Gender Differences in the Use of Generative Artificial Intelligence Chatbots in Higher Education: Characteristics and Consequences DOI Creative Commons
Anja Møgelvang, Camilla Bjelland, Simone Grassini

et al.

Education Sciences, Journal Year: 2024, Volume and Issue: 14(12), P. 1363 - 1363

Published: Dec. 12, 2024

Student gender differences in technology acceptance and use have persisted for years, giving rise to equity concerns higher education (HE). To explore if such extend generative artificial intelligence (genAI) chatbot use, we surveyed a large Norwegian HE student sample (n = 2692) using fully mixed concurrent equal status design. Our findings show that men exhibit more frequent engagement with genAI chatbots across broader spectrum of applications. Further, demonstrate heightened interest as tools their relevance future career prospects. Women primarily utilize text-related tasks express greater regarding critical independent thinking. also stronger need learn how determine when it is wise trust chatbots. Consequences are discussed the individual, society, institutions terms social reproduction, diversity competence, equitable teaching practices.

Language: Английский

Integrating generative artificial intelligence in K-12 education: Examining teachers’ preparedness, practices, and barriers DOI Creative Commons
Yin Hong Cheah, Jingru Lu, Juhee Kim

et al.

Computers and Education Artificial Intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 100363 - 100363

Published: Jan. 1, 2025

Language: Английский

Citations

1

“I Just Think It Is The Way of the Future”: Teachers Use of ChatGPT to Develop Motivationally-Supportive Math Lessons DOI Creative Commons
Teomara Rutherford, Andrew Rodrigues,

Santiago Duque-Baird

et al.

Computers and Education Artificial Intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 100367 - 100367

Published: Jan. 1, 2025

Language: Английский

Citations

1

Teachers’ perceived social-emotional competence: a personal resource linked with well-being and turnover intentions DOI Creative Commons
Rebecca J. Collie

Educational Psychology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 18

Published: Feb. 22, 2025

Language: Английский

Citations

1

Artificial Intelligence Integration: Pedagogical Strategies and Policies at Leading Universities DOI
Naifa Alqahtani, Zarina Wafula

Innovative Higher Education, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 22, 2024

Language: Английский

Citations

5

Large language models and GenAI in education: Insights from Nigerian in-service teachers through a hybrid ANN-PLS-SEM approach DOI Creative Commons
Musa Adekunle Ayanwale, Owolabi Paul Adelana, Nurudeen Babatunde Bamiro

et al.

F1000Research, Journal Year: 2025, Volume and Issue: 14, P. 258 - 258

Published: March 4, 2025

Background The rapid integration of Artificial Intelligence (AI) in education offers transformative opportunities to enhance teaching and learning. Among these innovations, Large Language Models (LLMs) like ChatGPT hold immense potential for instructional design, personalized learning, administrative efficiency. However, integrating tools into resource-constrained settings such as Nigeria presents significant challenges, including inadequate infrastructure, digital inequities, teacher readiness. Despite the growing research on AI adoption, limited studies focus developing regions, leaving a critical gap understanding how educators perceive adopt technologies. Methods We adopted hybrid approach, combining Partial Least Squares Structural Equation Modelling (PLS-SEM) Neural Networks (ANN) uncover both linear nonlinear dynamics influencing behavioral intention (BI) 260 Nigerian in-service teachers regarding after participating structured training. Key predictors examined include Perceived Ease Use (PEU), Usefulness (PUC), Attitude Towards (ATC), Your Colleagues (YCC), Technology Anxiety (TA), Teachers’ Trust (TTC), Privacy Issues (PIU). Results Our PLS-SEM results highlight PUC, TA, YCC, PEU, that order importance, predictors, explaining 15.8% variance BI. Complementing these, ANN analysis identified ATC, PUC most factors, demonstrating substantial predictive accuracy with an RMSE 0.87. This suggests while drives PEU positive attitudes are foundational fostering engagement Conclusion need targeted professional development initiatives teachers’ competencies, reduce technology-related anxiety, build trust ChatGPT. study actionable insights policymakers educational stakeholders, emphasizing importance inclusive ethical ecosystem. aim empower support AI-driven transformation resource-limited environments by addressing contextual barriers.

Language: Английский

Citations

0

Integrating learner characteristics and generative AI affordances to enhance self-regulated learning: a configurational analysis DOI Creative Commons
Xiu-Yi Wu, Thomas K. F. Chiu

Journal of New Approaches in Educational Research, Journal Year: 2025, Volume and Issue: 14(1)

Published: March 17, 2025

Abstract This study investigates the configurational impact of generative artificial intelligence (GenAI) tools on self-regulated learning (SRL) across various educational levels using a 28-week fuzzy-set qualitative comparative analysis (fsQCA) approach. The research explores how factors such as technological proficiency, user engagement, skills, and feedback quality interact with functionalities GenAI to enhance SRL capacities. Data were collected through semi-structured surveys assessments from diverse sample undergraduate postgraduate students. findings reveal that synergistic relationship between learner characteristics tool affordances significantly boosts skills. Key configurations identified include critical role high-quality functionalities, importance positive attitudes moderating effect interface experience. underscores necessity tailoring meet individual needs highlights potential these technologies create adaptive, personalized environments. results advocate for strategic integration in practices support pathways, contributing global discourse digital pedagogy enhancement learning.

Language: Английский

Citations

0

Teachers’ early uptake of genAI in teaching and learning: important questions and answers DOI
Rebecca J. Collie, Andrew J. Martin

Social Psychology of Education, Journal Year: 2025, Volume and Issue: 28(1)

Published: March 28, 2025

Language: Английский

Citations

0

Teachers’ Generative AI Self-Efficacy, Valuing, and Integration at Work: Examining Job Resources and Demands DOI Creative Commons
Rebecca J. Collie, Andrew J. Martin, