in providing comprehensive feedback and streamlining the grading process. While the study highlights the benefits of AI integration in education, it also addresses potential risks, including the exacerbation of educational inequalities and the limitations associated with AI's automated nature. This research contributes to the ongoing discourse surrounding AI's role in education, emphasizing the importance of striking a balance between AI and human instruction for optimal educational outcomes. [ABSTRACT FROM AUTHOR]

AbstractChatGPT, a cutting-edge artificial intelligence (AI) tool with the potential to transform education, has gained global recognition. Learners’ attitudes toward new technologies significantly influence their use of AI tools, such as ChatGPT. However, variable-centered studies struggle to fully capture potential heterogeneity attitudes. This study employed a person-centered approach (latent profile analysis) and thematic analysis to uncover students’ attitudes and behavioral intentions regarding ChatGPT. Utilizing a meticulous stratified random sampling approach, this study conducted a mixed-method study based on representative data from 850 Chinese university students, revealing three profiles: Positive Embracers, Cautious Rational Optimism, and Complex Attitudinal Profile. Of the participants, 80.2% showed Cautious Rational Optimism profile, where Positive Embracers showed notably higher ChatGPT intentions. These findings emphasize the need for multidimensional approaches when studying university students’ ChatGPT attitudes. This study is the first to explore and uncover attitude diversity, offering new directions and strong evidence for future research and education. [ABSTRACT FROM AUTHOR]

AbstractChatGPT and other AI chat information retrieval and processing service systems can deal with many problems, which are crucial for users, yet current research lacks depth in user experience. And those studies predominantly focus on positive aspects of user intention, which have a large limitation. Against this backdrop, this study, framed by Behavioral Reasoning Theory, utilizes factor analysis and linear regression to create a comprehensive user intention evaluation scale and model. The eight-factor evaluation scale, shaped by user values, includes supporting reasons like usefulness, convenience, growth, and interactivity, and inhibiting factors such as inaccuracy, semantic rigidity, security risk, and cognitive limitation. Attitude serves as an intermediary, positively affected by supporting factors and negatively influenced by inhibiting ones. Core factors impacting user intention are convenience, cognitive limitation, and security risk. This research not only bridges existing gaps but also lays a theoretical foundation for related industries. [ABSTRACT FROM AUTHOR]

The Thomas Mahaffey Jr. Business Library conducted a study to assess the performance of two competing generative AI products, ChatGPT and Perplexity AI, in answering business reference questions. The study used a data set consisting of a sample of anonymized reference questions submitted through the library's ServiceNow ticketing system between January 2018 and May 2022. The questions were input as prompts to each competing AI. Responses were collected and evaluated by their performance in four separate dimensions relevant to business reference: accessibility, library referral, quality, and serendipity. Each dimension was scored on a 0-5 Likert scale resulting in a final composite performance score for each AI. Results showed similar and underwhelming performance between each AI at the composite level. Analysis of scores in each individual scoring dimension showed greater variance in the score distributions between the competing AI. Through the evaluation process, key strengths, weaknesses, and trends emerged between each AI. The study provides a quantitative measure of where generative AI stands in its capabilities in a business library reference context, and it recommends, based on the results of the evaluation, making use of generative AI in its current iteration as a supplementary tool for business reference as opposed to considering it as a replacement. [ABSTRACT FROM AUTHOR]

AbstractGenerative AI tools, like ChatGPT, have ignited global discussions and debates about potential educational impacts. By examining initial reactions to ChatGPT shared in online spaces, this study aims to deepen understanding of opportunities and concerns related to integrating such tools into education. With the keyword “chatgpt,” we searched 25 education-related subreddits on Reddit and conducted a content analysis of 7,009 posts and comments, identifying 4,397 containing reactions to the tool. Findings showed that initial ChatGPT discussions predominantly focused on perceived threats and educational applications, much less on strengths, weaknesses, and opportunities—although the discussions were multifaceted, nuanced, and contextualized. [ABSTRACT FROM AUTHOR]

