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
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			English	Article						artificial intelligence; rhetoric; large language models; political methodology; political debate		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.	[Palmer, Alexis] NYU, Dept Polit, New York, NY 10012 USA; [Spirling, Arthur] Princeton Univ, Dept Polit, Princeton, NJ USA	New York University; Princeton University	Palmer, A (corresponding author), NYU, Dept Polit, New York, NY 10012 USA.	ap6100@nyu.edu						Allen J, 2020, SCI ADV, V6, DOI 10.1126/sciadv.aay3539; [Anonymous], 1990, The clockwork muse: The predictability of artistic change; Chesney B, 2019, CALIF LAW REV, V107, P1753, DOI 10.15779/Z38RV0D15J; Coppock A, 2018, P NATL ACAD SCI USA, V115, P12441, DOI 10.1073/pnas.1808083115; Dai Yaoyao., 2023, SUMM POL METH M; Grumbach JM, 2018, PERSPECT POLIT, V16, P416, DOI 10.1017/S153759271700425X; Halterman Andrew., 2023, PREPRINT; Hu MQ, 2004, PROCEEDING OF THE NINETEENTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE SIXTEENTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE, P755; Jakesch M, 2023, P NATL ACAD SCI USA, V120, DOI 10.1073/pnas.2208839120; Lazer DMJ, 2018, SCIENCE, V359, P1094, DOI 10.1126/science.aao2998; Loewen PJ, 2012, ELECT STUD, V31, P212, DOI 10.1016/j.electstud.2011.07.003; Motoki F, 2024, PUBLIC CHOICE, V198, P3, DOI 10.1007/s11127-023-01097-2; Rapp Christof., 2009, COMPANION ARISTOTLE, P577; Rosenzweig Leah R., 2022, OPEN SCI FRAMEWORK; Schiff Kaylyn Jackson, 2022, LIARS DIVIDEND CAN P; Spirling A, 2023, NATURE, V616, P413, DOI 10.1038/d41586-023-01295-4; Stone P. J., 1966, The general inquirer: A computer approach to content analysis; Touvron H., 2023, CoRR abs/2302.13971	18	6	6	6	19	TAYLOR & FRANCIS LTD	ABINGDON	2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND	0032-3187	2041-0611		POLIT SCI	Polit. Sci.	SEP 2	2023	75	3					281	291		10.1080/00323187.2024.2335471	http://dx.doi.org/10.1080/00323187.2024.2335471		APR 2024	11	Political Science	Social Science Citation Index (SSCI)	Government & Law	RG2V3					2025-08-15	WOS:001204599400001
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			English	Article							INDIVIDUAL-DIFFERENCES; ELIZA	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.	[Jacobs, Oliver L.; Kingstone, Alan] Univ British Columbia, Dept Psychol, Vancouver, BC, Canada; [Pazhoohi, Farid] Univ Plymouth, Sch Psychol, Plymouth, England	University of British Columbia; University of Plymouth	Jacobs, OL (corresponding author), Univ British Columbia, Dept Psychol, Vancouver, BC, Canada.	ojacobs@psych.ubc.ca			Natural Sciences and Engineering Research Council of Canada [RGPIN-2022-03079]	Natural Sciences and Engineering Research Council of Canada(Natural Sciences and Engineering Research Council of Canada (NSERC)CGIAR)	The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Support for this work was provided by a Discovery Grant to AK from the Natural Sciences and Engineering Research Council of Canada (RGPIN-2022-03079) .	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Cogn.	SEP	2024	124								103733	10.1016/j.concog.2024.103733	http://dx.doi.org/10.1016/j.concog.2024.103733		AUG 2024	6	Psychology, Experimental	Social Science Citation Index (SSCI)	Psychology	C7H4U	39116598	hybrid			2025-08-15	WOS:001291042600001
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			English	Article						generative AI; Large Language Models; arguments; education; judges' reasons	ARTIFICIAL-INTELLIGENCE	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.	[Burgess, Paul; Williams, Iwan; Qu, Lizhen; Wang, Weiqing] Monash Univ, Monash, Australia	Monash University	Burgess, P (corresponding author), Monash Univ, Monash, Australia.			Qu, Lizhen/0000-0002-7764-431X; Burgess, Paul/0000-0002-5674-1735; Williams, Iwan/0000-0003-0582-0983; Wang, Weiqing/0000-0002-9578-819X				[Anonymous], 2019, Global insights on access to justice; [Anonymous], Declaration on equal access to justice for all by 2030, DOI DOI 10.1787/597F5B7F-EN; [Anonymous], 2019, Forty-two countries adopt new OECD Principles on Artificial Intelligence; Baidoo-Anu D., 2023, Journal of AI, V7, P52, DOI [DOI 10.61969/JAI.1337500, 10.2139/ssrn.4337484, DOI 10.2139/SSRN.4337484, 10.61969/jai.1337500]; Bongiovanni G., 2018, Handbook of Legal Reasoning and Argumentation, DOI [10.1007/978-90-481-9452-0, DOI 10.1007/978-90-481-9452-0]; Brewer S, 1996, HARVARD LAW REV, V109, P923, DOI 10.2307/1342258; Carlile W, 2018, PROCEEDINGS OF THE 56TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL), VOL 1, P621; Chen GZ, 2024, Arxiv, DOI arXiv:2311.09022; Corcoran Kieran, 2023, New York Times; DUTILH NOVAES C., 2021, STANFORD ENCY PHILOS; Feuerriegel S, 2024, BUS INFORM SYST ENG+, V66, P111, DOI 10.1007/s12599-023-00834-7; Frieder S., 2023, Advances in Neural Information Processing Systems, V36; Goel A, 2023, Arxiv, DOI [arXiv:2312.02296, DOI 10.48550/ARXIV.2312.02296]; Gold Michael Evan, 2018, A Primer on Legal Reasoning; Gray MA, 2024, PHILOS T R SOC A, V382, DOI 10.1098/rsta.2023.0155; Grossman Maura R, 2023, Duke Law & Technology Review, V23; Guha N, 2023, Arxiv, DOI [arXiv:2308.11462, 10.2139/ssrn.4583531, DOI 10.2139/SSRN.4583531]; Harshvardhan GM, 2020, COMPUT SCI REV, V38, DOI 10.1016/j.cosrev.2020.100285; Holland James A., 2013, Learning Legal Rules, V8th; Ji ZW, 2023, ACM COMPUT SURV, V55, DOI 10.1145/3571730; Kang XX, 2023, Arxiv, DOI arXiv:2310.14880; Katz DM, 2024, PHILOS T R SOC A, V382, DOI 10.1098/rsta.2023.0254; Koplin J., 2023, Monash Lens; Korzynski P, 2023, ENTREPR BUS ECON REV, V11, P25, DOI 10.15678/EBER.2023.110302; Lamond Grant, 2010, The Harvard Review of Philosophy, V17, P16; Lawrence J, 2019, COMPUT LINGUIST, V45, P765, DOI [10.1162/COLI_a_00364, 10.1162/COLIa00364]; LexisNexis, 2017, Lawyers and Robots Whitepaper; MacCormick N, 2010, DOXA, V33, P65; Makridakis S, 2017, FUTURES, V90, P46, DOI 10.1016/j.futures.2017.03.006; McCarthy J, 2006, AI MAG, V27, P12; Mok Jisoo, P 2024 C N AM CHAPT, V6, P419; Moss AJ, 2012, NEW ENGL J MED, V367, P2275, DOI 10.1056/NEJMoa1211107; Park J., 2014, P 1 WORKSHOP ARGUMEN, P29, DOI DOI 10.3115/V1/W14-2105; Perry Stephen., 1987, OXFORD J LEGAL STUD, V7, P215; Prakken H, 1997, Logical tools for modelling legal argument: A study of defeasible argumentation in law; Raz Joseph., 1996, Ratio Juris, V9, P349, DOI [10.1111/j.1467-9337.1996.tb00251.x, DOI 10.1111/J.1467-9337.1996.TB00251.X]; Rescala P, 2024, Arxiv, DOI arXiv:2404.00750; Roumeliotis KI, 2023, FUTURE INTERNET, V15, DOI 10.3390/fi15060192; Savelka J, 2023, PROCEEDINGS OF THE 2023 CONFERENCE ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE 2023, VOL 1, P117, DOI 10.1145/3587102.3588792; Sejnowski TJ, 2018, DEEP LEARNING REVOLUTION, P1; SUMMERS RS, 1978, CORNELL LAW REV, V63, P707; Thomson Reuters, 2023, Thomson Reuters Law Blog; Tu S Sean, 2024, Minnesota Journal of Law, Science & Technology, V25; Velarde G, 2020, Arxiv, DOI arXiv:2011.03044; Villasenor J., 2024, MJLST, V25, P25; Walton Douglas, 2002, Informal Logic, V22, DOI [10.22329/il.v22i1.2571, DOI 10.22329/IL.V22I1.2571]; Wang BS, 2023, PROCEEDINGS OF THE 61ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL 2023, VOL 1, P2717; Wang YX, 2023, Arxiv, DOI arXiv:2308.13387; Wei JS, 2022, ADV NEUR IN; Wiratunga N, 2024, Arxiv, DOI arXiv:2404.04302; Zhao WX, 2025, Arxiv, DOI [arXiv:2303.18223, DOI 10.48550/ARXIV.2303.18223]	51	2	2	3	4	QUEENSLAND UNIV TECHNOLOGY	BRISBANE	GPO  BOX 2434, BRISBANE, QLD 4001, AUSTRALIA		2652-4074		LAW TECHNOL HUMANS	Law Technol. Humans		2024	6	3					5	22		10.5204/lthj.3637	http://dx.doi.org/10.5204/lthj.3637			18	Law; Social Sciences, Interdisciplinary	Emerging Sources Citation Index (ESCI)	Government & Law; Social Sciences - Other Topics	O0M0E		gold			2025-08-15	WOS:001368158500001
J	O'Halloran, K				O'Halloran, Kieran			Digital assemblages with AI for creative interpretation of short stories	DIGITAL SCHOLARSHIP IN THE HUMANITIES			English	Article						AI literacy; assemblage; corpus stylistics; creative interpretation of literature; diffractive reading; digital stylistics; distant reading; distant-diffractive reading; Edgar Allan Poe ('The Black Cat'); Large Language Model Generative AI; literary studies; short stories; stylistics	POE	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] Kings Coll London, Sch Educ Commun & Soc, Waterloo Bridge Wing, London, England; [O'Halloran, Kieran] Kings Coll London, Sch Educ Commun & Soc, Waterloo Bridge Wing,Franklin Wilkins Bldg,150 Sta, London SE1 9NH, England	University of London; King's College London; University of London; King's College London	O'Halloran, K (corresponding author), Kings Coll London, Sch Educ Commun & Soc, Waterloo Bridge Wing,Franklin Wilkins Bldg,150 Sta, London SE1 9NH, England.	kieran.o'halloran@kcl.ac.uk		O'Halloran, Kieran/0000-0003-3424-994X				Ajana B., 2018, SELF TRACKING; Barad K., 2007, Meeting the Universe Halfway: Quantum Physics and the Entanglement of Matter and Meaning, DOI DOI 10.1086/597741; Bliss AV, 2009, EXPLICATOR, V67, P96, DOI 10.3200/EXPL.67.2.96-99; Buday M., 2014, ENGLISH MATTERS, P11; Cook Guy., 1994, Discourse and literature; Culpeper J, 2014, ROUTL ADV CORPUS LIN, V16, P9; Culpeper Jonathan., 2001, LANGUAGE CHARACTERIS; Davidson CathyN., 2017, NEW ED; DeLanda Manuel., 2016, Assemblage Theory; Deleuze G., 1994, What is Philosophy; Deleuze G., 1987, 1000 PLATEAUS CAPITA, P1980; Deleuze Gilles., 1987, DIALOGUES; Duff C, 2017, ORGANIZATION, V24, P418, DOI 10.1177/1350508416687765; Ellmann M., 2013, PSYCHOANALYTICAL LIT; Gregoriou C, 2011, ROUT STUD RHETORIC, P1; Hancock JT, 2013, LEGAL CRIMINOL PSYCH, V18, P102, DOI 10.1111/j.2044-8333.2011.02025.x; Harari Y. 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MAR 6	2024	39	2					657	689		10.1093/llc/fqad050	http://dx.doi.org/10.1093/llc/fqad050		MAR 2024	33	Humanities, Multidisciplinary; Linguistics	Social Science Citation Index (SSCI); Arts & Humanities Citation Index (A&HCI)	Arts & Humanities - Other Topics; Linguistics	UN3Z8		hybrid			2025-08-15	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			English	Article						Deep reading; ChatGPT; subject English; pedagogy; educational systems; reflexivity	ENGLISH	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] Univ Wollongong, Sch Educ, Wollongong, Australia	University of Wollongong	Weber, L (corresponding author), Univ Wollongong, Sch Educ, Wollongong, Australia.	lweber@uow.edu.au	; Weber, Lauren Alexandra/JAC-1507-2023	Weber, Lauren Alexandra/0000-0002-8297-4233; 				[Anonymous], Critical AI,; [Anonymous], 2008, Proust and the Squid: the Story and Science of the Reading Brain; Archer M., 2007, Making Our Way Through the World: Human Reflexivity and Social Mobility, DOI DOI 10.1192/BJP.112.483.211-A; Archer M. S., 2000, Being human: The problem of agency; Archer MargaretScotford., 2003, STRUCTURE AGENCY INT; Archer MS, 2012, REFLEXIVE IMPERATIVE IN LATE MODERNITY, P1, DOI 10.1017/CBO9781139108058; Australian Government Department of Education, 2022, National teacher workforce action plan; Australian Government Department of Education, 2023, Review to inform a better and fairer education system. Consultation activities; Australian Government Department of Education Teacher Education Expert Panel, 2023, Final report released; Baron N.S., 2015, WORDS ONSCREEN FATE; Carr N, 2020, The Shallows: What the Internet Is Doing to Our Brains; Davies L. M., 2023, Literary Knowing and the Making of English Teachers: The Role of Literature in Shaping English Teachers Professional Knowledge and Identities; Gibbons S, 2019, ENGL EDUC-UK, V53, P36, DOI 10.1080/04250494.2019.1568832; Goodlad Lauren M. E., 2023, Critical AI, V1, P1; Goodwyn A, 2016, ENGL TEACH-PRACT CRI, V15, P7, DOI 10.1108/ETPC-12-2015-0111; Gordon C, 2023, CONVERGENCE-US, V29, P28, DOI 10.1177/13548565221148105; Hayles NK, 2022, NEW LITERARY HIST, V53-54, P635, DOI 10.1353/nlh.2022.a898324; Hayles N.Katherine., 2010, ADE B, V150, P62, DOI [10.1632/ade.150.62, DOI 10.1632/ADE.150.62]; Herman Daniel, 2023, The Atlantic30 August; Herman Daniel, 2022, The Atlantic9 December; Kasneci E, 2023, LEARN INDIVID DIFFER, V103, DOI 10.1016/j.lindif.2023.102274; McKnight L, 2021, ENGL EDUC-UK, V55, P37, DOI 10.1080/04250494.2020.1768069; Netolicky D.M., 2018, Flip the system Australia: What matters in education; OpenAI, 2023, ChatGPT 3.5; Resch K, 2024, EUR J TEACH EDUC, V47, P564, DOI 10.1080/02619768.2022.2058928; Rutherford Leonie, 2024, Discovering a Good Read: Exploring Book Discovery and Reading for Pleasure Among Australian Teens, P11; Sahlberg P, 2023, INT J EDUC DEV, V98, DOI 10.1016/j.ijedudev.2023.102748; Semler LE, 2024, J LANG LIT CULT, V71, P41, DOI 10.1080/20512856.2024.2427574; Semler Liam E., 2017, METAPHOR, P8; Vaswani A., 2023, ARXIV; Wolf M., 2016, Tales of literacy for the 21st century; Wolf M., 2018, READER COME HOME REA; Yu H, 2023, FRONT PSYCHOL, V14, DOI 10.3389/fpsyg.2023.1181712	33	0	0	15	18	ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD	ABINGDON	2-4 PARK SQUARE, MILTON PARK, ABINGDON OX14 4RN, OXON, ENGLAND	2051-2856	2051-2864		J LANG LIT CULT	J. Lang. Lit. Cult.	JAN 2	2024	71	1			SI		57	72		10.1080/20512856.2024.2427567	http://dx.doi.org/10.1080/20512856.2024.2427567		NOV 2024	16	Language & Linguistics; Literature	Arts & Humanities Citation Index (A&HCI)	Linguistics; Literature	S3M5W					2025-08-15	WOS:001367006600001
J	Riemer, K; Peter, S				Riemer, Kai; Peter, Sandra			Conceptualizing generative AI as style engines: Application archetypes and implications	INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT			English	Article						Generative AI; Large language models; Style engines; AI assistants; AI agents	LARGE LANGUAGE MODELS; ARTIFICIAL-INTELLIGENCE	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.	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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			English	Article								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.	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J	Adamcová, S				Adamcova, Silvia			Artificial Intelligence and its Impact on Teaching, Learning and Work	MUTTERSPRACHE			German	Article						Artificial Intelligence; future competencies; ChatGPT; Large Language Models; digital language learning		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.	[Adamcova, Silvia] Wirtschaftsuniv Bratislava, Lehrstuhl Linguist & Translatol, Fak Angew Sprachen, Bratislava, Slovakia		Adamcová, S (corresponding author), Wirtschaftsuniv Bratislava, Lehrstuhl Linguist & Translatol, Fak Angew Sprachen, Bratislava, Slovakia.	silvia.adamcova@euba.sk						Adamcova Livia, 2018, Lingua et vita, V14, P9; Adamcova Silvia, 2023, Journal of Linguistics and Language Teaching, V14, P187; Alkaissi H, 2023, CUREUS J MED SCIENCE, V15, DOI 10.7759/cureus.35179; Bar M., 2019, Das Lehren und Lernen von Fremdund Zweitsprachen im digitalen Wandel, P12; Bender EM, 2021, PROCEEDINGS OF THE 2021 ACM CONFERENCE ON FAIRNESS, ACCOUNTABILITY, AND TRANSPARENCY, FACCT 2021, P610, DOI 10.1145/3442188.3445922; Beutel G, 2023, CRIT CARE, V27, DOI 10.1186/s13054-023-04425-6; Blossfeld Hans-Peter, 2018, Digitale Souvereinitat und Bildung; Brtihl Volker, 2023, Wirtschafisdienst, V8, P521; Hrdlickova Z, 2018, OVERCOMING THE CHALLENGES AND BARRIERS IN OPEN EDUCATION (DISCO 2018), P178; KI.NRW, 2023, KI-Schltisselbegriffe KI; Kugoth Jana., 2023, Vorstandin Stars ither Chancen neuer Technik: KI wird kiinftig bei VW eine noch grol3ere Rolle spielen; Lassebie J., 2022, OECD Social, Employment and Migration Working Papers, V282, DOI DOI 10.1787/646AAD77-EN; Marr B., 2023, Forbes; Middeke Annegret, 2021, Fachlich-Digital-Regional: Perspektiven auf das Sprachenlernen und -lehren, P169; Paiva R, 2020, LECT NOTES ARTIF INT, V12163, P448, DOI 10.1007/978-3-030-52237-7_36; Perrigo B., 2023, Time; Pokrivcakova S, 2019, J LANG CULT EDUC, V7, P135, DOI 10.2478/jolace-2019-0025; Salam E., 2022, GUARDIAN; Schmidt T., 2016, Der fremdsprachliche Unterricht Englisch, V144, P2; Schmidt T., 2022, Anglistik: International Journal of English Studies, V33, P165; Schmidt Torben, 2019, Das Lehren und Lernen von Fremdund Zweitsprachen im digitalen Wandel, P228; Schramm Karen, 2019, Das Lehren und Lernen von Fremdund Zweitsprachen im digitalen Wandel. Arbeitspapiere der 39. Friihjahreskonferenz zur Erforschung des Fremdsprachenunterrichts, P237; Thomas Martina, 2021, Jahrbuch der berufsund wirtschaftspadagogischen Forschung, P37	23	0	0	11	17	GESELLSCHAFT DEUTSCHE SPRACHE	WIESBADEN	SPIEGELGASSE 13, D-65183 WIESBADEN, GERMANY	0027-514X			MUTTERSPRACHE	Muttersprache	SEP	2024	134	3					251	267		10.53371/61178	http://dx.doi.org/10.53371/61178			17	Language & Linguistics	Arts & Humanities Citation Index (A&HCI)	Linguistics	J5I5Z					2025-08-15	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			English	Article						deep learning; neural networks; large language models; interpretability; psycholinguistics; cognitive development; philosophy of cognitive science	CONNECTIONISM; LANGUAGE; MODELS	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 Whitman] Brown Univ, Dept Philosophy, Providence, RI USA; [McGrath, Sam Whitman; Russin, Jacob; Feiman, Roman] Brown Univ, Dept Cognit & Psychol Sci, Providence, RI 02912 USA; [Russin, Jacob; Pavlick, Ellie] Brown Univ, Dept Comp Sci, Providence, RI USA; [Pavlick, Ellie; Feiman, Roman] Brown Univ, Program Linguist, Providence, RI 02912 USA	Brown University; Brown University; Brown University; Brown University	Feiman, R (corresponding author), Brown Univ, Dept Cognit & Psychol Sci, Providence, RI 02912 USA.; Feiman, R (corresponding author), Brown Univ, Program Linguist, Providence, RI 02912 USA.	roman_feiman@brown.edu		McGrath, Sam/0009-0000-5383-1885				Brown TB, 2020, Arxiv, DOI [arXiv:2005.14165, DOI 10.48550/ARXIV.2005.14165]; Bowers JS, 2022, BEHAV BRAIN SCI, V46, DOI 10.1017/S0140525X22002813; Buckner C, 2023, BRIT J PHILOS SCI, V74, P681, DOI 10.1086/714960; Chen A, 2025, Arxiv, DOI arXiv:2309.07311; Elhage N, 2021, Transformer Circuits Thread; Feiman R, 2022, COGNITIVE PSYCHOL, V135, DOI 10.1016/j.cogpsych.2022.101473; Firestone C, 2020, P NATL ACAD SCI USA, V117, P26562, DOI 10.1073/pnas.1905334117; FODOR JA, 1988, COGNITION, V28, P3, DOI 10.1016/0010-0277(88)90031-5; Geiger Atticus, 2021, Advances in Neural Information Processing Systems, V34; Gleitman L., 1990, Language acquisition, V1, P3, DOI [10.1207/s15327817la01012, DOI 10.1207/S15327817LA01012]; Golan T, 2020, P NATL ACAD SCI USA, V117, P29330, DOI 10.1073/pnas.1912334117; Hanna M, 2023, Arxiv, DOI arXiv:2305.00586; Kirov C, 2018, Transactions of the Association for Computational Linguistics, V6, P651, DOI [10.1162/tacl_a_00247, DOI 10.1162/TACLA00247]; Konkle T, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-28091-4; Lake BM, 2023, NATURE, V623, P115, DOI 10.1038/s41586-023-06668-3; Linzen T, 2021, ANNU REV LINGUIST, V7, P195, DOI 10.1146/annurev-linguistics-032020-051035; Manning CD, 2020, P NATL ACAD SCI USA, V117, P30046, DOI 10.1073/pnas.1907367117; McClelland J.L., 1986, Parallel distributed processing: Explorations in the microstructure of cognition; Meng K, 2022, ADV NEUR IN; Merullo J, 2024, Arxiv, DOI arXiv:2310.08744; Misra K, 2024, Arxiv, DOI arXiv:2403.19827; Olsson Catherine, 2022, Transformer Circuits Thread; Piantadosi S., 2023, MODERN LANGUAGE MODE, DOI lingbuzz/007180; PINKER S, 1988, COGNITION, V28, P73, DOI 10.1016/0010-0277(88)90032-7; Quilty-Dunn J, 2022, BEHAV BRAIN SCI, V46, DOI 10.1017/S0140525X22002849; Schrimpf M, 2020, bioRxiv, DOI [10.1101/407007, 10.1101/407007v1, DOI 10.1101/407007, 10.1101/407007, DOI 10.1101/407007V1]; Seidenberg MS, 2014, COGNITIVE SCI, V38, P1190, DOI 10.1111/cogs.12147; SMOLENSKY P, 1988, BEHAV BRAIN SCI, V11, P1, DOI 10.1017/S0140525X00052432; Smolensky P., 2022, arXiv, DOI DOI 10.48550/ARXIV.2205.01128; Tenney I, 2019, 57TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2019), P4593; Traylor A., 2023, Can neural networks learn implicit logic from physical reasoning?; Tucker M, 2021, FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL-IJCNLP 2021, P862; Vong WK, 2024, SCIENCE, V383, P504, DOI 10.1126/science.adi1374; Wang Kevin, 2022, arXiv; Warstadt A, 2024, Arxiv, DOI [arXiv:2208.07998, 10.48550/ARXIV.2208.07998, DOI 10.48550/ARXIV.2208.07998]; Whittington JCR, 2020, CELL, V183, P1249, DOI 10.1016/j.cell.2020.10.024; Wilcox Ethan Gotlieb., 2023, Linguistic Inquiry, P1, DOI [10.1162/linga00491, DOI 10.1162/LINGA00491]; Yamins DLK, 2014, P NATL ACAD SCI USA, V111, P8619, DOI 10.1073/pnas.1403112111	38	1	2	3	10	SAGE PUBLICATIONS INC	THOUSAND OAKS	2455 TELLER RD, THOUSAND OAKS, CA 91320 USA	0963-7214	1467-8721		CURR DIR PSYCHOL SCI	Curr. 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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			English	Article						Education; Sustainable development; Computational modeling; Systems thinking; Programming profession; Software systems; Green products; 21st-century skills; computer science (CS); creative pedagogy; foundational education; future thinking		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.	[Kalluri, Balaji; Prasad, Prajish; Sharma, Prakrati; Chippa, Divyaansh] FLAME Univ, Sch Comp & Data Sci, Pune 412115, Maharashtra, India		Kalluri, B (corresponding author), FLAME Univ, Sch Comp & Data Sci, Pune 412115, Maharashtra, India.	balaji.kalluri@flame.edu.in	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	Kalluri's Urban Design and Open-innovation Studio (KUDOS) at FLAME University	Kalluri's Urban Design and Open-innovation Studio (KUDOS) at FLAME University	This work was supported by the seed fund given to Kalluri's Urban Design and Open-innovation Studio (KUDOS) at FLAME University.	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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			English	Article						dentist; artificial intelligence; implications; public health dentistry; chatgpt		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.	[Tiwari, Anushree] Amer Acad Orthopaed Surg, Clin Qual & Value, Rosemont, IL 60018 USA; [Kumar, Amit] All India Inst Med Sci, Dept Dent, Patna, India; [Jain, Shailesh] Sharda Univ, Sch Dent Sci, Dept Prosthodont & Crown & Bridge, Greater Noida, India; [Dhull, Kanika S.] KIIT Univ, Dept Pedodont & Prevent Dent, Kalinga Inst Dent Sci, Bhubaneswar, India; [Sajjanar, Arunkumar] Swargiya Dadasaheb Kalmegh Smruti Dent Coll & Hosp, Dept Pediat & Prevent Dent, Nagpur, India; [Puthenkandathil, Rahul] Nitte Univ, AB Shetty Mem Inst Dent Sci ABSMIDS, Dept Prosthodont & Crown & Bridge, Mangalore, India; [Paiwal, Kapil] Daswani Dent Coll & Res Ctr, Dept Oral & Maxillofacial Pathol, Kota, India; [Singh, Ramanpal] New Horizon Dent Coll & Res Inst, Oral Med & Radiol, Bilaspur, India	All India Institute of Medical Sciences (AIIMS) Patna; Sharda University; Kalinga Institute of Industrial Technology (KIIT); NITTE (Deemed to be University)	Tiwari, A (corresponding author), Amer Acad Orthopaed Surg, Clin Qual & Value, Rosemont, IL 60018 USA.	tiwarianushree88@gmail.com	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; 				Agrawal P, 2022, CUREUS J MED SCIENCE, V14, DOI 10.7759/cureus.27405; Akhter HM, 2023, CUREUS J MED SCIENCE, V15, DOI 10.7759/cureus.34752; Biswas S, 2023, RADIOLOGY, V307, DOI 10.1148/radiol.223312; Fatani B, 2023, CUREUS J MED SCIENCE, V15, DOI 10.7759/cureus.37285; Giansanti D, 2022, INT J ENV RES PUB HE, V19, DOI 10.3390/ijerph191911907; Islam NM, 2022, J DENT EDUC, V86, P1545, DOI 10.1002/jdd.13010; Jungwirth David, 2023, Int J Environ Res Public Health, V20, DOI 10.3390/ijerph20054541; Kumar A. 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J	Jung, DW; Suh, S				Jung, Dawool; Suh, Sungeun			Enhancing Soft Skills through Generative AI in Sustainable Fashion Textile Design Education	SUSTAINABILITY			English	Article						soft skill enhancement; Design Sprint; generative AI; AI-based fashion textile design education; sustainable fashion textile development	COMPETENCE	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.	[Jung, Dawool; Suh, Sungeun] Gachon Univ, Coll Social Sci, Dept Fash Design & Merchandising, Seongnam 13120, Gyeonggi Do, South Korea	Gachon University	Suh, S (corresponding author), Gachon Univ, Coll Social Sci, Dept Fash Design & Merchandising, Seongnam 13120, Gyeonggi Do, South Korea.	dawooljung@gachon.ac.kr; sesuh@gachon.ac.kr	Suh, Sungeun/GYV-6085-2022	Jung, Dawool/0000-0002-8424-5261	Gachon University;  [GCU-202304740001]	Gachon University; 	This work was supported by the Gachon University research fund of 2023 (GCU-202304740001).	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J	González-Rico, P; Sintes, ML				Gonzalez-Rico, Pablo; Sintes, Mireia Lluch			Empowering Soft Skills through Artificial Intelligence and Personalised Mentoring	EDUCATION SCIENCES			English	Article						educational technology; personalised tutoring; soft skills; artificial intelligence; higher education		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] Univ San Pablo CEU, Business Management Dept, Madrid 28040, Spain; [Sintes, Mireia Lluch] Univ Valencia, Social Psychol Dept, Valencia 46010, Spain	San Pablo CEU University; University of Valencia	González-Rico, P (corresponding author), Univ San Pablo CEU, Business Management Dept, Madrid 28040, Spain.	pablo.gonzalezrico@ceu.es; lluchsin@alumni.uv.es		Gonzalez Rico, Pablo/0000-0003-0498-0248				Agncia per a la Qualitat del Sistema Universitari de Catalunya, 2014, Empleabilidad y Competencias de Los Recin Titulados: La Opinin de Empresas e Instituciones; Anthonysamy L, 2021, EDUC INF TECHNOL, V26, P6881, DOI 10.1007/s10639-021-10518-y; Antonius F., 2023, International Journal of Humanities Education and Social Sciences, V3; Cardona M. A., 2023, Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations; Crovetto A., 2023, Future Today, V4, P29, DOI [10.52749/fh.v4i1.6, DOI 10.52749/FH.V4I1.6]; Efendi M., 2023, J. 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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			English	Article								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; Sorin, Vera; Klang, Eyal] Chaim Sheba Med Ctr, Dept Diagnost Imaging, Ramat Gan, Israel; [Brin, Dana; Sorin, Vera; Klang, Eyal] Tel Aviv Univ, Fac Med, Tel Aviv, Israel; [Vaid, Akhil; Charney, Alexander W.] Icahn Sch Med Mt Sinai, Charles Bronfman Inst Personalized Med, New York, NY USA; [Soroush, Ali] Icahn Sch Med Mt Sinai, Div Data Driven & Digital Med D3M, New York, NY USA; [Glicksberg, Benjamin S.] Icahn Sch Med Mt Sinai, Hasso Plattner Inst Digital Hlth, Nyc, NY USA; [Nadkarni, Girish] Icahn Sch Med Mt Sinai, Charles Bronfman Inst Personalized Med, Div Data Driven & Digital Med D3M, New York, NY USA	Chaim Sheba Medical Center; Tel Aviv University; Tel Aviv University; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai	Brin, D (corresponding author), Chaim Sheba Med Ctr, Dept Diagnost Imaging, Ramat Gan, Israel.; Brin, D (corresponding author), Tel Aviv Univ, Fac Med, Tel Aviv, Israel.	dannabrin@gmail.com	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				Ayers JW, 2023, JAMA INTERN MED, V183, P589, DOI 10.1001/jamainternmed.2023.1838; Gilson A, 2023, JMIR MED EDUC, V9, DOI 10.2196/45312; Howley LD, 2021, ACAD MED, V96, P1247, DOI 10.1097/ACM.0000000000004217; Jiang LY, 2023, NATURE, V619, P357, DOI 10.1038/s41586-023-06160-y; John JT, 2023, TEACH LEARN MED, V35, P218, DOI 10.1080/10401334.2022.2039154; Kung TH, 2023, PLOS DIGIT HEALTH, V2, DOI 10.1371/journal.pdig.0000198; Li R, 2023, JAMA INTERN MED, V183, P596, DOI 10.1001/jamainternmed.2023.1835; Liebrenz M, 2023, LANCET DIGIT HEALTH, V5, pE105, DOI 10.1016/S2589-7500(23)00019-5; Mladenovic J, 2023, ACAD MED, V98, P444, DOI 10.1097/ACM.0000000000005051; Nazario-Johnson L, 2023, J AM COLL RADIOL, V20, P1004, DOI 10.1016/j.jacr.2023.06.008; Nori H, 2023, Arxiv, DOI [arXiv:2303.13375, DOI 10.48550/ARXIV.2303.13375]; Sharma Akshita, 2019, J Grad Med Educ, V11, P412, DOI 10.4300/JGME-D-19-00099.1; Sorin V, 2023, NPJ BREAST CANCER, V9, DOI 10.1038/s41523-023-00557-8; Sorin V, 2023, J CANCER RES CLIN, V149, P9505, DOI 10.1007/s00432-023-04824-w; usmle, Work to relaunch USMLE Step. 2 CS discontinued; usmle, USMLE Physician Tasks/Competencies|USMLE; Yudkowsky R, 2021, ACAD MED, V96, P1250, DOI 10.1097/ACM.0000000000004209	17	153	155	14	60	NATURE PORTFOLIO	BERLIN	HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY	2045-2322			SCI REP-UK	Sci Rep	OCT 1	2023	13	1							16492	10.1038/s41598-023-43436-9	http://dx.doi.org/10.1038/s41598-023-43436-9			5	Multidisciplinary Sciences	Science Citation Index Expanded (SCI-EXPANDED)	Science & Technology - Other Topics	U4ER9	37779171	gold, Green Published			2025-08-15	WOS:001084350000002
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			English	Article						ChatGPT; AI tools; latent profile analysis; dependency; 21st-century skills	STUDENTS; TECHNOLOGY	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.	[Wijaya, Tommy Tanu; Yu, Qingchun; Cao, Yiming] Beijing Normal Univ, Sch Math Sci, Beijing 100088, Peoples R China; [Wijaya, Tommy Tanu; Yu, Qingchun; Cao, Yiming] Natl Res Inst Math Teaching Mat, Beijing 100190, Peoples R China; [He, Yahan] Capital Normal Univ, Sch Math Sci, Beijing 100048, Peoples R China; [Leung, Frederick K. S.] Beijing Normal Univ, Coll Educ Future, Zhuhai 519087, Peoples R China	Beijing Normal University; Capital Normal University; Beijing Normal University	Wijaya, TT (corresponding author), Beijing Normal Univ, Sch Math Sci, Beijing 100088, Peoples R China.; Wijaya, TT (corresponding author), Natl Res Inst Math Teaching Mat, Beijing 100190, Peoples R China.; Leung, FKS (corresponding author), Beijing Normal Univ, Coll Educ Future, Zhuhai 519087, Peoples R China.	202139130001@mail.bnu.edu.cn; yuqc@bnu.edu.cn; caoym@bnu.edu.cn; b454@cnu.edu.cn; frederickleung@hku.hk	; 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; 	National Research Institute for Mathematics Teaching Materials;  [2023GH-ZDA-JJ-Y-04]	National Research Institute for Mathematics Teaching Materials; 	This research was funded by the National Research Institute for Mathematics Teaching Materials (2023GH-ZDA-JJ-Y-04).	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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			English	Article						Artificial intelligence; distance education; English for Specific Purposes; ChatGPT; higher education; smart technologies; soft skills	ARTIFICIAL-INTELLIGENCE; ONLINE EDUCATION	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.	[Borkovska, Inna; Kolosova, Hanna; Kozubska, Iryna; Antonenko, Inna] Natl Tech Univ Ukraine Igor Sikorsky Kyiv Polytech, Fac Linguist, Dept English Language Humanities, Kiev, Ukraine		Kozubska, I (corresponding author), Natl Tech Univ Ukraine Igor Sikorsky Kyiv Polytech, Fac Linguist, Dept English Language Humanities, Kiev, Ukraine.	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APR	2024					SI		56	72		10.24093/awej/ChatGPT.3	http://dx.doi.org/10.24093/awej/ChatGPT.3			17	Language & Linguistics	Emerging Sources Citation Index (ESCI)	Linguistics	TZ3Y7		Green Submitted			2025-08-15	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			English	Article						artificial intelligence; generative AI; AI-mediated communication; business education; soft skills	SOFT SKILLS; INTELLIGENCE; LEADERSHIP	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.	[Cardon, Peter; Aritz, Jolanta] Univ Southern Calif, Los Angeles, CA USA; [Fleischmann, Carolin] Rosenheim Tech Univ Appl Sci, Rosenheim, Germany; [Logemann, Minna] Baruch Coll, New York, NY USA; [Heidewald, Jeanette] Indiana Univ, Bloomington, IN USA; [Swartz, Stephanie] Hsch Mainz, Mainz, Germany; [Cardon, Peter] Univ Southern Calif, 3225 W Mossey Creek Ln, South Jordan, UT 84095 USA	University of Southern California; City University of New York (CUNY) System; Baruch College (CUNY); Indiana University System; Indiana University Bloomington; University of Southern California	Cardon, P (corresponding author), Univ Southern Calif, 3225 W Mossey Creek Ln, South Jordan, UT 84095 USA.	cardon@marshall.usc.edu	; Heidewald, Jeanette/JRX-9144-2023; Cardon, Peter/MIN-0877-2025	Cardon, Peter/0000-0002-4574-4439; Fleischmann, Carolin/0009-0001-5475-994X				Anthony S, 2016, BUS PROF COMMUN Q, V79, P360, DOI 10.1177/2329490616642247; Beauchene V., 2023, BCG; Biro M.M., 2012, Forbes; Cardon P, 2023, BUS PROF COMMUN Q, V86, P257, DOI 10.1177/23294906231176517; Cardon PW, 2023, INT J BUS COMMUN, V60, P1095, DOI 10.1177/23294884211037009; Cardon Peter W., 2023, arXiv, DOI [10.31235/osf.io/b3ezy, DOI 10.31235/OSF.IO/B3EZY]; Chowdhury S., 2023, AACSB; Chui M., 2023, The Economic Potential of Generative AI; Davenport T. 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Prof. Commun. Q.	JUN	2024	87	2					223	246		10.1177/23294906231208166	http://dx.doi.org/10.1177/23294906231208166		NOV 2023	24	Communication	Emerging Sources Citation Index (ESCI)	Communication	RE1X8					2025-08-15	WOS:001100609100001
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			English	Article						prompt engineering; artificial intelligence; 21st century skills; ChatGPT; digital skills; critical online reasoning; LLM	APOPTOSIS	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.	[Federiakin, Denis; Molerov, Dimitri; Zlatkin-Troitschanskaia, Olga; Maur, Andreas] Johannes Gutenberg Univ Mainz, Dept Business & Econ Educ, Mainz, Germany	Johannes Gutenberg University of Mainz	Federiakin, D (corresponding author), Johannes Gutenberg Univ Mainz, Dept Business & Econ Educ, Mainz, Germany.	denis.federiakin@uni-mainz.de	Zlatkin-Troitschanskaia, O./AAM-8286-2020; Federiakin, Denis/P-8505-2015		German Research Foundation [5404]	German Research Foundation(German Research Foundation (DFG))	The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research work was conducted in the context of the research Unit CORE (Critical Online Reasoning in Higher Education) funded, by the German Research Foundation (Funding number: 5404).	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Educ.	NOV 29	2024	9								1366434	10.3389/feduc.2024.1366434	http://dx.doi.org/10.3389/feduc.2024.1366434			14	Education & Educational Research	Emerging Sources Citation Index (ESCI)	Education & Educational Research	P2E2B		gold			2025-08-15	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			English	Article						AI; critical thinking; written communication; engineering; soft skills; higher education	EMPLOYABILITY SKILLS	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.	[Miron-Merida, Vicente Antonio; Garcia-Garcia, Rebeca Maria] Tecnol Monterrey, Sch Engn & Sci, Monterrey, Mexico	Tecnologico de Monterrey	Mirón-Mérida, VA; García-García, RM (corresponding author), Tecnol Monterrey, Sch Engn & Sci, Monterrey, Mexico.	vicente.miron.m@tec.mx; rebeca.garcia.garcia@tec.mx			Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico	Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico	We thank the students from the TA2006B course for its collaboration and interest on providing the studied material; in the same way, we acknowledge the partial financial support of Writing Lab, Institute for the Future of Education, Tecnologico de Monterrey, Mexico, in the preparation of this manuscript.	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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			English	Article; Early Access						ChatGPT; lesson plan; 21st century skills; teacher education		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.	[Yildiz, Tugba Aydin] Zonguldak Bulent Ecevit Univ, Egitim Fakult, TR-67500 Kdz Eregli, Turkiye	Zonguldak Bulent Ecevit University	Yildiz, TA (corresponding author), Zonguldak Bulent Ecevit Univ, Egitim Fakult, TR-67500 Kdz Eregli, Turkiye.	tugbaaydinyildiz5@gmail.com						ahin H., 2020, The Reading Matrix: An International Online Journal, V20, P167; Ananiadou K., 2009, OECD Education Working Papers, DOI DOI 10.1787/218525261154; Biletska I.O., 2021, Linguist. Cult. 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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			English	Article						ChatGPT; Generative Artificial Intelligence; Natural Language Processing; Skills; ESCO	ARTIFICIAL-INTELLIGENCE; EMPLOYMENT; JOBS; EXTRACTION; FUTURE; TOPICS	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; Chiarello, Filippo] Univ Pisa, Dept Energy Syst Terr & Construct Engn, Largo Lucio Lazzarino 2, I-56122 Pisa, Italy; [Spada, Irene; Fantoni, Gualtiero] Univ Pisa, Dept Civil & Ind Engn, Largo Lucio Lazzarino 2, I-56122 Pisa, Italy; [Giordano, Vito; Spada, Irene; Chiarello, Filippo; Fantoni, Gualtiero] Business Engn Data Sci B4DS Res Lab, Pisa, Italy	University of Pisa; University of Pisa	Giordano, V (corresponding author), Univ Pisa, Dept Energy Syst Terr & Construct Engn, Largo Lucio Lazzarino 2, I-56122 Pisa, Italy.; Giordano, V (corresponding author), Business Engn Data Sci B4DS Res Lab, Pisa, Italy.	vito.giordano@unipi.it; irene.spada@phd.unipi.it; filippo.chiarello@unipi.it; gualtiero.fantoni@unipi.it	Giordano, Vito/JWP-2098-2024; Fantoni, Gualtiero/GWZ-8445-2022	GIORDANO, VITO/0000-0002-8149-8124; 	PNRR-M4C2-Investimento 1.3, "FAIR-Future Artificial Intelligence Research"-Spoke 1 "Human-centered AI" - European Commission under the Nexteneration EU program [PE00000013]; PRA 2022-23 project - University of Pisa; CIMEA (Centro Informazioni Mobilita Equivalenze Accademiche)	PNRR-M4C2-Investimento 1.3, "FAIR-Future Artificial Intelligence Research"-Spoke 1 "Human-centered AI" - European Commission under the Nexteneration EU program; PRA 2022-23 project - University of Pisa; CIMEA (Centro Informazioni Mobilita Equivalenze Accademiche)	This research has been partly funded by PNRR-M4C2-Investimento 1.3, Partenariato Esteso PE00000013-"FAIR-Future Artificial Intelligence Research"-Spoke 1 "Human-centered AI", funded by the European Commission under the Nexteneration EU program and by PRA 2022-23 project "EduSkillMeter, a text mining -based tool to support universities & companies to be in line with SDGs", funded by University of Pisa. This research has been partly funded by CIMEA (Centro Informazioni Mobilita Equivalenze Accademiche) under the joitn agreeement "Joint Observatory CIMEA-UNIPI on higher edu skills and competences".	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Forecast. Soc. Chang.	JUN	2024	203								123389	10.1016/j.techfore.2024.123389	http://dx.doi.org/10.1016/j.techfore.2024.123389		APR 2024	24	Business; Regional & Urban Planning	Social Science Citation Index (SSCI)	Business & Economics; Public Administration	RL8L3		hybrid			2025-08-15	WOS:001227910200001
J	Toncheva, M				Toncheva, Michaela			MNEMONICS - KNOWN AND UNKNOWN	PEDAGOGIKA-PEDAGOGY			English	Article						learning, mnemonics; creativity; memory; artificial intelligence; ChatGPT		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.	[Toncheva, Michaela] Sofia Univ St Kliment Ohridski, Sofia, Bulgaria	University of Sofia	Toncheva, M (corresponding author), Sofia Univ, Sofia, Bulgaria.	mihaela.s.toncheva@edu.mon.bg						ASTVACATUROV A., 2009, Potential Magazine, V12, P79; bin Mohamed MZ, 2022, INT ELEC J MATH EDUC, V17, DOI 10.29333/iejme/12132; BUZAN T., 1996, Use Your Memory; Gruneberg M., 1973, ED RESOURCES, V15, P134, DOI DOI 10.1080/0013188730150209; IVANOVA-NEDELCHEVA A., 2016, MATTEX 2016-Shumen, P247; Karpicke JD, 2009, MEMORY, V17, P471, DOI 10.1080/09658210802647009; LYUBCHENKO V., 2022, The scientific heritage, V84, P39; McCabe JA, 2013, TEACH PSYCHOL, V40, P183, DOI 10.1177/0098628313487460; Mountstephens James, 2020, 2020 Sixth International Conference on e-Learning (econf), P271, DOI 10.1109/econf51404.2020.9385452; MURASHOV O., 2021, RMAT, V3, P80; PAUK B, 2013, How To Study In College; Pavlova NH, 2024, INT ELEC J MATH EDUC, V19, DOI 10.29333/iejme/14025; Soler MJ, 1996, APPL COGNITIVE PSYCH, V10, P41, DOI 10.1002/(SICI)1099-0720(199602)10:1<41::AID-ACP361>3.0.CO;2-1; Stalder DR, 2005, TEACH PSYCHOL, V32, P222, DOI 10.1207/s15328023top3204_3; TITLIN L., 1868, Electronic Philosophical Journal, V23; TSITSERON M, 1992, Orator; VanVoorhis CRW, 2002, TEACH PSYCHOL, V29, P249; Wardat Y., 2023, Eurasia Journal of Mathematics, Science and Technology Education, V19, P1, DOI DOI 10.29333/EJMSTE/13272; Yates FrancesAmelia., 1999, ART MEMORY	19	0	0	2	6	NATSIONALNO IZDATELSTVO AZ BUKI	SOFIA	BUL TSARIGRADSKO SHOSE, 125, BL 5, SOFIA, 1113, BULGARIA	0861-3982	1314-8540		PEDAGOGIKA	Pedagogika		2024	96	2		S			42	55		10.53656/ped2024-2s.04	http://dx.doi.org/10.53656/ped2024-2s.04			14	Education & Educational Research	Emerging Sources Citation Index (ESCI)	Education & Educational Research	SH8U6					2025-08-15	WOS:001233664000004
