PT AU BA BE GP AF BF CA TI SO SE BS LA DT CT CY CL SP HO DE ID AB C1 C3 RP EM RI OI FU FP FX CR NR TC Z9 U1 U2 PU PI PA SN EI BN J9 JI PD PY VL IS PN SU SI MA BP EP AR DI DL D2 EA PG WC WE SC GA PM OA HC HP DA UT C Sioziou, K; Zervas, P; Giotopoulos, K; Tzimas, G Maglogiannis, I; Iliadis, L; Papaleonidas, A; Pimenidis, E; Jayne, C Sioziou, Kyriaki; Zervas, Panagiotis; Giotopoulos, Kostas; Tzimas, Giannis Comparative Analysis of Large Language Models in Structured Information Extraction from Job Postings ENGINEERING APPLICATIONS OF NEURAL NETWORKS, EANN 2024 Communications in Computer and Information Science 25th International Conference on Engineering Applications of Neural Networks (EANN) JUN 27-30, 2024 Corfu, GREECE The recent progress in Large Language Models has opened up new possibilities for their application in different domains. This study focuses on exploring the potential of LLMs in structured information extraction, specifically in the context of job postings. We compare commercial and open-source LLMs to see how well they can extract key information from job postings in Greece's tourism sector. Our goal is to understand the performance differences between these models and assess their general applicability in real-world information extraction tasks. We aim to evaluate and compare the capability of these models in accurately identifying and extracting specific data points such as Job Title, Company, Industry, Location, Soft Skills, and Hard Skills. This research contributes to our understanding of how practical LLMs are in real-world information extraction tasks and highlights the differences in performance among various state-of-the-art models. Tzimas, Giannis/R-5550-2019; Giotopoulos, Konstantinos/HLW-1225-2023 1865-0929 1865-0937 978-3-031-62494-0; 978-3-031-62495-7 2024 2141 82 92 10.1007/978-3-031-62495-7_7 http://dx.doi.org/10.1007/978-3-031-62495-7_7 WOS:001295254400007 J Palmer, A; Spirling, A Palmer, Alexis; Spirling, Arthur Large Language Models Can Argue in Convincing Ways About Politics, But Humans Dislike AI Authors: implications for Governance POLITICAL SCIENCE All politics relies on rhetorical appeals, and the ability to make arguments is considered perhaps uniquely human. But as recent times have seen successful large language model (LLM) applications to similar endeavours, we explore whether these approaches can out-compete humans in making appeals for/against various positions in US politics. We curate responses from crowdsourced workers and an LLM and place them in competition with one another. Human (crowd) judges make decisions about the relative strength of their (human v machine) efforts. We have several empirical 'possibility' results. First, LLMs can produce novel arguments that convince independent judges at least on a par with human efforts. Yet when informed about an orator's true identity, judges show a preference for human over LLM arguments. This may suggest voters view such models as potentially dangerous; we think politicians should be aware of related 'liar's dividend' concerns. 0032-3187 2041-0611 SEP 2 2023 75 3 281 291 10.1080/00323187.2024.2335471 http://dx.doi.org/10.1080/00323187.2024.2335471 APR 2024 WOS:001204599400001 C Song, IHJ; Wang, JY; Sunico, R; Dahlstrom, A IEEE Song, Isabel Hyo Jung; Wang, Jingyi; Sunico, Rafael; Dahlstrom, Andrew WIP:Enhancing Career Preparedness Through a Software Engineering Capstone Course Design 2024 IEEE FRONTIERS IN EDUCATION CONFERENCE, FIE Frontiers in Education Conference 2024 Frontiers in Education Conference OCT 13-16, 2024 Washington, DC This research to practice WIP paper describes capstone projects in software engineering which effectively combine theoretical education with practical skills, fostering career development in alignment with Career Construction Theory (CCT). This paper introduces a course designed to enhance students' career readiness by incorporating Agile methodologies for soft skills development, proficiency in modern technologies like Large Language Models (LLMs), and targeted career preparation such as resume building. The course's effectiveness, evaluated through CCT adaptability for 42 students, shows a positive impact on career preparedness in three of the four dimensions. This is the first attempt to measure the impact of a capstone course on career development using CCT adaptability. While the initial results are promising, further research is crucial to fully enhance all dimensions of CCT adaptability and to explore the scalability of this study across other engineering fields, potentially transforming engineering education and career preparation on a broader scale. 0190-5848 979-8-3503-6306-7; 979-8-3503-5150-7 2024 10.1109/FIE61694.2024.10893284 http://dx.doi.org/10.1109/FIE61694.2024.10893284 WOS:001447128100330 J Frank, MC Frank, Michael C. Openly accessible LLMs can help us to understand human cognition NATURE HUMAN BEHAVIOUR Large language models can be construed as 'cognitive models', scientific artefacts that help us to understand the human mind. If made openly accessible, they may provide a valuable model system for studying the emergence of language, reasoning and other uniquely human behaviours. Frank, Michael/0000-0002-7551-4378 2397-3374 2023 NOV 20 2023 10.1038/s41562-023-01732-4 http://dx.doi.org/10.1038/s41562-023-01732-4 NOV 2023 37985910 WOS:001107579600010 J Jacobs, OL; Pazhoohi, F; Kingstone, A Jacobs, Oliver L.; Pazhoohi, Farid; Kingstone, Alan Large language models have divergent effects on self-perceptions of mind and the attributes considered uniquely human CONSCIOUSNESS AND COGNITION The rise of powerful Large Language Models (LLMs) provides a compelling opportunity to investigate the consequences of anthropomorphism, particularly regarding how their exposure may influence the way individuals view themselves (self-perception) and other people (other-perception). Using a mind perception framework, we examined attributions of agency (the ability to do) and experience (the ability to feel). Participants evaluated their agentic and experiential capabilities and the extent to which these features are uniquely human before and after exposure to LLM responses. Post-exposure, participants increased evaluations of their agentic and experiential qualities while decreasing their perception that agency and experience are considered to be uniquely human. These results indicate that anthropomorphizing LLMs impacts attributions of mind for humans in fundamentally divergent ways: enhancing the perception of one's own mind while reducing its uniqueness for others. These results open up a range of future questions regarding how anthropomorphism can affect mind perception toward humans. 1053-8100 1090-2376 SEP 2024 124 103733 10.1016/j.concog.2024.103733 http://dx.doi.org/10.1016/j.concog.2024.103733 AUG 2024 39116598 WOS:001291042600001 C Li, ZM; Babar, PP; Barry, M; Peiris, RL ASSOC COMPUTING MACHINERY Li, Ziming; Babar, Pinaki Prasanna; Barry, Mike; Peiris, Roshan L. Exploring the Use of Large Language Model-Driven Chatbots in Virtual Reality to Train Autistic Individuals in Job Communication Skills EXTENDED ABSTRACTS OF THE 2024 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2024 CHI Conference on Human Factors in Computing Sytems (CHI) MAY 11-16, 2024 Honolulu, HI Assoc Comp Machinery, ACM SIGCHI, Apple, Google, NSF, Tianqiao & Chrissy Chen Inst Autistic individuals commonly encounter challenges in communicating with others which can lead to difficulties in obtaining and maintaining jobs. Thus, job training programs have emphasized training the communication skills of autistic individuals to improve their employability. Hence, we developed a virtual reality application that features avatars as chatbots powered by Large Language Models (LLMs), such as GPT-3.5 Turbo, and employs speech-based interactions with users. The use of LLM-driven chatbots allows job coaches to create training scenarios for trainees using text prompts. We conducted a preliminary study with three autistic trainees and two job coaches to gather early-stage feedback on the application's usability and user experience. In the study, the trainee participants were asked to interact with the application in two scenarios involving customer interactions. Our findings indicate that our application shows promise for training job communication. Furthermore, we discuss its user experience aspects from the trainees' and job coaches' perspectives. Peiris, Roshan Lalintha/0000-0002-4191-3565; Li, Ziming/0000-0003-4302-9949 979-8-4007-0331-7 2024 10.1145/3613905.3651996 http://dx.doi.org/10.1145/3613905.3651996 WOS:001227587704100 C Malandri, L; Mercorio, F; Serino, A ACM Malandri, Lorenzo; Mercorio, Fabio; Serino, Antonio SkiLLMo: Normalized ESCO Skill Extraction through Transformer Models 40TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING 40th Symposium on Applied Computing-SAC MAR 31-APR 04, 2025 Catania, ITALY ACM SIGAPP In recent years, natural language processing (NLP) technologies have made a significant contribution in addressing a number of labour market tasks. One of the most interesting challenges is the automatic extraction of competences from unstructured texts. This paper presents a pipeline for efficiently extracting and standardizing skills from job advertisements using NLP techniques. The proposed methodology leverages open-source Transformer and Large Language Models to extract skills and map them to the European labour market taxonomy, ESCO. To address the computational challenges of processing lengthy job advertisements, a BERT model was fine-tuned to identify text segments likely containing skills. This filtering step reduces noise and ensures that only relevant content is processed further. The filtered text is then passed to an LLM, which extracts implicit and explicit hard and soft skills through prompt engineering. The extracted skills are subsequently matched with entries in a vector store containing the ESCO taxonomy to achieve standardization. Evaluation by domain experts shows that the pipeline achieves a precision of 91% for skill extraction, 80% for skill standardization and a combined overall precision of 79%. These results demonstrate the effectiveness of the proposed approach in facilitating structured and standardized skill extraction from job postings. Mercorio, Fabio/E-4369-2013 979-8-4007-0629-5 2025 1969 1976 10.1145/3672608.3707960 http://dx.doi.org/10.1145/3672608.3707960 WOS:001497934400263 J Abi-Rafeh, J; Xu, HH; Kazan, R; Tevlin, R; Furnas, H Abi-Rafeh, Jad; Xu, Hong Hao; Kazan, Roy; Tevlin, Ruth; Furnas, Heather Large Language Models and Artificial Intelligence: A Primer for Plastic Surgeons on the Demonstrated and Potential Applications, Promises, and Limitations of ChatGPT AESTHETIC SURGERY JOURNAL Background The rapidly evolving field of artificial intelligence (AI) holds great potential for plastic surgeons. ChatGPT, a recently released AI large language model (LLM), promises applications across many disciplines, including healthcare.Objectives The aim of this article was to provide a primer for plastic surgeons on AI, LLM, and ChatGPT, including an analysis of current demonstrated and proposed clinical applications.Methods A systematic review was performed identifying medical and surgical literature on ChatGPT's proposed clinical applications. Variables assessed included applications investigated, command tasks provided, user input information, AI-emulated human skills, output validation, and reported limitations.Results The analysis included 175 articles reporting on 13 plastic surgery applications and 116 additional clinical applications, categorized by field and purpose. Thirty-four applications within plastic surgery are thus proposed, with relevance to different target audiences, including attending plastic surgeons (n = 17, 50%), trainees/educators (n = 8, 24.0%), researchers/scholars (n = 7, 21%), and patients (n = 2, 6%). The 15 identified limitations of ChatGPT were categorized by training data, algorithm, and ethical considerations.Conclusions Widespread use of ChatGPT in plastic surgery will depend on rigorous research of proposed applications to validate performance and address limitations. This systemic review aims to guide research, development, and regulation to safely adopt AI in plastic surgery. 宏浩, 徐/HKE-7858-2023 Abi-Rafeh, Jad/0000-0002-7483-1515 1090-820X 1527-330X FEB 15 2024 44 3 329 343 10.1093/asj/sjad260 http://dx.doi.org/10.1093/asj/sjad260 SEP 2023 37562022 WOS:001066826600001 J Sorin, V; Brin, D; Barash, Y; Konen, E; Charney, A; Nadkarni, G; Klang, E Sorin, Vera; Brin, Dana; Barash, Yiftach; Konen, Eli; Charney, Alexander; Nadkarni, Girish; Klang, Eyal Large Language Models and Empathy: Systematic Review JOURNAL OF MEDICAL INTERNET RESEARCH Background: Empathy, a fundamental aspect of human interaction, is characterized as the ability to experience another being's emotions within oneself. In health care, empathy is a fundamental for health care professionals and patients' interaction. It is a unique quality to humans that large language models (LLMs) are believed to lack. Objective: We aimed to review the literature on the capacity of LLMs in demonstrating empathy. Methods: We conducted a literature search on MEDLINE, Google Scholar, PsyArXiv, medRxiv, and arXiv between December 2022 and February 2024. We included English-language full-length publications that evaluated empathy in LLMs' outputs. We excluded papers evaluating other topics related to emotional intelligence that were not specifically empathy. The included studies' results, including the LLMs used, performance in empathy tasks, and limitations of the models, along with studies' metadata were summarized. Results: A total of 12 studies published in 2023 met the inclusion criteria. ChatGPT-3.5 (OpenAI) was evaluated in all studies, with 6 studies comparing it with other LLMs such GPT-4, LLaMA (Meta), and fine-tuned chatbots. Seven studies focused on empathy within a medical context. The studies reported LLMs to exhibit elements of empathy, including emotions recognition and emotional support in diverse contexts. Evaluation metric included automatic metrics such as Recall-Oriented Understudy for Gisting Evaluation and Bilingual Evaluation Understudy, and human subjective evaluation. Some studies compared performance on empathy with humans, while others compared between different models. In some cases, LLMs were observed to outperform humans in empathy-related tasks. For example, ChatGPT-3.5 was evaluated for its responses to patients' questions from social media, where ChatGPT's responses were preferred over those of humans in 78.6% of cases. Other studies used subjective readers' assigned scores. One study reported a mean empathy score of 1.84-1.9 (scale 0-2) for their fine-tuned LLM, while a different study evaluating ChatGPT-based chatbots reported a mean human rating of 3.43 out of 4 for empathetic responses. Other evaluations were based on the level of the emotional awareness scale, which was reported to be higher for ChatGPT-3.5 than for humans. Another study evaluated ChatGPT and GPT-4 on soft-skills questions in the United States Medical Licensing Examination, where GPT-4 answered 90% of questions correctly. Limitations were noted, including repetitive use of empathic phrases, difficulty following initial instructions, overly lengthy responses, sensitivity to prompts, and overall subjective evaluation metrics influenced Conclusions: LLMs exhibit elements of cognitive empathy, recognizing emotions and providing emotionally supportive responses in various contexts. Since social skills are an integral part of intelligence, these advancements bring LLMs closer to room for improvement in both the performance of these models and the evaluation strategies used for assessing soft skills. ; mirzaei, hamed/X-2374-2018; Sorin, Vera/IAR-4247-2023; Barash, Yiftach/MCK-5975-2025; Brin, Dana/MVU-5184-2025 Brin, Dana/0009-0003-7316-206X; Sorin, Vera/0000-0003-0509-4686; Barash, Yiftach/0000-0002-7242-1328; 1438-8871 DEC 11 2024 26 e52597 10.2196/52597 http://dx.doi.org/10.2196/52597 39661968 WOS:001382690300002 J Burgess, P; Williams, I; Qu, LZ; Wang, WQ Burgess, Paul; Williams, Iwan; Qu, Lizhen; Wang, Weiqing Using Generative AI to Identify Arguments in Judges' Reasons: Accuracy and Benefits for Students LAW TECHNOLOGY AND HUMANS This study evaluates the effectiveness of generative artificial intelligence (GAI) in identifying and reconstructing legal arguments from judges' reasons in court cases, focusing on the practical implications for law students and legal educators. By examining the performance of two versions of popular Large Language Models - ChatGPT and Claude - across five recent High Court of Australia decisions, the study makes a preliminary assessment of the accuracy of LLM systems in replicating a skill essential for l awyers: identification of arguments and argument chains in judges' reasons. The methodology involves marking LLM-generated outputs with reference to both a sample answer and a detailed rubric. Key findings reveal a significant variance in the accuracy of different LLMs, with Claude 3.5 markedly outperforming all others, achieving average grades up to 90 per cent. In contrast, ChatGPT versions demonstrated lower accuracy, with average marks not exceeding 50 per cent. These results highlight the critical importance of selecting the right GAI system for legal applications, as well as the necessity for users to critically engage with AI outputs rather than relying solely on automated tools. The study concludes that while LLMs hold potential benefits for the legal profession, including increased efficiency and enhanced access to justice, for GAI use that may be carried out by a law student, the technology cannot yet replace the nuanced human skill of legal argument analysis. Qu, Lizhen/0000-0002-7764-431X; Burgess, Paul/0000-0002-5674-1735; Williams, Iwan/0000-0003-0582-0983; Wang, Weiqing/0000-0002-9578-819X 2652-4074 2024 6 3 5 22 10.5204/lthj.3637 http://dx.doi.org/10.5204/lthj.3637 WOS:001368158500001 J O'Halloran, K O'Halloran, Kieran Digital assemblages with AI for creative interpretation of short stories DIGITAL SCHOLARSHIP IN THE HUMANITIES I demonstrate an approach fostering inventive interpretation of short stories in Literary Studies and higher education generally. It involves constructing an 'assemblage'-at its simplest, an evolving network of unusual connections for creative outcome. The assemblage of this article combines freshly located research literature, directly and indirectly related to a story's themes, and/or the personality type of protagonists. Importantly, this assemblage also utilizes text analysis software revealing the relatively invisible (e.g. (in)frequent words, parts of speech, and topics) and Large Language Model (LLM) Generative AI to enrich the interpretation. The use of all these elements helps productively exceed initial intuitions about the story, facilitating creativity. I model the approach using Edgar Allan Poe's short story, The Black Cat, whose protagonist is a homicidal psychopath. Specifically, the assemblage here includes relevant software-based research (a corpus analysis of homicidal psychopathic language), non-software-based research (psychoanalytical literary criticism of The Black Cat using the empirically validated concept of transference), text analysis software (WMatrix and Datayze), and the LLM Generative AI, 'ChatGPT' (using the freely available LLM GPT-3.5). One use of this approach is as a pedagogy in Literary Studies employing text analysis software (e.g. on a digital stylistics course). Yet given creative adaptability is a key 21st-century skill, with digital literacy-including the use of Generative AI-an important contemporary competence, and with the short story genre universally known, I highlight too the utility of this approach as a university-wide pedagogy for enhancing creative thinking. O'Halloran, Kieran/0000-0003-3424-994X 2055-7671 2055-768X MAR 6 2024 39 2 657 689 10.1093/llc/fqad050 http://dx.doi.org/10.1093/llc/fqad050 MAR 2024 WOS:001179470400001 J Weber, L Weber, Lauren Deep Reading as Resistance: Reading with ChatGPT and Battling SysEd through Reflexive Reading Pedagogy JOURNAL OF LANGUAGE LITERATURE AND CULTURE This paper serves as a theoretical reflection with a practical proposal. There are two core goals for my discussion: (1) to reflect on deep reading for the purposes of education and why it matters in the current context of the study of English; and (2) to support a nuanced approach to promoting deep reading in English by introducing the argument that deep reading may be a form of resistance to two major challenges in English classrooms. These challenges are Semler's articulation of 'SysEd' and the emergence of AI in the form of large language models (LLMs). My reflections on reading are mediated by a conversation with ChatGPT about its reading practice and how English may distinguish the teaching of deep reading as a human skill. Finally, I draw on Margaret Archer's theory of reflexivity to present a practical approach to facilitating deep reading as a form of resistance. ; Weber, Lauren Alexandra/JAC-1507-2023 Weber, Lauren Alexandra/0000-0002-8297-4233; 2051-2856 2051-2864 JAN 2 2024 71 1 SI 57 72 10.1080/20512856.2024.2427567 http://dx.doi.org/10.1080/20512856.2024.2427567 NOV 2024 WOS:001367006600001 C Ashktorab, Z; Bansal, G; Buçinca, Z; Holstein, K; Hullman, J; Smith-Renner, A; Wu, TS; Zhang, WJ ASSOC COMPUTING MACHINERY Ashktorab, Zahra; Bansal, Gagan; Bucinca, Zana; Holstein, Kenneth; Hullman, Jessica; Smith-Renner, Alison; Wu, Tongshuang; Zhang, Wenjuan Trust and Reliance in Evolving Human-AI Workflows (TREW) EXTENDED ABSTRACTS OF THE 2024 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2024 ACM CHI Conference on Human Factors in Computing Sytems (CHI) MAY 11-16, 2024 Honolulu, HI Assoc Comp Machinery, ACM SIGCHI, Apple, Google, NSF, Tianqiao & Chrissy Chen Inst State-of-the-art AIs, including Large Language Models (LLMs) like GPT-4, now possess capabilities once unique to humans, such as coding, idea generation, and planning. Advanced AIs are now integrated into a plethora of platforms and tools, including GitHub Copilot, Bing Chat, Bard, ChatGPT, and Advanced Data Analytics. In contrast to conventional, specialized AIs that typically offer singular solutions, these LLMs redefine human-AI dynamics, with a growing trend toward humans viewing them as collaborative counterparts. This shift leads to enhanced dialogues, negotiations, and task delegation between humans and AI. With these rapid advancements, the nature of human roles in the AI collaboration spectrum is evolving. While our previous workshops CHI TRAIT 2022 and 2023 delved into the trust and reliance concerning traditional AIs, the pressing question now is: how should we measure trust and reliance with these emerging AI technologies? As these systems witness widespread adoption, there's also a need to assess their impact on human skill development. Does AI assistance amplify human skill progression, or does it inadvertently inhibit it? Considering the multifaceted challenges and solutions that revolve around human-AI interactions, we invite experts from diverse fields, including HCI, AI, ML, psychology, and social science. Our aim is to bridge communication gaps and facilitate rich collaborations across these domains. Bansal, Gagan/LZG-0954-2025; Hullman, Jessica/P-7130-2018 Hullman, Jessica/0000-0001-6826-3550; Holstein, Ken/0000-0001-6730-922X 979-8-4007-0331-7 2024 10.1145/3613905.3636319 http://dx.doi.org/10.1145/3613905.3636319 WOS:001227587700053 J Riemer, K; Peter, S Riemer, Kai; Peter, Sandra Conceptualizing generative AI as style engines: Application archetypes and implications INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT The rise of generative AI has brought with it a surprising paradox: systems that excel at tasks once thought to be uniquely human, like fluent conversation or persuasive writing, while simultaneously failing to meet traditional expectations of computing, in terms of reliability, accuracy, and veracity (e.g., given the various issues with socalled 'hallucinations'). We argue that, when generative AI is seen through a traditional computing lens, its development focuses on optimizing for traditional computing traits that remain in principle unattainable. This risks backgrounding what is most novel and defining about it. As probabilistic technologies, generative AIs do not store, in any traditional sense, any data or content. Rather, essential features of training data become encoded in deep neural networks as patterns, that become practically available as styles. We discuss what happens when the distinction between objects and their appearance dissolves and all aspects of images or text become understood as styles, accessible for exploration and creative combination and generation. For example, defining visual qualities of entities like 'chair' or 'cat' become available as 'chair-ness' or 'cat-ness' for creative image generation. We argue that, when understood as style engines, unique generative AI capabilities become conceptualized as complementing traditional computing ones. This will aid both computing practitioners and information systems researchers in reconciling and integrating generative AI into the traditional IS landscape. Our conceptualization leads us to propose four archetypes of generative AI application and use, and to highlight future avenues for information systems research made visible by this conceptualization, as well as implications for practice and policymaking. Riemer, Kai/D-7523-2015 0268-4012 1873-4707 DEC 2024 79 102824 10.1016/j.ijinfomgt.2024.102824 http://dx.doi.org/10.1016/j.ijinfomgt.2024.102824 JUL 2024 WOS:001274645300001 C Selitskiy, S; Inoue, C AIAA Selitskiy, Stanislav; Inoue, Chihiro Education Paradigm Shift To Maintain Human Competitive Advantage Over AI AIAA AVIATION FORUM AND ASCEND 2024 AIAA Aviation Forum JUL 29-AUG 02, 2024 Las Vegas, NV AIAA Discussion about the replacement of intellectual human labour by "thinking machines" has been present in the public and expert discourse since the creation of Artificial Intelligence (AI) as an idea and terminology since the middle of the twentieth century. Until recently, it was more of a hypothetical concern. However, in recent years, with the rise of Generative AI, especially Large Language Models (LLM), and particularly with the widespread popularity of the ChatGPT model, that concern became practical. Many domains of human intellectual labour have to adapt to the new AI tools that give humans new functionality and opportunity, but also question the viability and necessity of some human work that used to be considered intellectual yet has now become an easily automatable commodity. Education, unexpectedly, has now become burdened by an especially crucial role of charting long-range strategies for discovering viable human skills that would guarantee their place in the world of the ubiquitous use of AI in the intellectual sphere. We highlight weaknesses of the current AI and, especially, of its LLM-based core, show that root causes of LLMs' weaknesses are unfixable by the current technologies, and propose directions in the constructivist paradigm for the changes in Education that ensure long-term advantages of humans over AI tools. Selitskiy, Stanislav/JTS-9589-2023; Inoue, Chihiro/AAT-3219-2021 978-1-62410-716-0 2024 WOS:001397464106014 C Ul Haq, MU; Frazzetto, P; Da San Martino, G; Sperduti, A ASSOC COMPUTING MACHINERY Ul Haq, Muhammad Uzair; Frazzetto, Paolo; Da San Martino, Giovanni; Sperduti, Alessandro Improving Soft Skill Extraction via Data Augmentation and Embedding Manipulation 39TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, SAC 2024 39th Annual ACM Symposium on Applied Computing (SAC) APR 08-12, 2024 Univ Salamanca, Avila, SPAIN Assoc Comp Machinery, ACM Special Interest Grp Appl Comp Univ Salamanca Soft skills (SS) are important for Human Resource Management when recruiting suitable candidates for a job. Nowadays, enterprises aim to automatically extract such information from documents, curriculum vitae (CVs) and job descriptions, to speed up their recruitment process. State-of-the-art Large Language Models (LLMs) have been successful in Natural Language Processing (NLP) by finetuning them to the domain-specific task. However, annotated data for the task is very limited and costly to obtain, since it requires domain experts. Moreover, SS consists of complex long entities which are difficult to extract given few annotated examples. As a consequence, the performance of the LLMs on soft skill detection still needs improvement before being used in a real-world context. In this paper, we introduce data augmentation based entity extraction approach which shows promising performance when the entity length is long (i.e more than three tokens). Moreover, we explore the performance of pre-trained LLMs to generate synthetic data for training. The pre-trained models are used to generate contextual augmentation of the baseline dataset. We further analyse the embeddings generated by these models in aiding the extraction process of entities. We develop an Embedding Manipulation (EM) approach to further improve the performance of baseline models. We evaluated our approach on the only publicly available dataset for soft skills (SKILLSPAN), and on three Entity Extraction datasets (GUM, WNUT-2017 and CoNLL-2003) to assess the proposed approach. Empirical evidence shows that the proposed approach allows us to get 6.52% increased F-1 over the baseline model for the soft skills. Frazzetto, Paolo/0000-0002-3227-0019 979-8-4007-0243-3 2024 987 996 10.1145/3605098.3636010 http://dx.doi.org/10.1145/3605098.3636010 WOS:001236958200141 J Hubert, KF; Awa, KN; Zabelina, DL Hubert, Kent F.; Awa, Kim N.; Zabelina, Darya L. The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks SCIENTIFIC REPORTS The emergence of publicly accessible artificial intelligence (AI) large language models such as ChatGPT has given rise to global conversations on the implications of AI capabilities. Emergent research on AI has challenged the assumption that creative potential is a uniquely human trait thus, there seems to be a disconnect between human perception versus what AI is objectively capable of creating. Here, we aimed to assess the creative potential of humans in comparison to AI. In the present study, human participants (N = 151) and GPT-4 provided responses for the Alternative Uses Task, Consequences Task, and Divergent Associations Task. We found that AI was robustly more creative along each divergent thinking measurement in comparison to the human counterparts. Specifically, when controlling for fluency of responses, AI was more original and elaborate. The present findings suggest that the current state of AI language models demonstrate higher creative potential than human respondents. ; Zabelina, Darya/AAD-1985-2022 Hubert, Kent/0009-0009-7348-5102; Zabelina, Darya/0000-0002-0313-7358; Awa, Kim/0000-0002-4932-6277 2045-2322 FEB 10 2024 14 1 3440 10.1038/s41598-024-53303-w http://dx.doi.org/10.1038/s41598-024-53303-w 38341459 WOS:001160069200016 J Feuerriegel, S; Maarouf, A; Bär, D; Geissler, D; Schweisthal, J; Pröllochs, N; Robertson, CE; Rathje, S; Hartmann, J; Mohammad, SM; Netzer, O; Siegel, AA; Plank, B; Van Bavel, JJ Feuerriegel, Stefan; Maarouf, Abdurahman; Baer, Dominik; Geissler, Dominique; Schweisthal, Jonas; Proellochs, Nicolas; Robertson, Claire E.; Rathje, Steve; Hartmann, Jochen; Mohammad, Saif M.; Netzer, Oded; Siegel, Alexandra A.; Plank, Barbara; Van Bavel, Jay J. Using natural language processing to analyse text data in behavioural science NATURE REVIEWS PSYCHOLOGY Language is a uniquely human trait at the core of human interactions. The language people use often reflects their personality, intentions and state of mind. With the integration of the Internet and social media into everyday life, much of human communication is documented as written text. These online forms of communication (for example, blogs, reviews, social media posts and emails) provide a window into human behaviour and therefore present abundant research opportunities for behavioural science. In this Review, we describe how natural language processing (NLP) can be used to analyse text data in behavioural science. First, we review applications of text data in behavioural science. Second, we describe the NLP pipeline and explain the underlying modelling approaches (for example, dictionary-based approaches and large language models). We discuss the advantages and disadvantages of these methods for behavioural science, in particular with respect to the trade-off between interpretability and accuracy. Finally, we provide actionable recommendations for using NLP to ensure rigour and reproducibility. ; Siegel, Alexandra/M-1331-2019; Feuerriegel, Stefan/ABD-6599-2021; Netzer, Oded/KHW-9415-2024; Hartmann, Jochen/IUN-2216-2023; Bavel, Jay/I-6748-2015 Schweisthal, Jonas/0000-0003-3725-3821; 2731-0574 FEB 2025 4 2 96 111 10.1038/s44159-024-00392-z http://dx.doi.org/10.1038/s44159-024-00392-z JAN 2025 WOS:001386522700001 J Adamcová, S Adamcova, Silvia Artificial Intelligence and its Impact on Teaching, Learning and Work MUTTERSPRACHE In today's foreign language learning, a constant expansion of vocabulary is necessary in order to keep pace with developments in technology and science. This article looks at a current topic in German linguistics the language about artificial intelligence in relation to applications such as ChatGPT and chatbots. As the rapid development of modern technologies and their applications raises numerous linguistic issues, the new generation of university graduates must adapt to constant changes in the labour market. In addition to the development of new skills, this also involves the acquisition of specialised vocabulary from digital media such as Al. It is also being investigated whether artificial intelligence can help to promote and support language skills in the classroom. In a next step, specific requirements of foreign language teaching for teachers and students will be addressed with regard to future skills, which represent a particular challenge in the education sector in view of the high speed of the diverse developments. This study thus makes a contribution to the current debate on the role of artificial intelligence in higher education. Overall, this evaluation offers an insight into a highly topical subject of the application of artificial intelligence, which will have a significant influence on the linguistic and pedagogical practice of the future. 0027-514X SEP 2024 134 3 251 267 10.53371/61178 http://dx.doi.org/10.53371/61178 WOS:001337400800004 J McGrath, SW; Russin, J; Pavlick, E; Feiman, R McGrath, Sam Whitman; Russin, Jacob; Pavlick, Ellie; Feiman, Roman How Can Deep Neural Networks Inform Theory in Psychological Science? CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE Over the last decade, deep neural networks (DNNs) have transformed the state of the art in artificial intelligence. In domains such as language production and reasoning, long considered uniquely human abilities, contemporary models have proven capable of strikingly human-like performance. However, in contrast to classical symbolic models, neural networks can be inscrutable even to their designers, making it unclear what significance, if any, they have for theories of human cognition. Two extreme reactions are common. Neural network enthusiasts argue that, because the inner workings of DNNs do not seem to resemble any of the traditional constructs of psychological or linguistic theory, their success renders these theories obsolete and motivates a radical paradigm shift. Neural network skeptics instead take this inability to interpret DNNs in psychological terms to mean that their success is irrelevant to psychological science. In this article, we review recent work that suggests that the internal mechanisms of DNNs can, in fact, be interpreted in the functional terms characteristic of psychological explanations. We argue that this undermines the shared assumption of both extremes and opens the door for DNNs to inform theories of cognition and its development. McGrath, Sam/0009-0000-5383-1885 0963-7214 1467-8721 OCT 2024 33 5 325 333 10.1177/09637214241268098 http://dx.doi.org/10.1177/09637214241268098 SEP 2024 39949337 WOS:001313189700001 J Nasra, M; Jaffri, R; Pavlin-Premrl, D; Kok, HK; Khabaza, A; Barras, C; Slater, LA; Yazdabadi, A; Moore, J; Russell, J; Smith, P; Chandra, RV; Brooks, M; Jhamb, A; Chong, WS; Maingard, J; Asadi, H Nasra, Mohamed; Jaffri, Rimsha; Pavlin-Premrl, Davor; Kok, Hong Kuan; Khabaza, Ali; Barras, Christen; Slater, Lee-Anne; Yazdabadi, Anousha; Moore, Justin; Russell, Jeremy; Smith, Paul; Chandra, Ronil V.; Brooks, Mark; Jhamb, Ashu; Chong, Winston; Maingard, Julian; Asadi, Hamed Can artificial intelligence improve patient educational material readability? A systematic review and narrative synthesis INTERNAL MEDICINE JOURNAL Enhancing patient comprehension of their health is crucial in improving health outcomes. The integration of artificial intelligence (AI) in distilling medical information into a conversational, legible format can potentially enhance health literacy. This review aims to examine the accuracy, reliability, comprehensiveness and readability of medical patient education materials (PEMs) simplified by AI models. A systematic review was conducted searching for articles assessing outcomes of use of AI in simplifying PEMs. Inclusion criteria are as follows: publication between January 2019 and June 2023, various modalities of AI, English language, AI use in PEMs and including physicians and/or patients. An inductive thematic approach was utilised to code for unifying topics which were qualitatively analysed. Twenty studies were included, and seven themes were identified (reproducibility, accessibility and ease of use, emotional support and user satisfaction, readability, data security, accuracy and reliability and comprehensiveness). AI effectively simplified PEMs, with reproducibility rates up to 90.7% in specific domains. User satisfaction exceeded 85% in AI-generated materials. AI models showed promising readability improvements, with ChatGPT achieving 100% post-simplification readability scores. AI's performance in accuracy and reliability was mixed, with occasional lack of comprehensiveness and inaccuracies, particularly when addressing complex medical topics. AI models accurately simplified basic tasks but lacked soft skills and personalisation. These limitations can be addressed with higher-calibre models combined with prompt engineering. In conclusion, the literature reveals a scope for AI to enhance patient health literacy through medical PEMs. Further refinement is needed to improve AI's accuracy and reliability, especially when simplifying complex medical information. Slater, Lee-Anne/AAC-4151-2022; Chandra, Ronil/GPK-0357-2022 Nasra, Mohamed/0000-0002-0818-8285; 1444-0903 1445-5994 JAN 2025 55 1 20 34 10.1111/imj.16607 http://dx.doi.org/10.1111/imj.16607 DEC 2024 39720869 WOS:001382481600001 J Kalluri, B; Prasad, P; Sharma, P; Chippa, D Kalluri, Balaji; Prasad, Prajish; Sharma, Prakrati; Chippa, Divyaansh Developing Future Computational Thinking in Foundational CS Education: A Case Study From a Liberal Education University in India IEEE TRANSACTIONS ON EDUCATION Contribution: This article proposes a new theoretical model with a goal to develop future human computational thinking (CT) in foundational computer science (CS) education. The model blends six critical types of thinking, i.e., logical thinking, systems thinking, sustainable thinking, strategic thinking, creative thinking, and responsible thinking into the design of a first-year undergraduate programming course. The study describes a creative blended pedagogy that embeds the proposed model into the course plan. Background: The emergence of artificial intelligent systems such as large language models from a knowledge provider perspective, coupled with a gradual change in post-pandemic outlook of education challenge the relevance and raises concerns about the future of education. The 21st-century human CT requirements, viz., learning to code (skill) and thinking computationally (competency), will be inadequate in the future. Moreover, there is substantial evidence which shows that most introductory programming courses fail to integrate critical elements like ethics and responsibility as part of the course. Intended Outcomes: The authors anticipate experiential learning models such as this has immense potential to future-proof CS education, as well as make future software engineers responsible citizens. Application Design: The proposed model blends six types of thinking into the design and activities of the course. The underlying theoretical basis of these activities revolve around three key principles: 1) experiential learning; 2) self-reflection; and 3) peer learning. Findings: This case study from a liberal educational institution in India qualitatively shows evidence of students developing six critical elements of thinking that shapes their future CT ability. University, FLAME/HSG-7860-2023; Kalluri, Balaji/ABF-8321-2020; , FLAME University/HSG-7860-2023 Prasad, Prajish/0000-0001-7986-6277; , FLAME University/0009-0003-3435-6187; Kalluri, Balaji/0000-0002-0033-5463 0018-9359 1557-9638 DEC 2024 67 6 944 953 10.1109/TE.2024.3394060 http://dx.doi.org/10.1109/TE.2024.3394060 MAY 2024 WOS:001226166900001 C Vrågård, J; Brorsson, F; Aghaee, N Moriera, F Vragard, John; Brorsson, Freddie; Aghaee, Naghmeh Generative AI in Higher Education: Educators' Perspectives on Academic Learning and Integrity PROCEEDINGS OF THE 23RD EUROPEAN CONFERENCE ON E-LEARNING, ECEL 2024 Proceedings on the European Conference of e-Learning 23rd European Conference on e-Learning OCT 24-25, 2024 Universidade Portucalense Infante D. Henrique, Porto, PORTUGAL Universidade Portucalense Infante D. Henrique Generative Artificial Intelligence (Gen AI), exemplified by models such as ChatGPT, has rapidly advanced, becoming a significant force in various sectors, including higher education. ChatGPT, a leading application of Gen AI, utilizes large language models (LLMs) to generate human-like text, providing capabilities that range from answering complex questions to facilitating software development. As these tools become increasingly integrated into academic environments, their impact on teaching and learning processes has become more under focus. However, there are not many studies focusing on the impact of such systems on students' performance and the use of such systems. This study therefore examines the impact of GPT tools on higher education, aiming to address the following research questions: How does the use of GPTs influence the teaching and learning process in higher education? What are the perceived impacts of GPTs on educational practices from university educators' perspective? The research employs a qualitative methodology, incorporating semi-structured interviews with educators from Swedish universities who have integrated GPT into their curricula. Data were transcribed and analysed using OpenAI's Whisper to extract key themes and insights. Data analysis was done through thematic analysis and categorizing the data using codes. The study uncovers a dual impact of GPT on education, while it offers substantial opportunities for enhancing productivity and personalized learning, it also raises significant concerns about academic integrity, over-reliance on AI, and the potential influences on students' soft skills. These findings contribute to the discourse on digital learning by highlighting the need for instructional and constructive integration of AI technologies such as GenAI, in educational settings. In addition, the rise and integration of GPT technology is irreversible, and we must adapt to it rather than return to old ways. Embracing AI's potential while addressing its challenges is essential for progress and innovation in this new era. The study emphasizes the importance of developing clear policies and guidelines to ensure that the benefits of GPT are realized without compromising the integrity of the educational process. As such, this research provides valuable insights for educators, policymakers, and scholars interested in the ethical and effective implementation of AI in higher education. 2048-8637 978-1-917204-21-7; 978-1-917204-22-4 2024 23/1 406 414 WOS:001438533400050 J Rizzo, SA Rizzo, Santi Agatino To be Artificial Intelligence for sustainability or not to be sustainable Artificial Intelligence RENEWABLE & SUSTAINABLE ENERGY REVIEWS Sustainable electrical energy (SEE) represents a direct and indirect critical enabling factor for sustainable development. Artificial Intelligence (AI) has emerged as a disruptive technology that accelerates the transition toward full SEE, but concurrently, presents a fatal issue. This study inspects the benefits and limitations of AI applications in the context of SEE. The primary finding highlights a common assumption: AI utilization in areas such as green power generation, electric vehicles, and so on is often deemed, per se, sufficient to achieve full SEE. However, the study highlights a critical shortcoming of this perspective: the absence of a holistic SEE. Achieving full SEE requires integrating the life cycle assessment, which evaluates the environmental impact from raw material extraction to end-of-life management. This ensures considering the environmental adverse effects of green technologies such as renewables and electric transportation, thus embracing a real technology neutrality. Additionally, a thorough consideration of electrical energy production and consumption is necessary. Moreover, it emerged that AI-based holistic planning enabling a fully green-supplied power system has not been sufficiently investigated so far. In conclusion, the first part of the study has brought out that a transition toward fully sustainable electricity imposes that AI considers the design for sustainability paradigm and a holistic view of sustainability that combines life cycle assessment and exploitable electrical energy. The large room for improvement in the adoption of AI for full SEE and its imperative priority ask for an urgent research effort of academia and industry. With this in mind, some figures of merit have been discussed. The second part of this study investigates the main sustainability challenges of AI. The analysis of the (e-)waste, pollution, and energy demand has highlighted that AI widespread use is untenable with the current technologies. The key issue is the unsustainable growth of electrical energy consumption due to AI, which incontrovertibly emerges as the core challenge, because the research effort has focused on achieving even-increasing accuracy regardless of the energy consumption. Large diffusion of humanoids that would exploit various AI tools to face different problems while using large language models and generative AI systems will skyrocket energy demand. Natural evolution has inherently optimized the human brain for energy efficiency, while the evolution of AI has led, conversely, to energyinefficient outcomes. Therefore, a worldwide research effort must be lavished on developing low-energydemand AI while keeping sufficient accuracy. In conclusion, all the research efforts have focused so far on providing AI with human skills until reaching super-human abilities, overlooking the crucial one: very lowenergy-demand high-computing aptitude. Rizzo, Santi/M-5987-2013 1364-0321 1879-0690 NOV 2025 223 116063 10.1016/j.rser.2025.116063 http://dx.doi.org/10.1016/j.rser.2025.116063 WOS:001534882600001 J Tiwari, A; Kumar, A; Jain, S; Dhull, KS; Sajjanar, A; Puthenkandathil, R; Paiwal, K; Singh, R Tiwari, Anushree; Kumar, Amit; Jain, Shailesh; Dhull, Kanika S.; Sajjanar, Arunkumar; Puthenkandathil, Rahul; Paiwal, Kapil; Singh, Ramanpal Implications of ChatGPT in Public Health Dentistry: A Systematic Review CUREUS JOURNAL OF MEDICAL SCIENCE An artificial intelligence (AI) program called ChatGPT that generates text in response to typed commands has proven to be highly popular, as evidenced by the fact that OpenAI makes it available online. The goal of the present investigation was to investigate ChatGPT's potential applications as an outstanding instance of large language models (LLMs) in the fields of public dental health schooling, writing for academic use, research in public dental health, and clinical practice in public dental health based on the available data. Importantly, the goals of the current review included locating any drawbacks and issues that might be connected to using ChatGPT in the previously mentioned contexts in healthcare settings. Using search practice in public health dentistry, education in public health dentistry, academic writing in public health dentistry, etc., a thorough search was carried out on the Pubmed database, the Embase database, the Ovid database, the Global Health database, PsycINFO, and the Web of Science. The dates of publication were not restricted. Systematic searches were carried out for all publications according to inclusion and exclusion criteria between March 31, 2018, and March 31, 2023. Eighty-four papers were obtained through a literature search using search terms. Sixteen similar and duplicate papers were excluded and 68 distinct articles were initially selected. Thirty-three articles were excluded after reviewing abstracts and titles. Thirty-five papers were selected, for which full text was managed. Four extra papers were found manually from references. Thirty-nine articles with full texts were eligible for the study. Eighteen inadequate articles are excluded from the final 21 studies that were finally selected for systemic review. According to previously published studies, ChatGPT has demonstrated its effectiveness in helping scholars with the authoring of scientific research and dental studies. If the right structures are created, ChatGPT can offer suitable responses and more time to concentrate on the phase of experimentation for scientists. Risks include prejudice in the training data, undervaluing human skills, the possibility of fraud in science, as well as legal and reproducibility concerns. It was concluded that practice considering ChatGPT's potential significance, the research's uniqueness, and the premise-the activity of the human brain-remains. While there is no question about the superiority of incorporating ChatGPT into the practice of public health dentistry, it does not, in any way, take the place of a dentist since clinical practice involves more than just making diagnoses; it also involves relating to clinical findings and providing individualized patient care. Even though AI can be useful in a number of ways, a dentist must ultimately make the decision because dentistry is a field that involves several disciplines. makkad, Ramanpal/I-2353-2012; Paiwal, Kapil/AFV-2918-2022; Dhull, Kanika Singh/ABF-6978-2021 Paiwal, Kapil/0000-0002-6982-5612; Dhull, Kanika Singh/0000-0002-0002-8084; 2168-8184 JUN 13 2023 15 6 e40367 10.7759/cureus.40367 http://dx.doi.org/10.7759/cureus.40367 37456464 WOS:001032064700023 J Rebelo, EM Rebelo, Emilia Malcata Artificial Intelligence in Higher Education: Proposal for a Transversal Curricular Unit JOURNAL OF FORMATIVE DESIGN IN LEARNING Given the very recent appearance and rapid dissemination of tools based on artificial intelligence (AI), particularly the ChatGPT application, and the inevitability of their installation in the lives of students and professors, this article proposes the creation of a new "transversal skills" curricular unit to be taught to students in the Engineering Programs at the Faculty of Engineering of the University of Porto. Given the "revolution" that these AI-based tools can represent, it is important to reflect on what they constitute, how they can support professors in their teaching tasks, how they can support students in acquiring and interrelating knowledge and developing their competences, and how they can shape assessment processes. This article begins by analyzing the characteristics, potential and limitations of AI and the importance of developing AI-related transversal skills in higher education, followed by examples of the application of AI-based tools in science, technology, engineering, and mathematics (STEM) courses. Finally, the design of an AI-based curricular unit is proposed, as well as a methodology for identifying, assessing and mitigating the effects of biases in AI applications in curricula. Despite this proposal is directly applicable to STEM courses, it can be easily adapted to other areas of study. Rebelo, Emília/X-4251-2019; Rebelo, Emilia/X-4251-2019 Rebelo, Emilia/0000-0003-4257-9017 2509-8039 JUN 2025 9 1 1 24 10.1007/s41686-024-00097-9 http://dx.doi.org/10.1007/s41686-024-00097-9 JAN 2025 WOS:001395426400001 J Jung, DW; Suh, S Jung, Dawool; Suh, Sungeun Enhancing Soft Skills through Generative AI in Sustainable Fashion Textile Design Education SUSTAINABILITY This study explores the significance of incorporating soft skill training in fashion design education through the use of artificial intelligence (AI) technology and examines various AI-based approaches for sustainable fashion textile design education employing a multifaceted methodology that encompasses empirical, quantitative, and qualitative methods. We investigate the aspects of Design Sprints, identify key soft skills that help students meet the complex demands of contemporary fashion design workplaces, propose a curriculum guide for AI textile design programs, and evaluate the soft skill training process. Participants included students who had completed basic fashion design courses over three to four semesters and had experience with the fashion design process. The findings confirmed that participants' soft skills improved across four areas-digital competence, sense of initiative and entrepreneurship, problem-solving and thinking skills, and communication-through the AI-based fashion textile design curriculum. This study validates the importance of integrating AI technology into educational programs to enhance essential soft skills in the digital fashion industry environment. Additionally, it emphasizes the necessity of developing AI technology-specialized design prompts while maintaining a balance between traditional design education and digital design education for sustainable fashion design education. Suh, Sungeun/GYV-6085-2022 Jung, Dawool/0000-0002-8424-5261 2071-1050 AUG 2024 16 16 6973 10.3390/su16166973 http://dx.doi.org/10.3390/su16166973 WOS:001304696800001 J González-Rico, P; Sintes, ML Gonzalez-Rico, Pablo; Sintes, Mireia Lluch Empowering Soft Skills through Artificial Intelligence and Personalised Mentoring EDUCATION SCIENCES At present, the integration of technology into education has generated a significant change in the way students access knowledge and develop skills. The availability of digital tools and online platforms has democratised access to information, allowing students to learn from anywhere and at any time. This article focuses on how the combination of artificial intelligence digital tools, such as ChatGPT, with one-to-one tutoring affects the development of soft skills in higher education students. A total of 182 university students participated in the study, divided into two groups. One group was required to construct an academic topic autonomously using only ChatGPT. The other group used the ChatGPT tool in conjunction with personal tutoring, with the teacher present to expand knowledge and enrich learning. The findings suggest that a combination of technology and meaningful human interactions is necessary to optimise the educational experience. While digital tools can be beneficial in accessing knowledge and developing skills, it is essential to acknowledge the value of individual connections with teachers in fostering authentic and deep learning. Furthermore, the study considers the potential necessity to modify and refocus both teaching participation and the student assessment system. This would entail a shift away from an emphasis on the memorisation of theoretical knowledge and towards the training and development of soft skills, competences, values and social implications. Gonzalez Rico, Pablo/0000-0003-0498-0248 2227-7102 JUL 2024 14 7 699 10.3390/educsci14070699 http://dx.doi.org/10.3390/educsci14070699 WOS:001277511500001 J Brin, D; Sorin, V; Vaid, A; Soroush, A; Glicksberg, BS; Charney, AW; Nadkarni, G; Klang, E Brin, Dana; Sorin, Vera; Vaid, Akhil; Soroush, Ali; Glicksberg, Benjamin S.; Charney, Alexander W.; Nadkarni, Girish; Klang, Eyal Comparing ChatGPT and GPT-4 performance in USMLE soft skill assessments SCIENTIFIC REPORTS The United States Medical Licensing Examination (USMLE) has been a subject of performance study for artificial intelligence (AI) models. However, their performance on questions involving USMLE soft skills remains unexplored. This study aimed to evaluate ChatGPT and GPT-4 on USMLE questions involving communication skills, ethics, empathy, and professionalism. We used 80 USMLE-style questions involving soft skills, taken from the USMLE website and the AMBOSS question bank. A follow-up query was used to assess the models' consistency. The performance of the AI models was compared to that of previous AMBOSS users. GPT-4 outperformed ChatGPT, correctly answering 90% compared to ChatGPT's 62.5%. GPT-4 showed more confidence, not revising any responses, while ChatGPT modified its original answers 82.5% of the time. The performance of GPT-4 was higher than that of AMBOSS's past users. Both AI models, notably GPT-4, showed capacity for empathy, indicating AI's potential to meet the complex interpersonal, ethical, and professional demands intrinsic to the practice of medicine. Brin, Dana/MVU-5184-2025; Glicksberg, Benjamin/I-9500-2019; Sorin, Vera/IAR-4247-2023; mirzaei, hamed/X-2374-2018; Soroush, Ali/O-5540-2016 Brin, Dana/0009-0003-7316-206X; Soroush, Ali/0000-0001-6900-5596; Sorin, Vera/0000-0003-0509-4686 2045-2322 OCT 1 2023 13 1 16492 10.1038/s41598-023-43436-9 http://dx.doi.org/10.1038/s41598-023-43436-9 37779171 WOS:001084350000002 J Deroncele-Acosta, A; Sayán-Rivera, RME; Mendoza-López, AD; Norabuena-Figueroa, ED Deroncele-Acosta, Angel; Sayan-Rivera, Rosa Maria Elizabeth; Mendoza-Lopez, Angel Deciderio; Norabuena-Figueroa, Emerson Damian Generative Artificial Intelligence and Transversal Competencies in Higher Education: A Systematic Review APPLIED SYSTEM INNOVATION Generative AI is an emerging tool in higher education; however, its connection with transversal competencies, as well as their sustainable adoption, remains underexplored. The study aims to analyze the scientific and conceptual development of generative artificial intelligence in higher education to identify the most relevant transversal competencies, strategic processes for its sustainable implementation, and global trends in academic production. A systematic literature review (PRISMA) was conducted on the Web of Science, Scopus, and PubMed, analyzing 35 studies for narrative synthesis and 897 publications for bibliometric analysis. The transversal competencies identified were: Academic Integrity, Critical Thinking, Innovation, Ethics, Creativity, Communication, Collaboration, AI Literacy, Responsibility, Digital Literacy, AI Ethics, Autonomous Learning, Self-Regulation, Flexibility, and Leadership. The conceptual framework connotes the interdisciplinary nature and five key processes were identified to achieve the sustainable integration of Generative AI in higher education oriented to the development of transversal competencies: (1) critical and ethical appropriation, (2) institutional management of technological infrastructure, (3) faculty development, (4) curricular transformation, and (5) pedagogical innovation. On bibliometric behavior, scientific articles predominate, with few systematic reviews. China leads in publication volume, and social sciences are the most prominent area. It is concluded that generative artificial intelligence is key to the development of transversal competencies if it is adopted from a critical, ethical, and pedagogically intentional approach. Its implications and future projections in the field of higher education are discussed. Deroncele-Acosta, Angel/IRZ-1383-2023 2571-5577 JUN 18 2025 8 3 83 10.3390/asi8030083 http://dx.doi.org/10.3390/asi8030083 WOS:001515253800001 J Wijaya, TT; Yu, QC; Cao, YM; He, YH; Leung, FKS Wijaya, Tommy Tanu; Yu, Qingchun; Cao, Yiming; He, Yahan; Leung, Frederick K. S. Latent Profile Analysis of AI Literacy and Trust in Mathematics Teachers and Their Relations with AI Dependency and 21st-Century Skills BEHAVIORAL SCIENCES Artificial Intelligence (AI) technology, particularly generative AI, has positively impacted education by enhancing mathematics instruction with personalized learning experiences and improved data analysis. Nonetheless, variations in AI literacy, trust in AI, and dependency on these technologies among mathematics teachers can significantly influence their development of 21st-century skills such as self-confidence, problem-solving, critical thinking, creative thinking, and collaboration. This study aims to identify distinct profiles of AI literacy, trust, and dependency among mathematics teachers and examines how these profiles correlate with variations in the aforementioned skills. Using a cross-sectional research design, the study collected data from 489 mathematics teachers in China. A robust three-step latent profile analysis method was utilized to analyze the data. The research revealed five distinct profiles of AI literacy and trust among the teachers: (1) Basic AI Engagement; (2) Developing AI Literacy, Skeptical of AI; (3) Balanced AI Competence; (4) Advanced AI Integration; and (5) AI Expertise and Confidence. The study found that an increase in AI literacy and trust directly correlates with an increase in AI dependency and a decrease in skills such as self-confidence, problem-solving, critical thinking, creative thinking, and collaboration. The findings underscore the need for careful integration of AI technologies in educational settings. Excessive reliance on AI can lead to detrimental dependencies, which may hinder the development of essential 21st-century skills. The study contributes to the existing literature by providing empirical evidence on the impact of AI literacy and trust on the professional development of mathematics teachers. It also offers practical implications for educational policymakers and institutions to consider balanced approaches to AI integration, ensuring that AI enhances rather than replaces the critical thinking and problem-solving capacities of educators. ; Tanu Wijaya, Tommy/AAZ-4460-2020; Leung, Frederick Koon Shing/A-3166-2010; mo, fan/KHT-4787-2024; Cao, Yiming/D-3541-2013 YU, Qingchun/0000-0002-6619-689X; Tanu Wijaya, Tommy/0000-0001-6840-3875; Leung, Frederick Koon Shing/0000-0003-1725-3883; 2076-328X NOV 2024 14 11 1008 10.3390/bs14111008 http://dx.doi.org/10.3390/bs14111008 39594308 WOS:001363933800001 J Borkovska, I; Kolosova, H; Kozubska, I; Antonenko, I Borkovska, Inna; Kolosova, Hanna; Kozubska, Iryna; Antonenko, Inna Integration of AI into the Distance Learning Environment: Enhancing Soft Skills ARAB WORLD ENGLISH JOURNAL Soft skills have become increasingly essential for success in the modern world, especially in the labor market, where employers value employees' social and communication skills. Online education, which is an integral part of the educational process in Ukraine, is adjusting to the development of students' soft skills. Integrating artificial intelligence tools into English language learning is becoming a new direction in soft skills development. This approach opens up new teaching strategies that make learning more effective, engaging, and innovative. While learning English, students develop communication, creativity, and critical thinking skills, which contribute to their educational process and prepare the foundation for employment. The study aims to 1) evaluate the impact of artificial intelligence on the development of students' soft skills in online learning; 2) identify the most essential soft skills for their effective learning and future employment based on a student survey; 3) develop criteria for an online course using artificial intelligence and outline strategies for integrating the ChatGPT tool into distance learning English classes. To achieve the objectives of our study, we developed and processed a questionnaire, collected quantitative data, and analyzed and interpreted qualitative data; the study sample included 304 students. The questionnaire results showed a generally positive attitude of students towards using artificial intelligence in English for Specific Purposes courses. They opened up prospects for introducing an online course in the English for Specific Purposes program and further research, including an experiment with the introduction of this online course. Kozubska, Iryna/I-7012-2017; Borkovska, Inna/IUM-2316-2023; Antonenko, Inna/KEJ-3961-2024; Kolosova, Hanna/GYU-1372-2022 Kolosova, Anna/0000-0003-4224-0371; 2229-9327 APR 2024 SI 56 72 10.24093/awej/ChatGPT.3 http://dx.doi.org/10.24093/awej/ChatGPT.3 WOS:001245053900004 J Cardon, P; Fleischmann, C; Logemann, M; Heidewald, J; Aritz, J; Swartz, S Cardon, Peter; Fleischmann, Carolin; Logemann, Minna; Heidewald, Jeanette; Aritz, Jolanta; Swartz, Stephanie Competencies Needed by Business Professionals in the AI Age: Character and Communication Lead the Way BUSINESS AND PROFESSIONAL COMMUNICATION QUARTERLY Many experts project generative AI will impact the types of competencies that are valued among working professionals. This is the first known academic study to explore the views of business practitioners about the impacts of generative AI on skill sets. This survey of 692 business practitioners showed that business practitioners widely use generative AI, with the most common uses involving research and ideation, drafting of business messages and reports, and summarizing and revising text. Business practitioners report that character-based traits such as integrity and soft skills will become more important. Implications for teaching business communication are discussed. ; Heidewald, Jeanette/JRX-9144-2023; Cardon, Peter/MIN-0877-2025 Cardon, Peter/0000-0002-4574-4439; Fleischmann, Carolin/0009-0001-5475-994X 2329-4906 2329-4922 JUN 2024 87 2 223 246 10.1177/23294906231208166 http://dx.doi.org/10.1177/23294906231208166 NOV 2023 WOS:001100609100001 J Zhang, DL; Wijaya, TT; Wang, Y; Su, MY; Li, XX; Damayanti, NW Zhang, Dongli; Wijaya, Tommy Tanu; Wang, Ying; Su, Mingyu; Li, Xinxin; Damayanti, Nia Wahyu Exploring the relationship between AI literacy, AI trust, AI dependency, and 21st century skills in preservice mathematics teachers SCIENTIFIC REPORTS Generation-Artificial Intelligence (Gen-AI) is widely used in education and has been shown to improve students' mathematical abilities. However, dependency on Gen-AI may negatively impact these abilities and should be approached with caution. This study uses Structural Equation Modeling (SEM) to determine the relationship between AI literacy, AI trust, AI dependency, and 21st-century skills in preservice mathematics teachers. This research utilizes a self-designed questionnaire with 469 preservice mathematics teachers as respondents. SPSS and AMOS software were used for data analysis. The findings reveal that both AI trust and AI literacy significantly influence preservice mathematics teachers' dependency on Gen-AI. Furthermore, this dependency on Gen-AI among preservice mathematics teachers has a significant negative effect on their problem-solving ability, critical thinking, creative thinking, collaboration skills, communication skills, and self-confidence. This research provides new information to governments, schools, and teachers that caution should be exercised when attempting to enhance AI literacy and trust in AI among preservice mathematics teachers. Su, Mingyu/HNQ-9403-2023; Tanu Wijaya, Tommy/AAZ-4460-2020 2045-2322 APR 24 2025 15 1 14281 10.1038/s41598-025-99127-0 http://dx.doi.org/10.1038/s41598-025-99127-0 40275054 WOS:001475676100014 J Haroud, S; Saqri, N Haroud, Samia; Saqri, Nadia Generative AI in Higher Education: Teachers' and Students' Perspectives on Support, Replacement, and Digital Literacy EDUCATION SCIENCES Artificial intelligence (AI) is increasingly shaping diverse sectors, including education, sparking debates about its potential to transform pedagogical practices and redefine the role of educators. This study explores the perceptions and applications of generative AI in Moroccan higher education to better understand its implications for teaching and learning. A mixed-methods approach was adopted, combining quantitative data from 130 teachers and 156 students with qualitative insights. Quantitative findings reveal significant differences: students demonstrate greater openness to adopting AI, appreciating its capacity to provide instant feedback, enhance creativity, and improve academic performance. In contrast, teachers express reservations, particularly regarding AI's potential to undermine critical soft skills such as collaboration, problem-solving, and critical thinking. Qualitative analyses confirm these trends, highlighting that, while AI is perceived as a valuable complementary tool, it cannot replace the essential human role of educators in providing personalized guidance and addressing students' emotional and cognitive needs. Both groups agree on the necessity of enhanced digital literacy to ensure ethical and effective AI integration. These findings underscore the opportunities of generative AI, such as personalized learning and efficiency, while addressing limitations like ethical concerns and over-reliance, offering actionable insights for policymakers, educators, and technologists aiming to integrate AI responsibly in education. HAROUD, SAMIA/0009-0004-8702-1943 2227-7102 MAR 21 2025 15 4 396 10.3390/educsci15040396 http://dx.doi.org/10.3390/educsci15040396 WOS:001474860700001 J Federiakin, D; Molerov, D; Zlatkin-Troitschanskaia, O; Maur, A Federiakin, Denis; Molerov, Dimitri; Zlatkin-Troitschanskaia, Olga; Maur, Andreas Prompt engineering as a new 21st century skill FRONTIERS IN EDUCATION Artificial Intelligence (AI) promises to revolutionize nearly every aspect of human learning. However, users have observed that the efficacy of AI assistants hinges crucially on the quality of the prompts supplied to them. A slight alteration in wording can make the difference between an assistant misinterpreting an instruction and exceeding expectations. The skill of precisely communicating the essence of a problem to an AI assistant is as crucial as the assistant itself. This paper aims to introduce Prompt Engineering (PE) as an emerging skill essential for personal and professional learning and development in the 21st century. We define PE as the skill of articulating a problem, its context, and the constraints of the desired solution to an AI assistant, ensuring a swift and accurate response. We show that no existing related frameworks on 21st skills and others cover PE to the extent that allows for its valid assessment and targeted promotion in school and university education. Thus, we propose a conceptual framework for this skill set including (1) comprehension of the basic prompt structure, (2) prompt literacy, (3) the method of prompting, and (4) critical online reasoning. We also discuss the implications and challenges for the assessment framework of this skill set and highlight current PE-related recommendations for researchers and educators. Zlatkin-Troitschanskaia, O./AAM-8286-2020; Federiakin, Denis/P-8505-2015 2504-284X NOV 29 2024 9 1366434 10.3389/feduc.2024.1366434 http://dx.doi.org/10.3389/feduc.2024.1366434 WOS:001376100500001 J Mirón-Mérida, VA; García-García, RM Miron-Merida, Vicente Antonio; Garcia-Garcia, Rebeca Maria Developing written communication skills in engineers in Spanish: is ChatGPT a tool or a hindrance? FRONTIERS IN EDUCATION As 2023 became a disruptive year, due to the accelerated appearance of AI tools such as ChatGPT, the educational systems started to change and adapt to the new approaches observed in students, teachers, and employers. Although AI is likely to be integrated into different industrial and academic processes, its indiscriminate use could hinder the development of soft skills, including oral and written communication. Hence, it is important to identify any AI-generated assignments to secure a successful learning process. For those reasons, in this work, the effectivity of three plagiarism checkers, namely Turnitin, Unicheck and GPTZero, was evaluated on an engineering-based written text generated in ChatGPT in the Spanish language. A comparison with the plagiarism rate obtained for an original piece was conducted with One-way ANOVA. In all the cases, based on the low plagiarism rates (Unicheck: 14.44%, Turnitin: 12.43%), no plagiarism was detected in the AI-generated texts. Likewise, the GPTZero platform detected low AI-Origin in the texts created in ChatGPT (1.04%). Both results denoted the low efficiency of these platforms for assignments in Spanish and the high risk of conducting plagiarism without implications. Additionally, different alternatives were proposed for either integrating ChatGPT in learning activities or replacing the use of AI to ensure the development of skills and competencies in the students. 2504-284X DEC 16 2024 9 1416152 10.3389/feduc.2024.1416152 http://dx.doi.org/10.3389/feduc.2024.1416152 WOS:001385583700001 J Sarsenbay, S; Kabdiyev, A; Varlamis, I; Sardianos, C; Turan, C; Razhametov, B; Kazym, Y Sarsenbay, Shakhmar; Kabdiyev, Asset; Varlamis, Iraklis; Sardianos, Christos; Turan, Cemil; Razhametov, Bobir; Kazym, Yermek Generating Job Recommendations Based on User Personality and Gallup Tests ALGORITHMS This paper introduces a novel approach to job recommendation systems by incorporating personality traits evaluated through the Gallup CliftonStrengths assessment, aiming to enhance the traditional matching process beyond skills and qualifications. Unlike broad models like the Big Five, Gallup's CliftonStrengths assesses 34 specific talents (e.g., 'Analytical', 'Empathy'), enabling finer-grained, actionable job matches. While existing systems focus primarily on hard skills, this paper argues that personality traits-such as those measured by the Gallup test-play a crucial role in determining career satisfaction and long-term job retention. The proposed approach offers a more granular and actionable method for matching candidates with job opportunities that align with their natural strengths. Leveraging Gallup tests, we develop a job-matching approach that identifies personality traits and integrates them with recommendation algorithms to generate a list of the most suitable specializations for the user. By utilizing a GPT-4 model to process job descriptions and rank relevant personality traits, the system generates more personalized recommendations that account for both hard and soft skills. The empirical experiments demonstrate that this integration can improve the accuracy and relevance of job recommendations, leading to better career outcomes. The paper contributes to the field by offering a comprehensive framework for personality-based job matching and validating its effectiveness, paving the way for a more holistic approach to recruitment and talent management. turan, cemil/P-7273-2017; Varlamis, Iraklis/Q-9191-2018; Sardianos, Christos/AAL-2500-2020 Varlamis, Iraklis/0000-0002-0876-8167; 1999-4893 MAY 8 2025 18 5 275 10.3390/a18050275 http://dx.doi.org/10.3390/a18050275 WOS:001495769300001 J Yildiz, TA Yildiz, Tugba Aydin Exploring the Impact of ChatGPT on Improving 21st-Century Skills for Future English Teachers During Lesson Planning COMPUTERS IN THE SCHOOLS Recognizing its potential impact on educational practices, this study aims to explore the impact of ChatGPT-aided lesson planning (LP) on enhancing 21st-century skills (4Cs: critical thinking, creativity, collaboration, and communication) among pre-service English teachers (PSTs). Utilizing a qualitative case study design, the research involved two PSTs conducting internships at different high schools. The study was conducted in two stages: the first focused on identifying PSTs' needs and providing structured instructional training on ChatGPT use, LP preparation, and 4 C skills; the second evaluated the impact through weekly discussions, reflection reports, observations, and semi-structured interviews. Thematic content analysis, aided by MAXQDA 2020, revealed that ChatGPT significantly enhanced critical thinking by aiding in problem-solving and evaluating multiple perspectives. Creativity was also fostered through innovative teaching strategies, communication was seen by helping articulate ideas and facilitate discussions, and collaboration was supported by enhancing idea-sharing and brainstorming sessions. 0738-0569 1528-7033 2024 NOV 14 2024 10.1080/07380569.2024.2429534 http://dx.doi.org/10.1080/07380569.2024.2429534 NOV 2024 WOS:001377684300001 C Pantazatos, D; Grammatikou, M; Maglaris, V IEEE Pantazatos, Dimitris; Grammatikou, Mary; Maglaris, Vasilis Enhancing Soft Skills in Network Management Education: A Study on the Impact of GenAI-based Virtual Assistants 2024 IEEE GLOBAL ENGINEERING EDUCATION CONFERENCE, EDUCON 2024 IEEE Global Engineering Education Conference 15th IEEE Global Engineering Education Conference (IEEE EDUCON) MAY 08-11, 2024 GREECE IEEE, Univ Piraeus Res Ctr, Aristotle Univ Thessaloniki, Univ W Attica, MathWorks, IEEE Educ Soc, Comp Log, Aegean Airlines, Avance Car Rental, Binarylogic, IEEE Try Engn The rapid evolution of technology in educational settings has opened new avenues for enhancing learning experiences, particularly in specialized fields like network management. This paper explores the novel integration of a GenAI-based virtual assistant in a university-level network management course, focusing on its impact on developing students' soft skills, notably critical thinking and problem-solving abilities. Recognizing the increasing importance of these skills in the digital age, our study aims to assess the empirical effectiveness of this artificial intelligence-driven educational tool in fostering these competencies among students. Pantazatos, Dimitris/X-7336-2019 2165-9559 979-8-3503-9402-3; 979-8-3503-9403-0 2024 10.1109/EDUCON60312.2024.10578597 http://dx.doi.org/10.1109/EDUCON60312.2024.10578597 WOS:001289091100042 J Giordano, V; Spada, I; Chiarello, F; Fantoni, G Giordano, Vito; Spada, Irene; Chiarello, Filippo; Fantoni, Gualtiero The impact of ChatGPT on human skills: A quantitative study on twitter data TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE The novel generative Artificial Intelligence (AI) developed by OpenAI, i.e., ChatGPT, rised a great interest in both scientific and business contexts. This new wave of technological advancement typically produces deep transformation in the workplace, requiring new skills. However, none of the studies in literature provide quantitative analysis and measures on the impact of ChatGPT on human skills. To address this gap, we collected a database of 616,073 tweets about ChatGPT, and used Natural Language Processing techniques to identify the tasks users requested ChatGPT to perform, and the sentiment related to these tasks. Then, we compared these tasks with a standard taxonomy of skills (i.e., ESCO) using BERT. The results of the study underline that ChatGPT impacts 185 different skills. Moreover, we proposed a model to represent the interaction of the user and ChatGPT, useful to define four skills which are emerging for using this new technology. Giordano, Vito/JWP-2098-2024; Fantoni, Gualtiero/GWZ-8445-2022 GIORDANO, VITO/0000-0002-8149-8124; 0040-1625 1873-5509 JUN 2024 203 123389 10.1016/j.techfore.2024.123389 http://dx.doi.org/10.1016/j.techfore.2024.123389 APR 2024 WOS:001227910200001 J Toncheva, M Toncheva, Michaela MNEMONICS - KNOWN AND UNKNOWN PEDAGOGIKA-PEDAGOGY The given article deals with the issue of mnemonics, their types and their application in the learning process and daily activities. Examples in several languages and for different study subjects and areas are covered. Mnemonic techniques proposed by artificial intelligence are reviewed. The work presents the results of a survey among 301 participants aimed at revealing people's awareness of the possibilities of mnemonics and their propensity to use them. The idea that mnemonics in school should be considered from two sides - as a finished product on the one hand and as an author's realization on the other hand - has been revealed. Creating your own mnemonics involves high cognitive levels and important soft skills. 0861-3982 1314-8540 2024 96 2 S 42 55 10.53656/ped2024-2s.04 http://dx.doi.org/10.53656/ped2024-2s.04 WOS:001233664000004 C Nydén, M; Bika, D Prastacos, G; Pouloudi, N Nyden, Magnus; Bika, Dafni New Medicines Design, Development and Commercialization in the Era of AI LEADING AND MANAGING IN THE DIGITAL ERA, LMDE 2023 Lecture Notes in Information Systems and Organization 2023 International Conference on Leading and Managing in the Digital Era JUN 19-20, 2023 Athens, GREECE University of Athens, Stevens Institute of Technology The escalating demand for innovative therapies and increasing chronic disease incidence pose significant challenges to the pharmaceutical industry. Regulatory bodies are prioritizing more cost-effective, sustainable solutions with greater transparency. In response, AstraZeneca is evolving its strategies to prioritize speed, sustainability, and cost-effectiveness, while maintaining quality and patient safety. We are leveraging advancements in data-centric science, digital twin technology, and AI, including generative AI, to expedite clinical trials and streamline drug development. Our digital transformation is rooted in a profound understanding of drug substance and product, clinical supply chain planning, and manufacturing. This shift is facilitated by data, novel business processes, and human skills. We are entering a new era of digital innovations, where our pharmaceutical development expertise is strengthened by tools like generative AI and deep understanding of various scientific disciplines. This paper provides an overview of our activities and methodology for digital innovations relevant to pharmaceutical technology and development. It delves into the Drug Development Holistic Digital Twin concept, aimed at transforming our work methods, productivity, and innovation, and concludes with an update on progress and future plans. 2195-4968 2195-4976 978-3-031-65781-8; 978-3-031-65782-5 2024 69 137 155 10.1007/978-3-031-65782-5_10 http://dx.doi.org/10.1007/978-3-031-65782-5_10 WOS:001441778500010 C Sadhukhan, S; Mishra, S; Iyer, S Shih, JL; Kashihara, A; Chen, W; Ogata, H Sadhukhan, Sumitra; Mishra, Shitanshu; Iyer, Sridhar ChatGPT in Education: Risks to Fairness of Access 31ST INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION, ICCE 2023, VOL II 31st International Conference on Computers in Education (ICCE) DEC 04-08, 2023 Kyoto Univ, Matsue, JAPAN Learning & Educ Technologies Res Unit, Res Council Evidence Driven Educ, Asia Pacific Soc Comp Educ, Uchida Yoko Co Ltd, Photron Ltd Kyoto Univ In the rapidly changing ChatGPT world, human skills training is the need of the hour. With a large amount of data, ChatGPT is training itself day by day to understand human prompts and to provide appropriate results. A lot of prompt engineering courses educate learners in structuring the prompts based on how the ChatGPT engine processes any prompt and response. However, these courses do not target specific cognitive skills required by users (learners) to unfold, understand, and express what they really need and want to know from ChatGPT. In this paper, we look at ChatGPT as a tool to support knowledge acquisition and we discuss the questioning skill as an essential cognitive skill required to interact with and make optimal use of ChatGPT capabilities. We argue that risk to the fairness of access does not just stem from the monetary availability of such technologies, but it can also arise from the unpreparedness of the target users. The AI and ethics of AI literacy communities should also focus on training individuals on the cognitive skills needed to become optimal users of such technologies. 978-626-968-902-6 2023 617 621 WOS:001191920400079 J Wu, D; Zhang, JY Wu, Dang; Zhang, Jianyang Generative artificial intelligence in secondary education: Applications and effects on students' innovation skills and digital literacy PLOS ONE As generative artificial intelligence (AI) rapidly transforms educational landscapes, understanding its impact on students' core competencies has become increasingly critical for educators and policymakers. Despite growing integration of AI technologies in classrooms, there remains a significant knowledge gap regarding how these tools influence the development of essential 21st-century skills in secondary education contexts. This study addresses this gap by investigating the relationships between generative AI applications and two critical student outcomes: innovation capability and digital literacy. Through structural equation modeling analysis of data collected from 500 students across grades 7-12, the research reveals three key findings: Firstly, generative AI applications demonstrate a substantial positive effect on students' innovation capability (beta = 0.862, p < .001), enhancing critical thinking, creative problem-solving, and adaptive learning processes. Secondly, AI integration significantly improves digital literacy (beta = 0.835, p < .001) by facilitating sophisticated information processing and active technological engagement. Thirdly, a strong bidirectional relationship exists between innovation capability and digital literacy (beta = 0.791, p < .001), suggesting these competencies mutually reinforce each other in AI-enhanced learning environments. The model demonstrates robust explanatory power with excellent fit indices. By integrating the Technology Acceptance Model with Diffusion of Innovations theory, this study advances theoretical understanding of AI's educational impact while providing practical guidelines for educators. The findings underscore the importance of strategic AI integration in educational curricula and suggest specific pathways for developing critical student competencies in the digital age. 1932-6203 2025 20 5 e0323349 10.1371/journal.pone.0323349 http://dx.doi.org/10.1371/journal.pone.0323349 40344078 WOS:001488715700042 J Rusandi, MA; Ahman; Saripah, I; Khairun, DY; Mutmainnah Rusandi, M. Arli; Ahman; Saripah, Ipah; Khairun, Deasy Yunika; Mutmainnah No worries with ChatGPT: building bridges between artificial intelligence and education with critical thinking soft skills JOURNAL OF PUBLIC HEALTH This correspondence discusses the role of artificial intelligence (AI) like ChatGPT in education and research, focusing on developing critical thinking skills and maintaining academic integrity. AI can complement learning and research processes when used ethically and responsibly. Integrating specific teaching methods in education and research can help develop better critical thinking skills and a deeper understanding of the contexts in which AI is used. The article emphasizes the importance of developing critical thinking skills among students and researchers to effectively use AI and distinguish accurate information from hoaxes and misinformation. In conclusion, the collaboration between AI and humans in learning and research will yield significant benefits for individuals and society as long as critical thinking skills and academic integrity remain top priorities. Saripah, Ipah/GPK-4538-2022; Rusandi, M. Arli/AAB-7092-2021 Rusandi, M. Arli/0000-0001-7385-104X 1741-3842 1741-3850 AUG 28 2023 45 3 E602 E603 10.1093/pubmed/fdad049 http://dx.doi.org/10.1093/pubmed/fdad049 APR 2023 37099761 WOS:000978904400001 J Rivera, PR; León, AM Rivera, Paula Rodriguez; Leon, Ana Manzano Transversal competencies and artificial intelligence in higher education: perceptions and applications REDU-REVISTA DE DOCENCIA UNIVERSITARIA Currently, artificial intelligence (AI) is beginning to integrate into higher education, demonstrating its ability to personalize and enrich learning processes. This study evaluates the impact of ChatGPT, an AI tool from OpenAI, on students' learning in the Social Education degree, focusing on the design and development of practical cases. Two main areas are investigated: the influence of ChatGPT on the acquisition of crosscutting skills essential for professional development and student perceptions of its use in learning. The study was conducted at the University of Vigo with 28 Social Education students during the 2023/2024 academic year, using a mixed- methods approach of quantitative and qualitative methods. Instruments included the Cross-Cutting Skills Assessment Questionnaire for Degrees (CECTGRA), a ChatGPT usage scale, an open-ended questionnaire, and an assessment rubric. Results showed significant improvements in the development of cross-cutting skills, mastery of these skills, and perceptions of the importance of these skills for professional growth. Most students positively evaluated ChatGPT, highlighting its convenience and accuracy. The educational possibilities of integrating ChatGPT into higher education are discussed, given its potential to enhance cross-cutting skills and enrich the educational experience. Manzano León, Ana/AAX-5249-2021; Rivera, Paula/MIO-9105-2025 1696-1412 1887-4592 JUL-DEC 2024 22 2 31 47 10.4995/redu.2024.22020 http://dx.doi.org/10.4995/redu.2024.22020 WOS:001395561300003 J Kwan, P; Kadel, R; Memon, TD; Hashmi, SS Kwan, Paul; Kadel, Rajan; Memon, Tayab D.; Hashmi, Saad S. Reimagining Flipped Learning via Bloom's Taxonomy and Student-Teacher-GenAI Interactions EDUCATION SCIENCES This paper explores how generative artificial intelligence (GenAI) technologies, such as ChatGPT 4o and other AI-based conversational models, can be applied to flipped learning pedagogy to achieve enhanced learning outcomes for students. By applying Bloom's taxonomy to intentionally align educational objectives to the key phases of flipped learning, our study proposes a model for assigning learning activities to pre-class, in-class, and post-class contexts that can be enhanced by the integration of GenAI. In the pre-class phase, GenAI tools can facilitate personalised content delivery, enabling students to grasp fundamental concepts at their own pace. During class, the interactions between students, teacher, and GenAI encourage collaborative learning and real-time feedback. Post-class activities utilise GenAI to reinforce knowledge, provide instant feedback, and support continuous learning through summarisation and content generation. Furthermore, our model articulates the synergies between the three key actors: interactions between students and teachers, learning support provided by GenAI to students, and use of GenAI by teachers to enhance their teaching strategies. These human-AI interactions fundamentally reshape the flipped learning experience, making it more adaptive, engaging, and supportive of the development of 21st-century skills such as critical thinking, collaboration, communication, and creativity. ; Kadel, Rajan/ABA-8977-2021 Kwan, Wing Hing Paul/0000-0002-4959-5274; Kadel, Rajan/0000-0001-9207-2148; 2227-7102 APR 8 2025 15 4 465 10.3390/educsci15040465 http://dx.doi.org/10.3390/educsci15040465 WOS:001474951400001 J Cail, J Cail, Jessica Visualization of AI Accuracy: A Novel Assignment for the Teaching of Critical Thinking and Science Writing TEACHING OF PSYCHOLOGY Background Rapid changes brought on by generative artificial intelligence (AI) have emphasized the need to teach students to work with this technology while also developing the "robot proof" human skills future workers will need, such as creativity, communication, and critical thinking.Objective The study objective was to explore whether a fact-checking, generative-AI assignment, inserted between the outline, and first-draft stages of a student's literature review writing process, would relate to student classification, perceptions of AI accuracy, and future trust in AI-generated content.Method Students in upper and lower division psychology classes used AI to generate a literature review on their final paper topic, which they then fact-checked for accuracy and usefulness using a color-coded system.Results Lower division students expected more inaccuracy, highlighted less information as inaccurate, and reported greater future trust of AI-generated content than upper division students.Conclusion Students with more experience critically evaluating primary sources may be better equipped to detect inaccuracies within AI-generated content.Teaching Implications Teachers of any course requiring a literature review paper may use this assignment to encourage student use of AI with a critical eye toward recognizing where that content is incorrect. Cail, Jessica/JVN-0770-2024 0098-6283 1532-8023 JUL 2025 52 3 SI 285 290 10.1177/00986283241289551 http://dx.doi.org/10.1177/00986283241289551 OCT 2024 WOS:001336171900001 J Monib, WK; Qazi, A; Apong, RA; Azizan, MT; De Silva, L; Yassin, H Monib, Wali Khan; Qazi, Atika; Apong, Rosyzie Anna; Azizan, Mohammad Tazli; De Silva, Liyanage; Yassin, Hayati Generative AI and future education: a review, theoretical validation, and authors' perspective on challenges and solutions PEERJ COMPUTER SCIENCE Generative AI (Gen AI), exemplified by ChatGPT, has witnessed a remarkable surge in popularity recently. This cutting-edge technology demonstrates an exceptional ability to produce human-like responses and engage in natural language conversations guided by context-appropriate prompts. However, its integration into education has become a subject of ongoing debate. This review examines the challenges of using Gen AI like ChatGPT in education and offers effective strategies. To retrieve relevant literature, a search of reputable databases was conducted, resulting in the inclusion of twenty-two publications. Using Atlas.ti, the analysis reflected six primary challenges with plagiarism as the most prevalent issue, closely followed by responsibility and accountability challenges. Concerns were also raised about privacy, data protection, safety, and security risks, as well as discrimination and bias. Additionally, there were challenges about the loss of soft skills and the risks of the digital divide. To address these challenges, a number of strategies were identified and subjected to critical evaluation to assess their practicality. Most of them were practical and align with the ethical and pedagogical theories. Within the prevalent concepts, " ChatGPT " emerged as the most frequent one, followed by " AI, " " student, " " research, " and " education, " highlighting a growing trend in educational discourse. Moreover, close collaboration was evident among the leading countries, all forming a single cluster, led by the United States. This comprehensive review provides implications, recommendations, and future prospects concerning the use of generative AI in education. Qazi, Atika/D-9377-2016; Monib, Wali Khan/ACI-7149-2022 Monib, Wali Khan/0000-0002-9575-9305 2376-5992 DEC 3 2024 10 e2105 10.7717/peerj-cs.2105 http://dx.doi.org/10.7717/peerj-cs.2105 39650462 WOS:001374721200005 J Dahri, NA; Yahaya, N; Al-Rahmi, WM Dahri, Nisar Ahmed; Yahaya, Noraffandy; Al-Rahmi, Waleed Mugahed Exploring the influence of ChatGPT on student academic success and career readiness EDUCATION AND INFORMATION TECHNOLOGIES Enhancing student academic success and career readiness is important in the rapidly evolving educational field. This study investigates the influence of ChatGPT, an AI tool, on these outcomes using the Stimulus-Organism-Response (SOR) theory and constructs from the Technology Acceptance Model (TAM). The aim is to explore how ChatGPT impacts cognitive skill development, career-relevant knowledge and skills, academic success, and career readiness. Employing a quantitative research approach, survey data from 290 students at University Teknologi Malaysia were analyzed using Structural Equation Modeling (SEM). Findings indicate that frequent ChatGPT usage positively affects cognitive skills and career-relevant knowledge. Specifically, high-quality ChatGPT outputs significantly enhance cognitive skills (beta = 0.40, p < 0.001) and career-relevant knowledge (beta = 0.36, p < 0.001). Personalized learning experiences through ChatGPT further support cognitive development (beta = 0.23, p < 0.001) and career-relevant knowledge acquisition (beta = 0.17, p < 0.001). The study also demonstrates that improved cognitive skills contribute to higher academic success (beta = 0.35, p < 0.001) and greater career readiness (beta = 0.28, p < 0.001). However, trust in ChatGPT and access to information alone did not significantly impact cognitive skills or career-relevant knowledge. Additionally, career-relevant knowledge alone did not predict substantially career readiness, highlighting the importance of practical experience and soft skills. While ChatGPT enhances academic performance and career preparation, potential challenges include over-reliance on AI and misinformation risks. The findings highlighted the need for balanced AI integration in education, complementing traditional methods with critical evaluation skills. Future research should examine how ChatGPT can be combined with other educational strategies to improve career readiness further and address AI's limitations in educational settings. Dahri, Dr Nisar Ahmed/AFK-1350-2022; Yahaya, Noraffandy/AAX-1687-2020; Al-Rahmi, Waleed/W-4086-2019 Yahaya, Noraffandy/0000-0002-7952-5461; 1360-2357 1573-7608 MAY 2025 30 7 8877 8921 10.1007/s10639-024-13148-2 http://dx.doi.org/10.1007/s10639-024-13148-2 NOV 2024 WOS:001362280000001 J Yunianto, W; Galiç, S; Lavicza, Z Yunianto, Wahid; Galic, Selen; Lavicza, Zsolt Exploring Computational Thinking in Mathematics Education: Integrating ChatGPT with GeoGebra for Enhanced Learning Experiences INTERNATIONAL JOURNAL OF EDUCATION IN MATHEMATICS SCIENCE AND TECHNOLOGY ChatGPT has become a significant topic of interest in the field of education, prompting of the potential applications of such technology. The utilization of ChatGPT may facilitate the fostering of 21st century skills, such as computational thinking (CT) and technology, which could subsequently provide a means of offering students personalized assistance. The current study presents the experience of students undertaking a GeoGebra-based mathematics+CT task with the assistance of ChatGPT. The data was collected and analyzed, including students' screen recording, students' interaction with ChatGPT, and the questionnaire. The findings indicate that a limited number of students were able to successfully construct objects on GeoGebra with the assistance of ChatGPT. Students were unable to provide a sufficiently detailed prompt to enable them to receive guidance. Nevertheless, the majority of students perceived ChatGPT as beneficial, although they felt that its responses required adaptation. This study highlights the importance of integrating and utilizing both ChatGPT and GeoGebra to enhance CT skills. Future research may examine the relationship between the expertise of using software or writing qualified prompts on ChatGPT and the effectiveness of responses. ; Galiç, Selen/KDO-6850-2024; Lavicza, Zsolt/AAH-3896-2020 Galic, Selen/0000-0002-3524-6428; Lavicza, Zsolt/0000-0002-3701-5068; Yunianto, Wahid/0000-0003-1693-6383 2147-611X 2024 12 6 10.46328/ijemst.4437 http://dx.doi.org/10.46328/ijemst.4437 WOS:001402099400003 C Bernetti, I; Borghini, T; Capecchi, I DePaolis, LT; Arpaia, P; Sacco, M Bernetti, Iacopo; Borghini, Tommaso; Capecchi, Irene Integrating Virtual Reality and Artificial Intelligence in Agricultural Planning: Insights from the VAIFARM Application EXTENDED REALITY, PT I, XR SALENTO 2024 Lecture Notes in Computer Science International Conference on Extended Reality (XR Salento) SEP 04-07, 2024 Lecce, ITALY Univ Salento, Augmented & Virtual Real Lab TheV.A.I.F.A.R.M. (Virtual and Artificial Intelligence for Farming and Agricultural Resource Management) app explores the integration of collaborative virtual reality (VR) with generative artificial intelligence (AI), specifically utilizing ChatGPT, to enhance educational approaches within agricultural management and planning. This study aims to investigate the educational outcomes associated with the combined use of VR and AI technologies, with a particular focus on their impact on critical thinking, problem-solving abilities, and collaborative learning among university students engaged in agricultural studies. By employing VR, the project creates a simulated agricultural environment where students are tasked with various management and planning activities, offering a practical application of theoretical knowledge. The addition of ChatGPT facilitates interactive, AI-mediated dialogues, challenging students to tackle complex agricultural problems through informed decision-making processes. The research anticipates findings that suggest an improvement in student engagement and a better grasp of complicated agricultural concepts, attributed to the immersive and interactive nature of the learning experience. Furthermore, it examines the role of VR and AI in cultivating essential soft skills critical for the agricultural sector. The study contributes to the understanding of how collaborative VR and generative AI can be effectively combined to advance educational practices in agriculture, aiming for a balanced evaluation of their potential benefits without overstating the outcomes. Bernetti, Iacopo/ABZ-1446-2022 0302-9743 1611-3349 978-3-031-71706-2; 978-3-031-71707-9 2024 15027 342 350 10.1007/978-3-031-71707-9_28 http://dx.doi.org/10.1007/978-3-031-71707-9_28 WOS:001336522800028 J Stoyanova, D; Stoyanova-Petrova, S; Mileva, N Stoyanova, Diana; Stoyanova-Petrova, Silviya; Mileva, Nevena Exploring Students' and Teachers' Perceptions about Using ChatGPT in Programming Education INTERNATIONAL JOURNAL OF ENGINEERING PEDAGOGY This paper aims to study the opinions of teachers and students regarding the opportunities and challenges of using ChatGPT in programming education. The research combines quantitative data from Likert-scale questions with qualitative data from open-ended responses. The findings reveal similarities between students' and teachers' views on the advantages of using ChatGPT in programming education and its potential to develop soft skills. A difference appears in assessing the attitudes of both groups toward the disadvantages of integrating ChatGPT in education. Compared to students, teachers express much greater concern about the negative effect of artificial intelligence (AI) on academic integrity and teaching quality. The results showed that both groups positively evaluate ChatGPT as a supplementary tool in education. They believe it should complement traditional teacher-student communication rather than replace it. Based on the research findings, the authors recommend that the integration of ChatGPT into education should be preceded by adopting university AI usage policies and training for the effective use of ChatGPT. Pedagogical guidelines for integrating ChatGPT into programming education are proposed to minimise the effect of students' overreliance on AI and achieve the learning outcomes defined by Bloom's Taxonomy. Petrova, Silviya/KFR-5624-2024; Stoyanova, Diana/V-8512-2018 2192-4880 2025 15 2 15 41 10.3991/ijep.v15i2.50607 http://dx.doi.org/10.3991/ijep.v15i2.50607 WOS:001460038800002 J Watkins, R; Barak-Medina, E Watkins, Ryan; Barak-Medina, Eran AI's Influence on Human Creative Agency CREATIVITY RESEARCH JOURNAL Emerging Artificial Intelligence (AI) capabilities are redefining roles traditionally assigned to humans or tools in numerous tasks, and thereby creating tensions in professions ranging from education and engineering, to design and film. As a result, we suggest now is the time for greater vitality in a professional dialogue and research agenda on how AI, especially Generative AI, affects human creative agency. While AI poses challenges to human creative agency, it also offers growth potential, demanding a balanced approach to its opportunities and risks. To bolster a professional dialogue, we propose a framework detailing three key attributes of AI's impact on creative agency: whether AI is perceived as a competitor or a complement to human skills; AI's perceived effectiveness and performance; and, whether the AI systems perform a high-stakes or a low-stakes function. We then propose AI literacy as a moderating influence on these attributes. Our aims for this framework are to (i) serve as a starting point for developing research-based strategies and tools that will allow AI to augment human creative agency, rather than diminish it, and (ii) provide a useful foundation for conversations between creativity researchers and AI developers. 1040-0419 1532-6934 2024 DEC 6 2024 10.1080/10400419.2024.2437264 http://dx.doi.org/10.1080/10400419.2024.2437264 DEC 2024 WOS:001370561400001 J Rojek, M; Kufel, J; Bielówka, M; Mitrega, A; Kaczynska, D; Czogalik, L; Kondol, D; Palkij, K; Mielcarska, S; Bartnikowska, W Rojek, Marcin; Kufel, Jakub; Bielowka, Michal; Mitrega, Adam; Kaczynska, Dominika; Czogalik, Lukasz; Kondol, Dominika; Palkij, Kacper; Mielcarska, Sylwia; Bartnikowska, Wiktoria Exploring the performance of ChatGPT3.5 in addressing dermatological queries: a research investigation into AI capabilities PRZEGLAD DERMATOLOGICZNY Introduction: In the 21 st century's era of rapid technological advancement, ChatGPT-3.5, an artificial intelligence (AI) language model, is scrutinized for its application in dermatology. Using 119 questions from the National Specialist Examination (PES), we assess ChatGPT-3.5's performance by comparing it to human skills and addressing ethical implications. Objective: Our primary aim is to evaluate ChatGPT-3.5's proficiency in responding to 119 dermatology questions from the PES. The study emphasizes ethical considerations and compares the model's knowledge and skills to those of human dermatologists. Material and methods: Utilizing the 2023 PES question database, questions were categorized by Bloom's taxonomy and thematic content. ChatGPT-3.5, version of 3 August 2023, answered 119 questions in five sessions, allowing for a probabilistic evaluation. Statistical analyses, conducted using R Studio, assessed correctness, confidence, and dif - ficulty. Results: ChatGPT-3.5 achieved a 49.58% correct response rate, below the 60% passing threshold. No significant differences in difficulty or correlations between difficulty and certainty were observed. Varied per - formance across question types highlighted strengths and weaknesses. Despite suboptimal results, ChatGPT-3.5's differential performance offers insights, suggesting future improvements. The study advocates for ongoing research into AI integration in dermatology, envisioning a promising role for AI in assisting dermatologists. Conclusions: Ethical considerations are crucial for effective AI intro - duction, minimizing errors, and enhancing dermatological healthcare quality, fostering optimism for AI's evolving role in dermatology. Kufel, Jakub/GSN-6436-2022; Bielówka, Michał/JLL-4813-2023 Kufel, Jakub/0000-0001-7633-3600; Bartnikowska, Wiktoria/0000-0002-9303-946X 0033-2526 2084-9893 2024 111 1 26 30 10.5114/dr.2024.140796 http://dx.doi.org/10.5114/dr.2024.140796 WOS:001263918000003 J Meishar-Tal, H Meishar-Tal, Hagit ChatGPT: The Challenges It Presents for Writing Assignments TECHTRENDS This paper critically analyzes the potential impact of ChatGPT, a creative artificial intelligence tool, on learning and teaching, focusing on its impact on using writing assignments as a means of assessing knowledge. The paper examines the challenges this tool presents to learners and teachers in various aspects, including writing as a means of constructing knowledge, designing writing assignments, and assessing ChatGPT-assisted writing tasks. The paper examines the challenges posed by ChatGPT for writing from three different aspects: the role of ChatGPT as a learning support tool, the consequences of using ChatGPT for acquiring 21st-century skills, and challenges regarding the evaluation of the learners. The analysis indicates that ChatGPT might serve as a performance support system rather than a learning support tool. It also argued that incorporating ChatGPT into the learning process requires a significant degree of critical thinking from both students and teachers. It is crucial that they utilize this tool with the primary objective of enriching their thinking and writing abilities rather than seeking to circumvent the cognitive information processing mechanisms as a shortcut to produce writing products. Meishar-Tal, Hagit/K-2666-2019 8756-3894 1559-7075 JUL 2024 68 4 SI 705 710 10.1007/s11528-024-00972-z http://dx.doi.org/10.1007/s11528-024-00972-z JUN 2024 WOS:001237759100001 J Folmeg, M; Fekete, I; Koris, R Folmeg, Marta; Fekete, Imre; Koris, Rita Towards identifying the components of students' AI literacy: An exploratory study based on Hungarian higher education students' perceptions JOURNAL OF UNIVERSITY TEACHING AND LEARNING PRACTICE With the advent of the popular use of artificial intelligence (AI), the higher education (HE) sector is now facing a new challenge regarding how to exploit the educational potentials of Human-computer interaction (HCI). Developing students' AI literacy is now attracting the attention of the HE and HCI research community. This paper aims to explore HE students' perceptions of efficient and critical use of AI tools, and to systematically map the potential components of AI literacy as a new 21st century skill for HE students. This study applied a qualitative, exploratory approach in the form of semi- structured interviews with HE students. Results indicate that the participants primarily use ChatGPT for tasks such as brainstorming, topic selection, searching for information, and translation. While many find it useful for creating and reformatting texts, some encountered challenges, including generality in responses, outdated information, and issues during exams. Students highlighted its effectiveness in various academic tasks, from writing essays and CVs to language learning and transcription. Instructors' perspectives on ChatGPT varied, with some advocating for its integration, while others expressed concerns about job security and misinformation. The implications of the study call for a more systematic introduction and discussion around AI literacy in educational settings. Koris, Rita/IYT-0925-2023 Koris, Rita/0000-0003-1912-8744 1449-9789 2024 21 6 33 WOS:001296541300002 J Chaka, C Chaka, Chaka Stylised-facts view of fourth industrial revolution technologies impacting digital learning and workplace environments: ChatGPT and critical reflections FRONTIERS IN EDUCATION When the 21st century was ushered in, and in the period following its inception, there was a lot of hype about how 21st-century skills, especially the 4Cs (critical thinking, collaboration, communication, and creativity), were going to play a pivotal role for digital learning and workplace environments. Two decades later, these environments are still grappling with the specific changes brought about and the actual role played by these skills in their respective facets. Within these two decades, though, a new hype has emerged about how fourth industrial revolution (4IR) technologies are likely to affect and change the future of digital learning and workplace environments in ways never seen in previous industrial and digital revolutions. Amongst these technologies, artificial intelligence and automation are touted as some of the technologies that will change the future of digital learning and work. Against this background, this paper sets out to critically reflect on the prospects and challenges these two 4IR technologies have for digital learning and work as the 21st century is on the cusp of the third decade. It does so by analysing and discussing AI-/machine-human fused stylised facts based on ChatGPT-generated responses and on a human distillation and reworking of those responses. Chaka, Chaka/AAN-3211-2021 2504-284X JUL 28 2023 8 1150499 10.3389/feduc.2023.1150499 http://dx.doi.org/10.3389/feduc.2023.1150499 WOS:001046462400001 C Zhong, YC; Ng, DTK; Chu, SKW Shih, JL; Kashihara, A; Chen, W; Ogata, H Zhong, Yuchun; Ng, Davy Tsz Kit; Chu, Samuel Kai Wah ICCE 2023 Exploring the Social Media Discourse: the Impact of ChatGPT on Teachers' Roles and Identity 31ST INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION, ICCE 2023, VOL I 31st International Conference on Computers in Education (ICCE) DEC 04-08, 2023 Kyoto Univ, Matsue, JAPAN Learning & Educ Technologies Res Unit, Res Council Evidence Driven Educ, Asia Pacific Soc Comp Educ, Uchida Yoko Co Ltd, Photron Ltd Kyoto Univ As the use of ChatGPT in education becomes more prevalent, it is important to examine the potential impact on teachers' roles and identity. This study aimed to investigate how ChatGPT may shape teachers' roles and identity by conducting a thematic analysis of contents from WeChat posts that discuss the use of ChatGPT by teachers. The analysis focused on identifying themes related to the impact of ChatGPT on teachers' perceived self, pedagogical roles, and relationships with students. The findings suggest that ChatGPT may have both positive and negative impacts on teachers' roles and identity. On the one hand, ChatGPT can bring new possibilities to teachers allowing them to focus more on students' qualities and soft skills development and personalise feedback and assessment for students, which could reduce the workload of teachers and enhance their effectiveness. On the other hand, the use of ChatGPT may threaten the professional identity of teachers, leading to feelings of inadequacy or a loss of control over the teaching process. Furthermore, the use of ChatGPT may give rise to ethical issues in teaching and lead to a trust crisis between teachers and students. This study highlights the need for further research on the impact of ChatGPT and provides insights into the implementation of ChatGPT in education. Zainuddin, Zamzami/E-8624-2015; Ng, Tsz Kit Davy/ADD-3433-2022 Zainuddin, Zamzami/0000-0002-4851-4102; 978-626-968-901-9 2023 838 848 WOS:001195903400134 J Hojeij, Z; Kuhail, MA; El Sayary, A Hojeij, Zeina; Kuhail, Mohammad Amin; El Sayary, Areej Investigating in-service teachers' views on ChatGPT integration INTERACTIVE TECHNOLOGY AND SMART EDUCATION PurposeThis study aims investigate in-service teachers' perspectives on the integration of ChatGPT, an artificial intelligence (AI)-driven chatbot, into United Arab Emirates (UAE) private schools. As the UAE progresses towards a knowledge-based economy, aligning with the goals of the UAE 2030 vision, this research assesses the capacity of ChatGPT to enhance the educational experience within the framework of technological pedagogical content knowledge.Design/methodology/approachA mixed-methods approach is used, combining a survey assessing teachers' attitudes and a thematic analysis of open-ended responses, to explore the effectiveness, challenges and pedagogical implications of ChatGPT's use in the classroom.FindingsFindings reveal that teachers value ChatGPT for its potential to individualize learning and streamline the creation of educational materials, aligning with the shift towards student-centred approaches and the demands of 21st-century skills. However, significant challenges are noted, including ethical concerns, the need for reliable content and a necessity for extensive professional development to fully realize ChatGPT's benefits.Practical implicationsWhile ChatGPT transforms teaching and learning practices, realizing this potential requires addressing critical issues through adaptive policy-making, continuous educator training and thoughtful integration into the curriculum.Originality/valueThe study highlights the importance of a collaborative approach to dealing with the details of AI in education, ensuring that advancements like ChatGPT align with the evolving educational paradigms of the UAE. Hojeij, Zeina/AAM-8239-2021; ElSayary, Areej/ABH-4270-2022; Kuhail, Mohammad/AAS-6745-2020 1741-5659 1758-8510 2024 JUL 29 2024 10.1108/ITSE-04-2024-0094 http://dx.doi.org/10.1108/ITSE-04-2024-0094 JUL 2024 WOS:001275986900001 J Li, KC; Chong, GHL; Wong, BTM; Wu, MMF Li, Kam Cheong; Chong, Grace Ho Lan; Wong, Billy Tak Ming; Wu, Manfred Man Fat A TAM-Based Analysis of Hong Kong Undergraduate Students' Attitudes Toward Generative AI in Higher Education and Employment EDUCATION SCIENCES This study explores undergraduate students' attitudes towards generative AI tools in higher education and their perspectives on the future of jobs. It aims to understand the decision-making processes behind adopting these emerging technologies. A multidimensional model based on the technology acceptance model was developed to assess various factors, including perceived ease of use, perceived benefits, perceived concerns, knowledge of AI, and students' perceptions of generative AI's impact on the future of jobs. Data were collected through a survey distributed to 93 undergraduate students at a university in Hong Kong. The findings of multiple regression analyses revealed that these factors collectively explained 23% of the variance in frequency of use [(F(4, 78) = 5.89, p < 0.001), R-2 = 0.23]. Perceived benefits played the most significant role in determining frequency of use of generative AI tools. While students expressed mixed attitudes toward the role of AI in the future of jobs, those who voiced concerns about AI in education were more likely to view generative AI as a potential threat to job availability. The results provide insights for educators and policymakers to promote the effective use of generative AI tools in academic settings to help mitigate risks associated with overreliance, biases, and the underdevelopment of essential soft skills, including critical thinking, creativity, and communication. By addressing these challenges, higher education institutions can better prepare students for a rapidly evolving, AI-driven workforce. Li, Kam Cheong/K-5309-2012 2227-7102 JUN 20 2025 15 7 798 10.3390/educsci15070798 http://dx.doi.org/10.3390/educsci15070798 WOS:001540966800001 J Tang, CM; Chaw, LY Tang, Chun Meng; Chaw, Lee Yen Public Discussions about ChatGPT in Malaysian Education During its Initial Launch: A Qualitative Content Analysis of Newspaper Articles ELECTRONIC JOURNAL OF E-LEARNING An open access article under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License Abstract: The launch of ChatGPT in late 2022 offers a glimpse into the capability of generative artificial intelligence (AI) chatbots, as well as a future that is both exciting and filled with uncertainty about how powerful chatbots might become. ChatGPT, which has been trained on a huge dataset, can engage in a conversation with its users and respond to their questions. The launch of ChatGPT was followed by newspaper articles speculating on the transformations and impacts that ChatGPT would have on various facets of life, especially education. To gain a better understanding of what people have discussed about ChatGPT in Malaysian education during ChatGPT's initial launch, this study first searched three mainstream national Malaysian English newspapers using the search terms "ChatGPT" and "education" to identify 16 relevant newspaper articles, which were then analysed using a qualitative content analysis. The analysis revealed that the discussions regarding ChatGPT in Malaysian education in these newspaper articles could be categorised into five level-one categories: academic ethics, AI competence, ChatGPT adoption, learning design, and soft skills, which were further divided into 15 level-two subcategories. The findings of this study have various practical implications that may help academics and educational institutions better prepare for the expected increase in chatbot use by students and academics. The findings also make several theoretical contributions and provide a point of departure for future research. ; Chaw, Lee Yen/AAF-7706-2019; Tang, Chun/ABW-6615-2022; Chaw, Lee Yen/AAF-7706-2019 Tang, Chun Meng/0000-0001-6227-5200; Chaw, Lee Yen/0000-0002-1516-0600; Chaw, Lee Yen/0000-0002-1516-0600 1479-4403 JUN 2024 22 7 20 30 10.34190/ejel.22.7.3504 http://dx.doi.org/10.34190/ejel.22.7.3504 WOS:001327687800002 J Pattaray, A; Satiadji, AR; Lantang, AG Pattaray, Anas; Satiadji, Amirosa Ria; Lantang, Ayu Gardenia Revitalizing rural tourism through collaborative community participation in Mandalika MotoGP Mega event COGENT SOCIAL SCIENCES This research aims to explore socio-cultural impact of MotoGP Mega event in Mandalika on local communities. Based on previous literature, international events have been found to possess substantial potential to drive social, cultural, and economic transformations in host areas. However, there remains a gap in the literature regarding the direct impact of these events on local communities. To achieve the objective of this reason. a qualitative approach, incorporating literature reviews, observations, in-depth interviews, and Focus Group Discussions (FGDs) was adopted, with key stakeholders, including village heads, tourism awareness groups, community leaders, and tourism professional. Furthermore, data were generated using ChatGPT and analyzed through R Studio application for data visualization, ensuring comprehensive insights. The results showed that the development of human resource (HR) through both technical training and soft skills enhancement is important for improving operational efficiency and the quality of tourism services in villages surrounding Mandalika. Additionally, by applying collaboration theory, this exploration emphasizes the sole importance of synergy between the government, local communities, and the private sector in fostering sustainable tourism while preserving local cultural values. The research to make a significant contribution by providing relevant information regarding the manner in which international events can act as catalysts for sustainable social and cultural transformation. It also proposes a model of human resource development that could be effectively adopted by other areas with similar tourism potential. Satiadji, Amirosa/KMA-1710-2024 2331-1886 DEC 31 2025 11 1 2516832 10.1080/23311886.2025.2516832 http://dx.doi.org/10.1080/23311886.2025.2516832 WOS:001503345700001 J Xie, Y; Avila, S Xie, Yu; Avila, Sofia The social impact of generative LLM-based AI CHINESE JOURNAL OF SOCIOLOGY Liking it or not, ready or not, we are likely to enter a new phase of human history in which artificial intelligence (AI) will dominate economic production and social life-the AI revolution. Before the actual arrival of the AI revolution, it is time for us to speculate on how AI will impact the social world. In this article, we focus on the social impact of generative LLM-based AI, discussing societal factors that contribute to its technological development and its potential roles in enhancing both between-country and within-country social inequality. There are good indications that the US and China will lead the field and will be the main competitors for domination of AI in the world. We conjecture that the AI revolution will likely give rise to a post-knowledge society in which knowledge per se will become less important than in today's world. Instead, individual relationships and social identity will become more important. So will soft skills, including the ability to utilize AI. Avila, Sofia/MAI-3968-2025 2057-150X 2057-1518 JAN 2025 11 1 SI 31 57 10.1177/2057150X251315997 http://dx.doi.org/10.1177/2057150X251315997 FEB 2025 WOS:001433247700001 J Fares, OH Fares, Omar H. "That is scary!": consumer perceptions and discourses on ChatGPT QUALITATIVE MARKET RESEARCH PurposeThe rise of conversational artificial intelligence (AI) bots such as ChatGPT highlights users' anxieties and high expectations. This study aims to explore consumers' views of AI conversational bots and examines their societal implications, emphasizing public perception as a fundamental factor in their acceptance and integration.Design/methodology/approachThis study combines manual and automated thematic analysis to understand public sentiment by analyzing 45,844 YouTube comments. The comments are collected from the top five nonsponsored English-language YouTube videos on ChatGPT, with comments extracted using Octoparse. Key themes and their relationships are identified through manual coding and further analyzed using Leximancer to enhance the depth and accuracy of the analysis by detecting patterns in large data sets.FindingsThe analysis reveals three primary areas: empowerment through AI-enhanced capabilities, anxiety over AI-induced societal shifts and negotiating human-AI collaboration. Concerns are expressed about misinformation, privacy and the impact of AI on employment and human skills. Conversely, positive perceptions highlight AI's role in education, personal productivity and medical diagnosis. These themes categorize public sentiment into techno-skepticism, techno-realism and techno-optimism, demonstrating the complex and diverse opinions on AI technology.Originality/valueThis research bridges AI's technical aspects with its social and ethical dimensions, providing a comprehensive understanding of public sentiment towards ChatGPT. It underscores the importance of examining consumer views as a foundational step in understanding AI's broader societal impacts. Fares, Omar/ABK-1281-2022 Fares, Omar/0000-0003-0950-0661 1352-2752 1758-7646 APR 29 2025 28 3 452 473 10.1108/QMR-07-2024-0122 http://dx.doi.org/10.1108/QMR-07-2024-0122 APR 2025 WOS:001462626300001 J Fang, XQ; Chiu, TKF Fang, Xueqing; Chiu, Thomas K. F. Using Self-Determination Theory to Explain How Mind Mapping and Real-time Commenting Enhance Student Engagement and Learning Outcomes in Video Creation COMPUTERS AND EDUCATION OPEN Video creation provides students with opportunities to engage in authentic learning experiences while developing knowledge and 21st-century skills across various subjects. The student-created video activity could be an effective pedagogical approach for contemporary higher education teaching in the artificial intelligence (AI) Era. However, its full potential has yet to be realized, and more research is needed to explore learning methodologies that can enhance its effectiveness. Mind mapping (MM) and real-time commenting (RTC) are two strategies that have been shown to enhance student engagement. This study investigated the effects of MM (with vs. without) and RTC (with vs. without) on students' need satisfaction, engagement, creativity, and collaboration, using SelfDetermination Theory (SDT) to explain how the two strategies influence engagement and learning outcomes in video creation activities. We conducted an eight-week intervention study with 138 Chinese university students, using a 2 x 2 between-subjects factorial design, with four experimental groups: video creation (VC), video creation with MM (VC-MM), video creation with RTC (VC-RTC), and video creation with both MM and RTC (VCMMRTC). Our analysis revealed that: (i) MM significantly satisfied students' needs for autonomy, competence, and relatedness, while RTC significantly fulfilled their need for relatedness; (ii) MM significantly improved students' behavioral, cognitive, and agentic engagement, while RTC significantly enhanced their emotional engagement; (iii) MM significantly improved students' collaboration; and (iv) neither the MM nor RTC significantly improved students' creativity. The results highlight the effectiveness of integrating MM and RTC strategies in satisfying students' three psychological needs, enhancing four types of student engagement, and improving collaboration in video-based learning activities. With the help of generative AI tools, instructors and students can easily adopt these strategies for effective learning. Chiu, Thomas K.F./AAR-4894-2021 Chiu, Thomas K.F./0000-0003-2887-5477 2666-5573 JUN 2025 8 100254 10.1016/j.caeo.2025.100254 http://dx.doi.org/10.1016/j.caeo.2025.100254 APR 2025 WOS:001464373400001 J Quarshie, B; Poku, KM Quarshie, Benjamin; Poku, Kelcy Menkah Dynamic resonance: unpacking Ghanaian traditional knowledge through proverbs for modern socio-environmental innovation FRONTIERS IN HUMAN DYNAMICS Traditional knowledge reflects the essence of a community, embodying its truths and ancestral lineage. Preserving this knowledge is vital for maintaining identity and cultural roots. However, viewing it as the sole marker of ethnic ancestry overlooks other factors, such as genetics and the interplay of beliefs and practises. Beliefs and practises, shaped by cumulative wisdom, represent a dynamic core of traditional knowledge influenced by geography, experiences, cultural encounters, and resource availability. Tradition is not static but evolves with time, adapting to the needs of the era. Thus, it is essential to critically evaluate traditional knowledge within its temporal context to distinguish sustainable practises from those that may hinder progress. This paper examines select traditional knowledge embedded in proverbs from two Ghanaian ethnic cultures, Akan and Ewe, through the lens of 21st-century sustainable practises. The focus is to demonstrate that whilst some traditional knowledge endures, others align with modern skills like creativity, innovation, critical thinking, and collaboration-key to socio-environmental sustainability. The paper begins by appreciating Ghanaian traditional knowledge and its practical applications in daily life. It then presents a selection of proverbs with their interpretations, followed by a critical review guided by 21st-century benchmarks with the aid of ChatGPT 4.0 and Gemini 1.5 