Research graph
References from Understanding art and design teachers’ willingness to adopt artificial intelligence in teaching under resource constraints: a mixed-methods study on perceived usefulness, resource readiness, and creativity-related concerns. Local targets link to admitted publications; unresolved targets remain external evidence.
Bootstrapping goodness-of-fit measures in structural equation models
10.1177/0049124192021002004 · 1992 · External reference
Using thematic analysis in psychology
10.1191/1478088706qp063oa · 2006 · External reference
Perceived usefulness, perceived ease of use, and user acceptance of information technology
10.2307/249008 · 1989 · External reference
User acceptance of computer technology: a comparison of two theoretical models
10.1287/mnsc.35.8.982 · 1989 · External reference
Generative AI enhances individual creativity but reduces the collective diversity of novel content
10.1126/sciadv.adn5290 · 2024 · External reference
Addressing first- and second-order barriers to change: strategies for technology integration
10.1007/bf02299597 · 1999 · External reference
Achieving integration in mixed methods designs—principles and practices
10.1111/1475-6773.12117 · 2013 · External reference
Content validity in psychological assessment: a functional approach to concepts and methods
10.1037/1040-3590.7.3.238 · 1995 · External reference
The factors affecting teachers’ adoption of AI technologies: a unified model of external and internal determinants
10.1007/s10639-025-13393-z · 2025 · External reference
A new criterion for assessing discriminant validity in variance-based structural equation modeling
10.1007/s11747-014-0403-8 · 2015 · External reference
Integrating technology into K–12 teaching and learning: current knowledge gaps and recommendations for future research
10.1007/s11423-006-9022-5 · 2007 · External reference
Generation gap: learning from the experience of compulsory remote architectural design studio
10.1186/s41239-022-00345-7 · 2022 · External reference
Artificial intelligence as a tool for creativity
10.1016/j.yjoc.2024.100079 · 2024 · External reference
Beyond detection: redesigning authentic assessment in an AI-mediated world
10.3390/educsci15111537 · 2025 · External reference
Teachers' perceptions of using an artificial intelligence-based educational tool for scientific writing
10.3389/feduc.2022.755914 · 2022 · External reference
Examining teachers’ behavioral intention to use generative artificial intelligence tools for teaching and learning based on the extended technology acceptance model
10.1016/j.caeai.2024.100328 · 2024 · External reference
Journal article reporting standards for qualitative primary, qualitative meta-analytic, and mixed methods research in psychology: the APA publications and communications board task force report
10.1037/amp0000151 · 2018 · External reference
Co-creating art with generative artificial intelligence: implications for artworks and artists
10.1016/j.chbah.2024.100056 · 2024 · External reference
Changing design education for the 21st century
10.1016/j.sheji.2019.12.002 · 2020 · External reference
How to use a Monte Carlo study to decide on sample size and determine power
10.1207/s15328007sem0904_8 · 2002 · External reference
Faculty acceptance and use of generative artificial intelligence in their practice
10.3389/feduc.2025.1427450 · 2025 · External reference
Teaching creativity in art and design studio classes: a systematic literature review
10.1016/j.edurev.2017.07.002 · 2017 · External reference
The technology acceptance model (TAM): a meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education
10.1016/j.compedu.2018.09.009 · 2019 · External reference
Exploring the attitude and use of GenAI-image among art and design college students based on TAM and SDT
10.1080/10494820.2024.2365959 · 2025 · External reference
Factors influencing educators' AI adoption: a grounded meta-analysis review
10.1016/j.caeai.2025.100464 · 2025 · External reference
Factors influencing teachers’ intention to use technology: the model development and test
10.1016/j.compedu.2011.06.008 · 2011 · External reference
Technology acceptance model 3 and a research agenda on interventions
10.1111/j.1540-5915.2008.00192.x · 2008 · External reference
A theoretical extension of the technology acceptance model: four longitudinal field studies
10.1287/mnsc.46.2.186.11926 · 2000 · External reference
User acceptance of information technology: toward a unified view
10.2307/30036540 · 2003 · External reference
Preparing for AI-enhanced education: conceptualizing and empirically examining teachers’ AI readiness
10.1016/j.chb.2023.107798 · 2023 · External reference
Sample size requirements for structural equation models: an evaluation of power, bias, and solution propriety
10.1177/0013164413495237 · 2013 · External reference
Systematic review of research on artificial intelligence applications in higher education—where are the educators?
10.1186/s41239-019-0171-0 · 2019 · External reference
Understanding teachers' adoption of AI technologies: an empirical study from Chinese middle schools
10.3390/systems13040302 · 2025 · External reference
Art and design teachers’ acceptance of AI-generated content for assisted tutoring: an extended TAM-TPACK framework
10.1057/s41599-026-06692-4 · 2026 · External reference