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			Spanish	Article						Artificial Intelligence (AI); Learning personalization; Ethics and privacy; Information and Communication Technologies (ICT); Transversal Skills; Learning		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.	[Rivera, Paula Rodriguez] Univ Vigo, Vigo, Spain; [Leon, Ana Manzano] Univ Almeria, Almeria, Spain	Universidade de Vigo; Universidad de Almeria	Rivera, PR (corresponding author), Univ Vigo, Vigo, Spain.	paula.rodriguez.rivera@uvigo.es; aml570@ual.es	Manzano León, Ana/AAX-5249-2021; Rivera, Paula/MIO-9105-2025					Akiba D, 2023, EDUC SCI, V13, DOI 10.3390/educsci13090885; Bahroun Z, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su151712983; Brown L., 2023, Adapting Curriculum for Tomorrow's Technology: Tools for Educators; Cilesiz S, 2020, REV RES EDUC, V44, P332, DOI 10.3102/0091732X20907347; Crompton H, 2023, INT J EDUC TECHNOL H, V20, DOI 10.1186/s41239-023-00392-8; Darwin, 2024, COGENT EDUC, V11, P1, DOI [10.1080/2331186X.2023.2290342, DOI 10.1080/2331186X.2023.2290342]; Dong Y., 2023, J HIGHER ED RES, V4; Fontenelle-Tereshchuk D., 2024, Discov. Educ, V3, P6, DOI [10.1007/s44217-023-00076-5, DOI 10.1007/S44217-023-00076-5]; Garcia Sanchez O., 2023, RITI REV INVESTIGACI, V11, P98, DOI [10.36825/RITI.11.23.009, DOI 10.36825/RITI.11.23.009]; Gonzalez J., 2003, TUNING ED STRUCTURES; Kamalov F, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su151612451; Labadze L, 2023, INT J EDUC TECHNOL H, V20, DOI 10.1186/s41239-023-00426-1; Lai TH, 2023, PLOS ONE, V18, DOI 10.1371/journal.pone.0283170; Libarkin Julie., 2002, J GEOSCIENCE ED, V50, P78, DOI [DOI 10.1080/10899995.2002.12028053, 10.1080/10899905.200212028053]; Martinez P., 2019, Bordon. Revista de Pedagogia, V71, P65; O'Dea XH, 2023, J UNIV TEACH LEARN P, V20; Onesi-Ozigagun O, 2024, Int. J. Appl. Res. Social Sci., V6, P589, DOI [10.51594/ijarss.v6i4.1011, DOI 10.51594/IJARSS.V6I4.1011]; Pisica AI, 2023, SOCIETIES, V13, DOI 10.3390/soc13050118; Romero M., 2024, Creative Applications of Artificial Intelligence in Education, DOI [10.1007/978-3-031-55272-4_10, DOI 10.1007/978-3-031-55272-4_10]; Saheb T, 2024, TELEMAT INFORM REP, V14, DOI 10.1016/j.teler.2024.100146; Tapalova O, 2022, ELECTRON J E-LEARN, V20, P639; Zeb A, 2024, INT J INF LEARN TECH, V41, P99, DOI 10.1108/IJILT-04-2023-0046	22	1	1	13	14	UNIV POLITECNICA VALENCIA, EDITORIAL UPV	VALENCIA	CAMINO VERA S-N, VALENCIA, 46022, SPAIN	1696-1412	1887-4592		REDU	REDU	JUL-DEC	2024	22	2					31	47		10.4995/redu.2024.22020	http://dx.doi.org/10.4995/redu.2024.22020			17	Education & Educational Research	Emerging Sources Citation Index (ESCI)	Education & Educational Research	S0X4W		gold			2025-08-15	WOS:001395561300003
J	Cail, J				Cail, Jessica			Visualization of AI Accuracy: A Novel Assignment for the Teaching of Critical Thinking and Science Writing	TEACHING OF PSYCHOLOGY			English	Article						critical thinking; technology; writing; artificial intelligence; teaching		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] Pepperdine Univ, Dept Psychol, 24255 Pacific Coast Hwy, Malibu, CA 90263 USA	Pepperdine University	Cail, J (corresponding author), Pepperdine Univ, Dept Psychol, 24255 Pacific Coast Hwy, Malibu, CA 90263 USA.	Jessica.cail@pepperdine.edu	Cail, Jessica/JVN-0770-2024					Aoun JE, 2017, ROBOT-PROOF: HIGHER EDUCATION IN THE AGE OF ARTIFICIAL INTELLIGENCE, P1; Bearman M, 2023, HIGH EDUC, V86, P369, DOI 10.1007/s10734-022-00937-2; Benvenuti M, 2023, COMPUT HUM BEHAV, V148, DOI 10.1016/j.chb.2023.107903; Bitzenbauer P, 2023, CONTEMP EDUC TECHNOL, V15, DOI 10.30935/cedtech/13176; Bogost I., 2022, ChatGPT is dumber than you think; Bowles DC, 2023, PEDAGOGY HEAL PROMOT, V9, P75, DOI 10.1177/23733799231175171; Cail J., 2024, AI LIT REV ASSIGNMEN; Carvalho L., 2022, Computers and Education: Artificial Intelligence, V3, DOI DOI 10.1016/J.CAEAI.2022.100053; Dumitru D, 2023, J INTELL-BASEL, V11, DOI 10.3390/jintelligence11100194; Fowler G, 2023, The washington post; Fyfe P, 2023, AI SOC, V38, P1395, DOI 10.1007/s00146-022-01397-z; Habibzadeh F, 2023, J KOREAN MED SCI, V38, DOI 10.3346/jkms.2023.38.e319; Imran M, 2023, CONTEMP EDUC TECHNOL, V15, DOI 10.30935/cedtech/13605; Johnson G. P., 2023, Composition Studies, V51, P169; Kasneci E, 2023, LEARN INDIVID DIFFER, V103, DOI 10.1016/j.lindif.2023.102274; Markauskaite L., 2022, Computers and Education Artificial Intelligence, V3, DOI [DOI 10.1016/J.CAEAI.2022.100056, 10.1016/j.caeai]; Morgan Stanley, 2023, GENERATIVE AI COULD; Morgan Stanley, 2023, GENERATIVE AI IS SET; Naumova EN, 2023, J PUBLIC HEALTH POL, V44, P173, DOI 10.1057/s41271-023-00400-1; Office of Educational Technology, 2023, ART INT FUT TEACH LE; Rampersad G, 2020, J BUS RES, V116, P68, DOI 10.1016/j.jbusres.2020.05.019; Terry O. K., 2023, CHRON HIGHER EDUC, V69, P1; Thornhill-Miller B, 2023, J INTELL-BASEL, V11, DOI 10.3390/jintelligence11030054; UNESCO, 2023, Guidance for Generative AI in Education and Research	24	1	1	46	96	SAGE PUBLICATIONS LTD	LONDON	1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND	0098-6283	1532-8023		TEACH PSYCHOL	Teach. Psychol.	JUL	2025	52	3			SI		285	290		10.1177/00986283241289551	http://dx.doi.org/10.1177/00986283241289551		OCT 2024	6	Education & Educational Research; Psychology, Multidisciplinary	Social Science Citation Index (SSCI)	Education & Educational Research; Psychology	3BE8O					2025-08-15	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			English	Article						Gen AI; ChatGPT; Education; Challenges; Solutions; Theory; Authors' perspective; UNESCO	ETHICAL DECISION-MAKING; STUDENTS	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.	[Monib, Wali Khan; Qazi, Atika; Azizan, Mohammad Tazli] Univ Brunei Darussalam, Ctr Lifelong Learning, Gadong, Brunei; [De Silva, Liyanage; Yassin, Hayati] Univ Brunei Darussalam, Sch Digital Sci, Gadong, Brunei; [De Silva, Liyanage; Yassin, Hayati] Univ Brunei Darussalam, Fac Integrated Technol, Gadong, Brunei	University Brunei Darussalam; University Brunei Darussalam; University Brunei Darussalam	Qazi, A (corresponding author), Univ Brunei Darussalam, Ctr Lifelong Learning, Gadong, Brunei.	atika.qazi@ubd.edu.bn	Qazi, Atika/D-9377-2016; Monib, Wali Khan/ACI-7149-2022	Monib, Wali Khan/0000-0002-9575-9305	Universiti Brunei Darussalam	Universiti Brunei Darussalam	<B>Funding</B> This work was supported by Universiti Brunei Darussalam. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.	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Sci.	DEC 3	2024	10								e2105	10.7717/peerj-cs.2105	http://dx.doi.org/10.7717/peerj-cs.2105			32	Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Theory & Methods	Science Citation Index Expanded (SCI-EXPANDED)	Computer Science	P0D3Q	39650462	gold			2025-08-15	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			English	Article						ChatGPT; Academic success; Career readiness; Cognitive skills; Personalized learning	USER ACCEPTANCE; COLLEGE; ACHIEVEMENT; RELIABILITY; FRAMEWORK; EDUCATION; SYSTEMS; IMPACT	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, Nisar Ahmed; Yahaya, Noraffandy] Univ Teknol Malaysia, Fac Educ Sci & Technol FEST, Johor Baharu, Malaysia; [Al-Rahmi, Waleed Mugahed] Dar Al Uloom Univ, Coll Business Adm, Dept Management Informat Syst, Riyadh 13314, Saudi Arabia	Universiti Teknologi Malaysia; Dar Al Uloom University	Dahri, NA; Yahaya, N (corresponding author), Univ Teknol Malaysia, Fac Educ Sci & Technol FEST, Johor Baharu, Malaysia.	dahrinisar@gmail.com; p-afandy@utm.my	Dahri, Dr Nisar Ahmed/AFK-1350-2022; Yahaya, Noraffandy/AAX-1687-2020; Al-Rahmi, Waleed/W-4086-2019	Yahaya, Noraffandy/0000-0002-7952-5461; 	Research Management Centre (RMC) at Universiti Teknologi Malaysia [Q.J130000.21A2.07E10]	Research Management Centre (RMC) at Universiti Teknologi Malaysia	We thank the Research Management Centre (RMC) at Universiti Teknologi Malaysia (UTM) for allowing us to conduct this research study (under the Postdoc fellowship project, Q.J130000.21A2.07E10).	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Inf. Technol.	MAY	2025	30	7					8877	8921		10.1007/s10639-024-13148-2	http://dx.doi.org/10.1007/s10639-024-13148-2		NOV 2024	45	Education & Educational Research	Social Science Citation Index (SSCI)	Education & Educational Research	2HW3N					2025-08-15	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			English	Article						ChatGPT; Computational thinking; GeoGebra; Mathematics education		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.	[Yunianto, Wahid; Lavicza, Zsolt] Johannes Kepler Univ Linz, Altenberger Str 69, A-4040 Linz, Austria; [Galic, Selen] Hacettepe Univ, Fac Educ, Dept Math & Sci Educ, TR-06800 Ankara, Turkiye	Johannes Kepler University Linz; Hacettepe University	Yunianto, W (corresponding author), Johannes Kepler Univ Linz, Altenberger Str 69, A-4040 Linz, Austria.	yunianto.wah@gmail.com	; 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				Adelabu FM, 2019, J TECH EDUC TRAIN, V11, P44, DOI 10.30880/jtet.2019.11.01.006; Albadarin Y, 2024, Discov Educ, V3, P60, DOI [10.1007/s44217-024-00138-2, DOI 10.1007/S44217-024-00138-2]; Ang K. C., 2020, P AS TECHN C MATH; Bocconi S., 2022, Dagiene,. and Gabriele. 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J. Educ. Math. Sci. Technol.		2024	12	6								10.46328/ijemst.4437	http://dx.doi.org/10.46328/ijemst.4437			21	Education, Scientific Disciplines	Emerging Sources Citation Index (ESCI)	Education & Educational Research	T0O1Z		gold			2025-08-15	WOS:001402099400003