pro language modelling Artificial Intelligence (AIs) after authentication of the selected proverbs by language experts who are also vested in Ghanaian proverbs. The analysis highlights the nuanced fabric of traditional knowledge, identifying some proverbs that remain relevant and adaptable for daily usage in educational and industrial organisations to elicit 21st-century competencies. The paper concludes with recommendations for scholarly contributions and educational initiatives grounded in traditional knowledge. These initiatives aim to foster sustainable, innovative practises that meet contemporary needs, bridging cultural heritage and modernity. Quarshie, Benjamin/JHT-9291-2023 2673-2726 FEB 20 2025 7 1456870 10.3389/fhumd.2025.1456870 http://dx.doi.org/10.3389/fhumd.2025.1456870 WOS:001437765800001 J Batista, J; Mesquita, A; Carnaz, G Batista, Joao; Mesquita, Anabela; Carnaz, Goncalo Generative AI and Higher Education: Trends, Challenges, and Future Directions from a Systematic Literature Review INFORMATION (1) Background: The development of generative artificial intelligence (GAI) is transforming higher education. This systematic literature review synthesizes recent empirical studies on the use of GAI, focusing on its impact on teaching, learning, and institutional practices. (2) Methods: Following PRISMA guidelines, a comprehensive search strategy was employed to locate scientific articles on GAI in higher education published by Scopus and Web of Science between January 2023 and January 2024. (3) Results: The search identified 102 articles, with 37 meeting the inclusion criteria. These studies were grouped into three themes: the application of GAI technologies, stakeholder acceptance and perceptions, and specific use situations. (4) Discussion: Key findings include GAI's versatility and potential use, student acceptance, and educational enhancement. However, challenges such as assessment practices, institutional strategies, and risks to academic integrity were also noted. (5) Conclusions: The findings help identify potential directions for future research, including assessment integrity and pedagogical strategies, ethical considerations and policy development, the impact on teaching and learning processes, the perceptions of students and instructors, technological advancements, and the preparation of future skills and workforce readiness. The study has certain limitations, particularly due to the short time frame and the search criteria, which might have varied if conducted by different researchers. ; Carnaz, Gonçalo/GXF-8763-2022; Batista, Joao/AAG-1859-2019; Mesquita, Anabela/B-3353-2008 Batista, Joao/0000-0002-5872-5341; 2078-2489 NOV 2024 15 11 676 10.3390/info15110676 http://dx.doi.org/10.3390/info15110676 WOS:001365458100001 J Collins, J; Thompson, S; Finley, K; Phillips, B Collins, Justin; Thompson, Shruti; Finley, Kimberly; Phillips, Bradley Improving learning using a layered learning model in the ambulatory care setting CURRENTS IN PHARMACY TEACHING AND LEARNING Introduction: Layered learning models (LLMs) are becoming increasingly popular at various clinical practice sites and give rotational student pharmacists the opportunity to learn from pharmacist preceptors and resident mentors. The purpose of this article is to give additional insight into implementation of a LLM in an ambulatory care clinical practice setting. Given the expanding services of ambulatory care pharmacy practice sites, this is poised as an excellent opportunity to train both current and future pharmacists through utilization of LLM. Commentary: The LLM employed at our institution gives student pharmacists an opportunity to work within a unique team consisting of a pharmacist preceptor and a postgraduate year one and/ or postgraduate year two resident mentor if applicable. The LLM gives student pharmacists the opportunity to apply clinical knowledge into practice while refining soft skills that many student pharmacists might struggle with during pharmacy school or may not have the chance to develop prior to graduation. Embedding a resident within a LLM provides an ideal environment for preceptorship experience towards the student pharmacist while developing skills or attributes required to become an effective educator. The pharmacist preceptor in the LLM is able to teach the resident how to precept student pharmacists by tailoring their rotational experience to enhance learning. Implications: LLMs are continuing to grow in popularity in clinical practice settings. This article offers additional insight into how a LLM can improve the learning experience of everyone involved which includes student pharmacists, resident mentors, and pharmacist preceptors. 1877-1297 1877-1300 FEB 2023 15 2 119 122 10.1016/j.cptl.2023.02.016 http://dx.doi.org/10.1016/j.cptl.2023.02.016 APR 2023 36898896 WOS:000990715300001 J Tusquellas, N; Santiago, R; Palau, R Tusquellas, Natalia; Santiago, Raul; Palau, Ramon Professional Development Analytics: A Smart Model for Industry 5.0 APPLIED SCIENCES-BASEL This paper presents a novel AI-driven conceptual smart model designed to help organizations enhance workforce professional development by upskilling and reskilling employees while fostering job satisfaction and staying competitive in their markets; this novel model is called Professional Development Analytics (PDA). The model's main focus is to provide a new design model that concentrates on how artificial intelligence (AI) can optimize personalized training and how it can improve employees' technical and soft skills, enabling companies to create their talent map at the same time. By compiling personnel data and their roles within the company, AI is able to create detailed and personalized profiles. In the next stage, this information is classified, analyzed, and used to enhance current skills while also predicting future training needs. These processes result in the creation of personalized learning paths, where AI recommends customized courses tailored to each employee's unique needs. The system will be automatically fed and adjusted by means of the gathered data and continuous feedback from the employees and their supervisors. The proposed AI tools are powered by machine learning, deep learning, natural language processing, generative AI and data analytics. Our model aims to support learning and development departments by delivering precise, personalized training solutions that address employees' unique needs, enabling skill development and professional growth through an automated and customized process. Palau, Ramon/AAG-3585-2020; Tusquellas, Natalia/KEH-1740-2024 Palau, Ramon/0000-0002-9843-3116; Tusquellas, Natalia/0009-0003-5471-0526 2076-3417 FEB 2025 15 4 2057 10.3390/app15042057 http://dx.doi.org/10.3390/app15042057 WOS:001429537400001 J Ramos, HCP; Caro, OC; Bardales, ES; Huatangari, LQ; Trigoso, JAC; Guevara, JLM; Santos, RC Ramos, Heily Consepcion Portocarrero; Caro, Omer Cruz; Bardales, Einstein Sanchez; Huatangari, Lenin Quinones; Trigoso, Jonathan Alberto Campos; Guevara, Jorge Luis Maicelo; Santos, River Chavez Artificial intelligence skills and their impact on the employability of university graduates FRONTIERS IN ARTIFICIAL INTELLIGENCE Artificial intelligence (AI) has emerged as a transformative technology in multiple areas, including the labor market. Its incorporation into organizations redefines professional profiles, required skills, and employability conditions. In this context, it is essential to understand how university graduates are preparing to face these changes and what role their AI skills play in their integration into the workforce. The study aimed to analyze the level of AI skills and their impact on the employability of university graduates through a quantitative and descriptive design. A survey was conducted with a sample of 148 undergraduate and graduate graduates. The data were analyzed using descriptive statistics and visualized using graphs. The results indicated that graduates who report greater knowledge and more frequent use of AI tools, especially generative ones such as ChatGPT, are more likely to be employed in areas related to their majors and to perceive higher productivity and better professional alignment. However, a generational gap in digital skills was also identified, as well as a widespread feeling of insufficient preparation for the challenges of the current labor market. The conclusion is that AI skills are consolidating as a key differentiating factor in employability and that their formal incorporation into university curricula is urgently needed. The implications of the study point to the need for an educational transformation that integrates AI as a transversal skill, promotes ongoing teacher training, and fosters policies that guarantee inclusive education aligned with the challenges of the digital age. 2624-8212 JUL 16 2025 8 1629320 10.3389/frai.2025.1629320 http://dx.doi.org/10.3389/frai.2025.1629320 40741284 WOS:001543205100001 J Bearman, M; Tai, J; Dawson, P; Boud, D; Ajjawi, R Bearman, Margaret; Tai, Joanna; Dawson, Phillip; Boud, David; Ajjawi, Rola Developing evaluative judgement for a time of generative artificial intelligence ASSESSMENT & EVALUATION IN HIGHER EDUCATION Generative artificial intelligence (AI) has rapidly increased capacity for producing textual, visual and auditory outputs, yet there are ongoing concerns regarding the quality of those outputs. There is an urgent need to develop students' evaluative judgement - the capability to judge the quality of work of self and others - in recognition of this new reality. In this conceptual paper, we describe the intersection between evaluative judgement and generative AI with a view to articulating how assessment practices can help students learn to work productively with generative AI. We propose three foci: (1) developing evaluative judgement of generative AI outputs; (2) developing evaluative judgement of generative AI processes; and (3) generative AI assessment of student evaluative judgements. We argue for developing students' capabilities to identify and calibrate quality of work - uniquely human capabilities at a time of technological acceleration - through existing formative assessment strategies. These approaches circumvent and interrupt students' uncritical usage of generative AI. The relationship between evaluative judgement and generative AI is more than just the application of human judgement to machine outputs. We have a collective responsibility, as educators and learners, to ensure that humans do not relinquish their roles as arbiters of quality. Dawson, Phillip/F-6438-2010; Tai, Joanna/AAV-9790-2020; Ajjawi, Rola/HRC-6132-2023; Bearman, Margaret/R-1191-2019; Boud, David/R-7498-2019 Boud, David/0000-0002-6883-2722; Bearman, Margaret/0000-0002-6862-9871; Tai, Joanna/0000-0002-8984-2671; Ajjawi, Rola/0000-0003-0651-3870; Dawson, Phillip/0000-0002-4513-8287; 0260-2938 1469-297X AUG 17 2024 49 6 893 905 10.1080/02602938.2024.2335321 http://dx.doi.org/10.1080/02602938.2024.2335321 MAR 2024 WOS:001199939900001 C Shibani, A; Knight, S; Kitto, K; Karunanayake, A; Shum, SB ASSOC COMPUTING MACHINERY Shibani, Antonette; Knight, Simon; Kitto, Kirsty; Karunanayake, Ajanie; Shum, Simon Buckingham Untangling Critical Interaction with AI in Students' Written Assessment EXTENDED ABSTRACTS OF THE 2024 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2024 CHI Conference on Human Factors in Computing Sytems (CHI) MAY 11-16, 2024 Honolulu, HI Assoc Comp Machinery, ACM SIGCHI, Apple, Google, NSF, Tianqiao & Chrissy Chen Inst Artificial Intelligence (AI) has become a ubiquitous part of society, but a key challenge exists in ensuring that humans are equipped with the required critical thinking and AI literacy skills to interact with machines effectively by understanding their capabilities and limitations. These skills are particularly important for learners to develop in the age of generative AI where AI tools can demonstrate complex knowledge and ability previously thought to be uniquely human. To activate effective human-AI partnerships in writing, this paper provides a first step toward conceptualizing the notion of critical learner interaction with AI. Using both theoretical models and empirical data, our preliminary findings suggest a general lack of Deep interaction with AI during the writing process. We believe that the outcomes can lead to better task and tool design in the future for learners to develop deep, critical thinking when interacting with AI. Knight, Simon/O-1513-2013; Shibani, Antonette/D-2096-2017; Knight, Simon/AAG-7525-2019; Shibani, Antonette/GRO-5170-2022 Knight, Simon/0000-0002-8709-5780; Shibani, Antonette/0000-0003-4619-8684; Kitto, Kirsty/0000-0001-7642-7121; Buckingham Shum, Simon/0000-0002-6334-7429; 979-8-4007-0331-7 2024 10.1145/3613905.3651083 http://dx.doi.org/10.1145/3613905.3651083 WOS:001227587704045 J Mcbride, C; Lee, CH; Soep, E Mcbride, Cherise; Lee, Clifford H.; Soep, Elisabeth "Gotta Love Some Human Connection": Humanizing Data Expression in an Age of AI READING RESEARCH QUARTERLY Rapidly developing technological advances have raised new questions about what makes us uniquely human. As data and generative AI become more powerful, what does it mean to learn, teach, create, make meaning, and express ourselves, even as machines are trained to take care of these tasks for us? With youth, and in the context of literacy and media education, we embrace this moment to broaden our social imaginations. Our collaboration with journalists ages 14-25 from 2019 to 2023 has yielded a corpus of over 30 multimodal compositions constructed with and/or about AI reaching audiences in the millions. On the basis of these youth texts - produced within our participatory research at YR Media, a national STEAM learning center and platform for emerging BIPOC content creators - we developed the conceptual framework presented here: Humanizing Data Expression (HDE). The key role of expression in HDE distinguishes the human from the machine through the lens of storytelling. Analysis of this corpus (podcasts, web-based interactives, videos, radio features, online posts, social media assets) revealed four literacy practices of YR Media authors as they made sense of AI: (1) contextualize: try out AI-powered features, reveal how it works; (2) unveil authorship: introduce AI creators and processes; (3) grapple: explore tensions and paradoxes; (4) play: hack, mess with, outsmart, exaggerate AI. From these insights, we end with implications of HDE as a framework for learning and teaching AI literacy, including its potential for critically transforming data literacy practice and pedagogy across schools, teaching, and teacher education. Lee, Clifford/0000-0003-0710-0242; McBride, Cherise/0000-0002-6000-2871 0034-0553 1936-2722 OCT 2024 59 4 SI 678 689 10.1002/rrq.550 http://dx.doi.org/10.1002/rrq.550 JUN 2024 WOS:001247229000001 J Seli, P; Ragnhildstveit, A; Orwig, W; Bellaiche, L; Spooner, S; Barr, N Seli, Paul; Ragnhildstveit, Anya; Orwig, William; Bellaiche, Lucas; Spooner, Sarah; Barr, Nathaniel Beyond the Brush: Human Versus Artificial Intelligence Creativity in the Realm of Generative Art PSYCHOLOGY OF AESTHETICS CREATIVITY AND THE ARTS Several decades ago, J. P. Guilford (1950) speculated that, although artificial intelligence (AI) might one day take over much of human thinking, creativity would remain a uniquely human faculty. However, rapid advancements in AI have led to the recent development of generative models that are capable of producing high-quality creative products, casting some doubt Guilford's prediction. Here, to shed light on this issue, we explored whether human creativity retains distinct value in the emerging domain of AI-assisted digital artworks. Using DALL-E 3, we generated images based on prompts crafted by professional artists, novice artists, and an AI chatbot (ChatGPT-4). Creativity ratings from 299 participants showed that images produced from professional artist prompts were rated as most creative, followed by those generated from AI chatbot prompts, with novice artist prompts rated lowest. Further analysis suggested that this pattern may be partially explained by the semantic distance of the prompts, which followed the same pattern (i.e., professionals > AI chatbot > novices). These findings suggest that, although AI demonstrates impressive creative abilities, the worth of human creativity has not been diminished in the domain of AI-assisted outputs, which supports Guilford's view on the enduring value of human creativity. Orwig, William/HGC-4125-2022 Seli, Paul/0000-0002-5398-6999 1931-3896 1931-390X 2025 FEB 27 2025 10.1037/aca0000743 http://dx.doi.org/10.1037/aca0000743 FEB 2025 WOS:001433477200001 J Lind, M Lind, Miriam Alexa's agency: a corpus-based study on the linguistic attribution of humanlikeness to voice user interfaces AI & SOCIETY Voice-based, spoken interaction with artificial agents has become a part of everyday life in many countries: artificial voices guide us through our bank's customer service, Amazon's Alexa tells us which groceries we need to buy, and we can discuss central motifs in Shakespeare's work with ChatGPT. Language, which is largely still seen as a uniquely human capacity, is now increasingly produced-or so it appears-by non-human entities, contributing to their perception as being 'human-like.' The capacity for language is far from the only prototypically human feature attributed to 'speaking' machines; their potential agency, consciousness, and even sentience have been widely discussed in the media. This paper argues that a linguistic analysis of agency (based on semantic roles) and animacy can provide meaningful insights into the sociocultural conceptualisations of artificial entities as humanlike actors. A corpus-based analysis investigates the varying attributions of agency to the voice user interfaces Alexa, Siri, and Google Assistant in German media data. The analysis provides evidence for the important role that linguistic anthropomorphisation plays in the sociocultural attribution of agency and consciousness to artificial technological entities, and how particularly the practise of using personal names for these devices contributes to the attribution of humanlikeness: it will be highlighted how Amazon's Alexa and Apple's Siri are linguistically portrayed as sentient entities who listen, act, and have a mind of their own, whilst the lack of a personal name renders the Google Assistant much more recalcitrant to anthropomorphism. 0951-5666 1435-5655 2025 MAR 13 2025 10.1007/s00146-025-02243-8 http://dx.doi.org/10.1007/s00146-025-02243-8 MAR 2025 WOS:001443847600001