AbstractIn this study, an online contextualized educational game was designed to provide interactive simulated dialogues using generative AI scaffolding (using ChatPDF) in a contextualized game as scaffolding for immediate feedback, where learners can access guides and explore knowledge. This study analyzed learners’ behaviors while performing AI prompting in the interactive scaffolding, as well as learners’ psychological responses. A total of 59 students participated in this study. The results of the study showed that learners had significantly high flow and low activity anxiety in the game tasks, while game feedback and scaffolding usefulness had significant effects on learning aids. The generative AI instant feedback interactive scaffolding had a certain high percentage of direct answers or indirect suggestions, which is suitable for interactive scaffolding. [ABSTRACT FROM AUTHOR]

This study investigates the integration of artificial intelligence (AI) tools, such as ChatGPT, into English as a Foreign Language (EFL) teacher learning, aiming to transcend the traditional, test-centric constraints of language education through inquiry-based learning (IBL). Conducted over a semester, the research involved thirteen in-service teachers who engaged in crafting lesson plans, executing microteaching sessions, and documenting their reflections. These qualitative data sources provided insights into how AI can enhance language teaching by personalizing content and supporting the development of communicative skills. The analysis through thematic analysis revealed that AI technologies empowered teachers to design interactive and adaptive learning materials, including picture books and karaoke exercises, thereby fostering a more dynamic and student-centered learning environment. In-service teachers noted that the adaptability of AI tools not only facilitated the creation of compelling lessons but also significantly improved students’ listening and speaking skills. The findings advocate for the strategic incorporation of AI in EFL teaching, suggesting that such technologies can lead to innovative pedagogical approaches that are attuned to the diverse needs of learners. This study underscores the potential of AI to revolutionize language education. [ABSTRACT FROM AUTHOR]

Generative Artificial Intelligence (AI) provides unprecedented opportunities to improve injury surveillance systems in many ways, including the curation and publication of information related to agricultural injuries and illnesses. This editorial explores the feasibility and implication of ChatGPT integration in an international sentinel agricultural injury surveillance system, AgInjuryNews, highlighting that AI integration may enhance workflows by reducing human and financial resources and increasing outputs. In the coming years, text intensive natural language reports in AgInjuryNews and similar systems could be a rich source for data for ChatGPT or other more customized and fine-tuned LLMs. By harnessing the capabilities of AI and NLP, teams could potentially streamline the process of data analysis, report generation, and public dissemination, ultimately contributing to improved agricultural injury prevention efforts, well beyond any manually driven efforts. [ABSTRACT FROM AUTHOR]

Communication programs seek to cultivate students who become professionals not only with expertise in their chosen field, but also ethical awareness. The current study investigates how exposure to ethics instruction and internship experiences may influence communication students' ethical perceptions, including ideological orientations on idealism and relativism, as well as awareness of contemporary ethical issues related to social media and artificial intelligence (AI). The effects were also assessed on students' support for general uses of AI for communication practices and adoption of generative AI, specifically ChatGPT. The survey results based on a student sample in Taiwan show that internship experience is more significant than ethics instruction on swaying ethical perceptions and behavioral inclinations of adopting AI applications. Adding to the limited body of knowledge on the effect of ethics education and internship programs, the findings also offer insights for how communication education can address emerging ethical challenges brought by new technology. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper examines the potential impact of AI-based language models on education, with a specific focus on the ChatGPT model developed by OpenAI. The study begins by providing an overview of the current state of AI in education, including the challenges and opportunities presented by these models. It then delves into an analysis of ChatGPT, including its capabilities, strengths and limitations. The paper also conducts a thorough analysis of potential implications and offers suggestions for assessment design to prevent students from utilising AI-based language models in educational environments. Finally, the paper concludes with a set of recommendations for assessment design, considering the specific characteristics of ChatGPT and the potential impact of AI-based language models on tourism education. [ABSTRACT FROM AUTHOR]