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			English	Article						medical education; artificial intelligence; dermatology; venereology; ChatGPT-3.5	ARTIFICIAL-INTELLIGENCE	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.	[Rojek, Marcin; Bielowka, Michal; Mitrega, Adam; Kaczynska, Dominika; Czogalik, Lukasz] Med Univ Siles, Dept Radiol & Nucl Med, Students Sci Assoc Comp Anal & Artificial Intellig, Katowice, Poland; [Kufel, Jakub] Med Univ Silesia, Dept Radiodiagnost Intervent Radiol & Nucl Med, Katowice, Poland; [Kufel, Jakub] Med Univ Siles, Dept Radiol & Nucl Med, Katowice, Poland; [Kondol, Dominika; Palkij, Kacper] Multispecialty Dist Hosp SA Dr B Hager Pyskowicka, Tarnowskie Gory, Poland; [Mielcarska, Sylwia] Med Univ Siles, Fac Med Sci Zabrze, Dept Med & Mol Biol, Katowice, Poland; [Bartnikowska, Wiktoria] Med Univ Siles, Fac Med Sci Katowice, Katowice, Poland	Medical University of Silesia; Medical University of Silesia; Medical University of Silesia; Medical University of Silesia; Medical University of Silesia	Bielówka, M (corresponding author), Med Univ Siles, Dept Radiol & Nucl Med, Students Sci Assoc Comp Anal & Artificial Intellig, Katowice, Poland.		Kufel, Jakub/GSN-6436-2022; Bielówka, Michał/JLL-4813-2023	Kufel, Jakub/0000-0001-7633-3600; Bartnikowska, Wiktoria/0000-0002-9303-946X				[Anonymous], Centrum Egzaminow Medycznych Internet; [Anonymous], 2023, S4 wyniki jesiennego naboru na specjalizacje. Hitem m.in. radiologia, dermatologia i psychiatria; [Anonymous], Introducing GPTs Internet; [Anonymous], 2023, Centrum Egzaminow Medycznych; [Anonymous], Introducing ChatGPT Internet; Fishman EK, 2023, CAN ASSOC RADIOL J, V74, P622, DOI 10.1177/08465371231174817; Foreland M, 2010, Emerging Perspectives on Learning, Teaching, and Technology Internet; Joly-Chevrier M, 2023, J CUTAN MED SURG, V27, P409, DOI 10.1177/12034754231188437; Kufel J, 2023, POL J RADIOL, V88, pE430, DOI 10.5114/pjr.2023.131215; Lewandowski M, 2023, CLIN EXP DERMATOL, V49, P686, DOI 10.1093/ced/llad255; Niewgowski K., 2021, Med. Og. Nauk. Zdr., V27, P213; Passby L, 2023, CLIN EXP DERMATOL, V49, P722, DOI 10.1093/ced/llad197; Patel S, 2021, CLIN DERMATOL, V39, P667, DOI 10.1016/j.clindermatol.2021.03.012; Porter E, 2023, J EUR ACAD DERMATOL, V37, pE943, DOI 10.1111/jdv.19174; Young AT, 2020, J INVEST DERMATOL, V140, P1504, DOI 10.1016/j.jid.2020.02.026	15	3	3	0	2	TERMEDIA PUBLISHING HOUSE LTD	POZNAN	KLEEBERGA 2, POZNAN, 61-615, POLAND	0033-2526	2084-9893		PRZ DERMATOL	Prz. Dermatol.		2024	111	1					26	30		10.5114/dr.2024.140796	http://dx.doi.org/10.5114/dr.2024.140796			5	Dermatology	Emerging Sources Citation Index (ESCI)	Dermatology	XT4O5		gold			2025-08-15	WOS:001263918000003
J	Meishar-Tal, H				Meishar-Tal, Hagit			ChatGPT: The Challenges It Presents for Writing Assignments	TECHTRENDS			English	Article						ChatGPT; Writing; Generative AI; 21th century skills; EPSS	WIKIPEDIA	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] Holon Inst Technol, 52th Golomb st, Holon, Israel		Meishar-Tal, H (corresponding author), Holon Inst Technol, 52th Golomb st, Holon, Israel.	hagitmt@hit.ac.il	Meishar-Tal, Hagit/K-2666-2019					Agosto DE, 2005, J AM SOC INF SCI TEC, V56, P1008, DOI 10.1002/asi.20155; AlAfnan M. 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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			English	Article							ICT	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.	[Folmeg, Marta; Fekete, Imre; Koris, Rita] Budapest Business Univ, Budapest, Hungary	Budapest Business University	Folmeg, M (corresponding author), Budapest Business Univ, Budapest, Hungary.		Koris, Rita/IYT-0925-2023	Koris, Rita/0000-0003-1912-8744				Atlas S., 2023, ChatGPT for Higher Education and Professional Development: A Guide to Conversational AI; Banele S. D., 2023, SocioEdu: Sociological Education, V4, P53, DOI [10.59098/socioedu.v4i2.1203, DOI 10.59098/SOCIOEDU.V4I2.1203]; Charow R, 2021, JMIR MED EDUC, V7, DOI 10.2196/31043; Chiu TKF, 2024, INTERACT LEARN ENVIR, V32, P6187, DOI 10.1080/10494820.2023.2253861; Crawford J, 2023, J UNIV TEACH LEARN P, V20, DOI 10.53761/1.20.3.02; Creswell J. W., 2014, A concise introduction to mixed methods research; Creswell JW., 2018, Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, DOI DOI 10.3109/08941939.2012.723954; Diveki R., 2024, Developing global competence in the Hungarian EFL classroom; Eager B, 2023, J UNIV TEACH LEARN P, V20; Fekete I., 2023, Akademiai Kiado, DOI [10.1556/9789634548706, DOI 10.1556/9789634548706]; Hews R, 2022, J UNIV TEACH LEARN P, V19; Ilieva G, 2023, INFORMATION, V14, DOI 10.3390/info14090492; Kamalov F, 2023, SUSTAINABILITY-BASEL, V15, DOI 10.3390/su151612451; Kelly A, 2023, J UNIV TEACH LEARN P, V20, DOI 10.53761/1.20.6.12; Khiat H, 2022, J UNIV TEACH LEARN P, V19; Kim S, 2021, AAAI CONF ARTIF INTE, V35, P15569; Kostka I., 2023, Tesl-ej, V27, pn3, DOI [https://doi.org/10.55593/ej.27107int, DOI 10.55593/EJ.27107INT]; Krakowski A, 2022, AAAI CONF ARTIF INTE, P12774; Lacey MM, 2023, MICROBIOL AUST, V44, P124, DOI 10.1071/MA23036; Lee I, 2022, PROCEEDINGS OF THE 53RD ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION (SIGCSE 2022), VOL 1, P202, DOI 10.1145/3478431.3499318; Lim CP, 2002, BRIT J EDUC TECHNOL, V33, P411, DOI 10.1111/1467-8535.00278; Lim WM, 2023, INT J MANAG EDUC-OXF, V21, DOI 10.1016/j.ijme.2023.100790; Lodge JM, 2023, J UNIV TEACH LEARN P, V20, DOI 10.53761/1.20.7.02; Long DR, 2020, PROCEEDINGS OF THE 2020 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'20), DOI 10.1145/3313831.3376727; McDougall A., 2006, Technology, Pedagogy and Education, V15, P353, DOI 10.1080/14759390600923915; Munoz S. A. S., 2023, Social Space, V23, P1; Nadeem M, 2021, J UNIV TEACH LEARN P, V18; Ng DTK, 2023, EDUC INF TECHNOL, V28, P8445, DOI 10.1007/s10639-022-11491-w; Ng DTK., 2021, Computers and Education: Artificial Intelligence, V2, P100041, DOI [DOI 10.1016/J.CAEAI.2021.100041, 10.1016/j.caeai.2021.100041]; Saetra HS, 2023, TECHNOL SOC, V75, DOI 10.1016/j.techsoc.2023.102372; Sutherland R, 2004, J COMPUT ASSIST LEAR, V20, P413, DOI 10.1111/j.1365-2729.2004.00104.x; Williams R, 2021, AAAI CONF ARTIF INTE, V35, P15678	32	6	6	5	15	Open Access Publishing Assoc	Launceston	28a Brisbane St, Launceston, Tasmania, AUSTRALIA	1449-9789			J UNIV TEACH LEARN P	J. Univ. Teach. Learn. Pract.		2024	21	6							33					16	Education & Educational Research	Emerging Sources Citation Index (ESCI)	Education & Educational Research	D5J4K					2025-08-15	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			English	Article						fourth industrial revolution; stylised facts; digital learning; workplace; artificial intelligence; automation; ChatGPT; critical reflections	STYLIZED FACTS; ALGORITHMS; DATAFICATION; AUTOMATION; ROBOTICS; FUTURE	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] UNISA, Coll Human Sci, Dept English Studies, Pretoria, South Africa	University of South Africa	Chaka, C (corresponding author), UNISA, Coll Human Sci, Dept English Studies, Pretoria, South Africa.	