Annotated Emotional Image Datasets of Chinese University Students in Real Classrooms for Deep Learning DOI Creative Commons
Chengliang Wang, Haoming Wang, Zihui Hu

и другие.

Data in Brief, Год журнала: 2024, Номер 57, С. 111147 - 111147

Опубликована: Ноя. 18, 2024

Язык: Английский

Deconstructing University Learners' Adoption Intention Towards AIGC Technology: A Mixed‐Methods Study Using ChatGPT as an Example DOI Open Access
Chengliang Wang, Xiaojiao Chen, Zhebing Hu

и другие.

Journal of Computer Assisted Learning, Год журнала: 2025, Номер 41(1)

Опубликована: Янв. 15, 2025

ABSTRACT Background ChatGPT, as a cutting‐edge technology in education, is set to significantly transform the educational landscape, raising concerns about technological ethics and equity. Existing studies have not fully explored learners' intentions adopt artificial intelligence generated content (AIGC) technology, highlighting need for deeper insights into factors influencing adoption. Objectives This study aims investigate higher education adoption towards AIGC with focus on understanding underlying reasons future prospects its application education. Methods The research divided two phases. First, an exploratory analysis involving practical activities interviews develops action decision framework Second, confirmatory using fuzzy‐set qualitative comparative 233 valid questionnaires identifies six configurations associated high intentions, emphasising roles of AI literacy perceived behavioural control. Results Conclusions reveals key adoption, including importance It provides actionable educators learners prepare effectively integrate ensuring equitable adaptive practices.

Язык: Английский

Процитировано

5

Acceptance of or resistance to facial recognition payment: A systematic review DOI Open Access
Teng Yu, Chengliang Wang,

晴子 渡辺

и другие.

Journal of Consumer Behaviour, Год журнала: 2024, Номер 23(6), С. 2933 - 2951

Опубликована: Авг. 1, 2024

Abstract With increasing evidence supporting the use of biometric identification methods for authentication, this study aims to enhance our understanding factors influencing acceptance and resistance facial recognition payment (FRP) systems. To provide a comprehensive review these factors, we conducted systematic literature (SLR) empirical studies. We examined 22 key research articles from an initial pool 1372 publications, identifying 37 that influence consumer or FRP. These were categorized into usage‐related aspects, attitudes evaluations, user‐related traits, privacy security concerns, other factors. Our findings reveal most frequently cited include performance expectancy, effort perceived usefulness, ease use. are crucial in contexts where FRP can increase productivity by providing prompt information effective assistance. This proposes collective model determinants resistance, integrating theoretical frameworks findings. The emphasizes context‐dependency user acceptance, highlighting importance addressing both technological psychological It incorporates usage characteristics, which mediated evaluations. proposed provides framework FRP, guiding service providers developing strategies adoption, with future needed refine assess further.

Язык: Английский

Процитировано

10

Unveiling learners’ intentions toward influencer-led education: an integration of qualitative and quantitative analysis DOI
Xiaojiao Chen, Teng Yu, Jian Dai

и другие.

Interactive Learning Environments, Год журнала: 2025, Номер unknown, С. 1 - 19

Опубликована: Янв. 31, 2025

Язык: Английский

Процитировано

1

Factors Influencing Tibetan College Students’ Willingness to Communicate in Their Second Language in China: A Mixed Methods Study DOI Open Access
Yang Jiang

International Journal of Applied Linguistics, Год журнала: 2025, Номер unknown

Опубликована: Янв. 7, 2025

ABSTRACT In the context of globalization, Tibetan students’ second language (L2) communication skills are crucial to allow effective intercultural and personal development. To better understand promote willingness university students communicate in their L2, this study adapts theory planned behavior (TPB) by introducing concept “language growth mindset (LGM)” replace original model's “Attitude (ATT)” component conjunction with L2 motivational self system (L2MSS). This mixed methods utilized structural equation modelling (SEM) for quantitative analysis NVivo open coding qualitative interview data. The participants were 409 from four universities China. Data collected using questionnaires in‐depth interviews. SEM model validated applicability TPB L2MSS explaining an (L2WTC). findings indicate that (a) a comprehensive based on can explain 52.9% variance L2WTC; (b) LGM, Ideal Self (IS), Ought‐to (OS) positively influence (c) perceived behavioral control (PBC) impacts while subjective norms (SN) do not affect LGM; (d) LGM does mediate relationship between SN OS.

Язык: Английский

Процитировано

0

Bibliometric Analysis of Natural Language Processing Technology in Education: Hot Topics, Frontier Evolution, and Future Prospects DOI Creative Commons
Hanbing Xue, Weishan Liu

SAGE Open, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 1, 2025

The application of natural language processing (NLP) technology in the field education has attracted considerable attention. This study takes 716 articles from Web Science database 1998 to 2023 as its research sample. Using bibliometrics theoretical foundation, and employing methods such literature review knowledge mapping analysis, utilizes tools like CiteSpace generate relevant visualizations, analyzing key themes, frontier developments, providing future prospects this domain. main findings are follows: First, number publications been increasing annually, forming core publishing journals Education Information Technology, teams led by figures Cucchiarini Catia Meurers Detmar, countries including United States China. Second, primarily covers five major themes: educational technical tools, analysis development content, computational linguistics education, acquisition learning, assessment methods. Third, exhibits certain developmental phases, progressing through stages emergence, exploration, development. Based on these findings, following proposed: at level, deeper personalized learning paths, emotional monitoring support, intelligent generation optimization content; practical interdisciplinary collaboration innovation, data mining global perspectives with international cooperation.

Язык: Английский

Процитировано

0

The Effect of Generative AI Ethics on Users’ Continuous Usage Intentions: A PLS-SEM and fsQCA Approach DOI
Yun Liu, Yingying Du

International Journal of Human-Computer Interaction, Год журнала: 2025, Номер unknown, С. 1 - 12

Опубликована: Фев. 24, 2025

Язык: Английский

Процитировано

0

Advancement in Microbiology Education: An Innovative Approach of Integrating Three-dimensional Holography Imaging Technology with Scanning Electron Microscopy DOI Creative Commons
Ankit Badge, Maithili Bankar, Nandkishor Bankar

и другие.

Nigerian Postgraduate Medical Journal, Год журнала: 2025, Номер 32(1), С. 79 - 80

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Assessment as learning: Evidence based on meta-analysis and quantitative ethnography research DOI
Yingchun Liu, Guangqiang Xu, Shuo Yuan

и другие.

Studies In Educational Evaluation, Год журнала: 2024, Номер 83, С. 101423 - 101423

Опубликована: Ноя. 18, 2024

Язык: Английский

Процитировано

1

Annotated Emotional Image Datasets of Chinese University Students in Real Classrooms for Deep Learning DOI Creative Commons
Chengliang Wang, Haoming Wang, Zihui Hu

и другие.

Data in Brief, Год журнала: 2024, Номер 57, С. 111147 - 111147

Опубликована: Ноя. 18, 2024

Язык: Английский

Процитировано

0