chakachaka8@gmail.com	Chaka, Chaka/AAN-3211-2021					Abad LA, 2015, J ECON METHODOL, V22, P143, DOI 10.1080/1350178X.2015.1024878; Acemoglu D, 2022, ECONOMETRICA, V90, P1973, DOI 10.3982/ECTA19815; Alismail HA., 2015, Journal of Education and Practice, V6, P150; Ally M., 2020, Sustainable Development and Education in the Fourth Industrial Revolution (4IR); Almarzooq ZI, 2020, J AM COLL CARDIOL, V75, P2635, DOI 10.1016/j.jacc.2020.04.015; Alsoliman BSH, 2022, FRONT EDUC, V7, DOI 10.3389/feduc.2022.950766; [Anonymous], 2018, S AFR J SCI, V114, DOI 10.17159/sajs.2018/a0271; [Anonymous], 2018, TECH4GOOD SUMMIT ORG; [Anonymous], 2018, Preparing Tomorrows Workforce for the Fourth Industrial Revolution-For Business: A Framework for Action; [Anonymous], 2010, SMART TEACHING TRANS; Badet J., 2021, OPEN J BUSINESS MANA, V9, P2452, DOI [10.4236/ojbm.2021.95132, DOI 10.4236/OJBM.2021.95132]; Balliester T., 2018, The future of work: A literature review; Belpaeme T, 2018, SCI ROBOT, V3, DOI 10.1126/scirobotics.aat5954; Bowman E., 2023, A College Student Created an App That Can Tell Whether AI Wrote an Essay; Butt R, 2020, INTERACT TECHNOL SMA, V17, P337, DOI 10.1108/ITSE-02-2020-0022; Care E., 2017, Skills for a changing world: National perspectives and the global movement; Catana SA, 2021, INT J ENV RES PUB HE, V18, DOI 10.3390/ijerph18158180; CERI, 2008, 21 CENTURY LEARNING; Chaka C., 2020, Research Square, DOI DOI 10.21203/RS.3.RS-61482/V1; Chaka C., 2022, J ED E LEARN RES, V9, P136, DOI [10.20448/jeelr.v9i3.4102, DOI 10.20448/JEELR.V9I3.4102]; Chaka C., 2016, J HIGH ED AFRICA, V3, P19; Chaka C., 2009, HDB RES E LEARNING L, P550; Chaka C., 2010, HDB RES WEB 2 0 3 0, VI, P630; Chaka C., 2010, Handbook of Research on Practices and Outcomes in E-Learning: Issues and Trends, P38; Chaka C., 2021, Zeitschrift fur Hochschulentwicklung, V16, P17, DOI 10.3217/zfhe-16-03/02; Chaka C, 2023, RES PRACT TECH ENHAN, V18, DOI 10.58459/rptel.2023.18002; Chaka C, 2022, J E-LEARN KNOWL SOC, V18, P83, DOI 10.20368/1971-8829/1135678; Chaka C, 2022, J E-LEARN KNOWL SOC, V18, P58, DOI 10.20368/1971-8829/1135578; Chaka C, 2022, FRONT EDUC, V7, DOI 10.3389/feduc.2022.824976; Chaka C, 2020, IFLA J-INT FED LIBR, V46, P369, DOI 10.1177/0340035219896376; Chaka C, 2019, NORD J DIGIT LIT, V14, P54, DOI 10.18261/issn.1891-943x-2019-01-02-05; Chaka C, 2011, PALGRAVE DIGIT ED LE, P37; Change Recruitment, 2017, WILL 4 IND REV IMP F; ChatGPT, 2023, CHATGPT WHAT AR YOU; Couldry N, 2019, TELEV NEW MEDIA, V20, P336, DOI 10.1177/1527476418796632; Cutcliffe J., 2022, CHATGPT CHATBOTS ART; da Silva LBP, 2022, COMPUT IND ENG, V168, DOI 10.1016/j.cie.2022.108111; Dede C., 2005, ED Q, V28, P7; Dede C., 2009, Comparing frameworks for 21st century skills; Elayyan S., 2021, Journal of Educational Technology Online Learning, V4, P23, DOI [10.31681/jetol.737193, DOI 10.31681/JETOL.737193, 10.31681/ jetol.737]; Evans C, 2020, HUM BEHAV EMERG TECH, V2, P269, DOI 10.1002/hbe2.196; Filippi E, 2023, TECHNOL FORECAST SOC, V191, DOI 10.1016/j.techfore.2023.122448; Frey CB, 2017, TECHNOL FORECAST SOC, V114, P254, DOI 10.1016/j.techfore.2016.08.019; Govender C.M., 2022, INT J ENTREPRENEURSH, V26, P1; Harris M., 2022, CHATGPT GAME CHANGIN; Heilweil R., 2022, AI is finally good at stuff, and that's a problem; Helfat CE, 2007, STRATEG ORGAN, V5, P185, DOI 10.1177/1476127007077559; Hern A., 2022, AI bot ChatGPT stuns academics with essay-writing skills and usability. 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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			English	Article; Early Access						ChatGPT integration; AI in education; Technological pedagogical content knowledge (TPACK); Teacher perceptions; Educational technology policy; UAE educational system	PEDAGOGICAL CONTENT KNOWLEDGE; TPACK	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] Zayed Univ, Coll Interdisciplinary Studies, Dubai, U Arab Emirates; [Kuhail, Mohammad Amin; El Sayary, Areej] Zayed Univ, Coll Interdisciplinary Studies, Abu Dhabi, U Arab Emirates	Zayed University; Zayed University	El Sayary, A (corresponding author), Zayed Univ, Coll Interdisciplinary Studies, Abu Dhabi, U Arab Emirates.	areej.elsayary@zu.ac.ae	Hojeij, Zeina/AAM-8239-2021; ElSayary, Areej/ABH-4270-2022; Kuhail, Mohammad/AAS-6745-2020				Statements and declarations. Funding: This work was supported by Zayed University Research Incentive (RIF) Grant (Grant number 23071). Competing interests: The authors have no relevant financial or non-financial interests to disclose.	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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			English	Article						Artificial intelligence; ChatGPT; Chatbot; Education; Education policy; Qualitative content analysis		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.	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J. E-Learn.	JUN	2024	22	7					20	30		10.34190/ejel.22.7.3504	http://dx.doi.org/10.34190/ejel.22.7.3504			11	Education & Educational Research	Emerging Sources Citation Index (ESCI)	Education & Educational Research	I1B8G		gold			2025-08-15	WOS:001327687800002
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			English	Article						Generative artificial intelligence; evaluative judgement; assessment for learning; higher education	FEEDBACK	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.	[Bearman, Margaret; Tai, Joanna; Dawson, Phillip; Boud, David; Ajjawi, Rola] Deakin Univ, Ctr Res Assessment & Digital Learning CRADLE, Melbourne, Australia; [Boud, David] Univ Technol Sydney, Fac Arts & Social Sci, Sydney, Australia; [Boud, David] Middlesex Univ, Work & Learning Res Ctr, London, England	Deakin University; University of Technology Sydney; Middlesex University	Bearman, M (corresponding author), Deakin Univ, Ctr Res Assessment & Digital Learning CRADLE, Melbourne, Australia.	margaret.bearman@deakin.edu.au	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; 				Alkaissi H, 2023, CUREUS J MED SCIENCE, V15, DOI 10.7759/cureus.35179; Aoun JE, 2017, ROBOT-PROOF: HIGHER EDUCATION IN THE AGE OF ARTIFICIAL INTELLIGENCE, P1; Autor DH, 2003, Q J ECON, V118, P1279, DOI 10.1162/003355303322552801; Barnett R, 2017, EDUC SCI, V7, DOI 10.3390/educsci7010038; Bearman M., 2020, RE IMAGINING U ASSES, P49, DOI DOI 10.1007/978-3-030-41956-1_5; Bearman M., 2018, DEVELOPING EVALUATIV, P147; Bearman M, 2023, BRIT J EDUC TECHNOL, V54, P1160, DOI 10.1111/bjet.13337; Bearman M, 2023, HIGH EDUC, V86, P369, DOI 10.1007/s10734-022-00937-2; Bearman M, 2023, ASSESS EVAL HIGH EDU, V48, P291, DOI 10.1080/02602938.2022.2069674; Bender EM, 2021, PROCEEDINGS OF THE 2021 ACM CONFERENCE ON FAIRNESS, ACCOUNTABILITY, AND TRANSPARENCY, FACCT 2021, P610, DOI 10.1145/3442188.3445922; Boud D., 2000, Studies inContinuing Education, V22, P151167, DOI [10.1080/713695728, DOI 10.1080/713695728, https://doi.org/10.1080/713695728]; Chen LW, 2022, ASSESS EVAL HIGH EDU, V47, P493, DOI 10.1080/02602938.2021.1933378; Chong SW, 2021, ASIAN-PAC J SEC FOR, V6, DOI 10.1186/s40862-021-00115-4; Dawson P., 2020, Re-imagining university assessment in a digital world, P37, DOI [DOI 10.1007/978-3-030-41956-14, DOI 10.1007/978-3-030-41956-1_4]; De Mello Heredia J., 2023, EV JUDG SOC INF TECH; Escalante J, 2023, INT J EDUC TECHNOL H, V20, DOI 10.1186/s41239-023-00425-2; Freeman J., 2024, PROVIDE PUNISH STUDE; Guo Y, 2023, J CHEM EDUC, V100, P4876, DOI 10.1021/acs.jchemed.3c00505; Gyamfi G, 2022, ASSESS EVAL HIGH EDU, V47, P126, DOI 10.1080/02602938.2021.1887081; Kuhn D, 2000, COGNITIVE DEV, V15, P309, DOI 10.1016/S0885-2014(00)00030-7; Lipnevich AA, 2009, EDUC ASSESS EVAL ACC, V21, P347, DOI 10.1007/s11092-009-9082-2; Lipnevich AA, 2009, J EXP PSYCHOL-APPL, V15, P319, DOI 10.1037/a0017841; Luo JH, 2023, ASSESS EVAL HIGH EDU, V48, P513, DOI 10.1080/02602938.2022.2088690; Malecka B, 2023, TEACH HIGH EDUC, V28, P1761, DOI 10.1080/13562517.2021.1928061; Markauskaite L., 2022, Computers and Education Artificial Intelligence, V3, DOI [DOI 10.1016/J.CAEAI.2022.100056, 10.1016/j.caeai]; McIver S, 2023, ACT LEARN HIGH EDUC, V24, P207, DOI 10.1177/14697874211054755; Molloy E, 2019, MED EDUC, V53, P32, DOI 10.1111/medu.13649; Nam J., 2023, BESTCOLLEGES    1122; Nicol D, 2021, ASSESS EVAL HIGH EDU, V46, P756, DOI 10.1080/02602938.2020.1823314; Prather J, 2023, PROCEEDINGS OF THE 2023 WORKING GROUP REPORTS ON INNOVATION AND TECHNOLOGY IN COMPUTER SCIENCE EDUCATION, ITICSE-WGR 2023, DOI 10.1145/3623762.3633499; SADLER DR, 1989, INSTR SCI, V18, P119, DOI 10.1007/BF00117714; Siiman L. 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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			English	Article								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.	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OCT	2024	59	4			SI		678	689		10.1002/rrq.550	http://dx.doi.org/10.1002/rrq.550		JUN 2024	12	Education & Educational Research; Psychology, Educational	Social Science Citation Index (SSCI)	Education & Educational Research; Psychology	J8C2R					2025-08-15	WOS:001247229000001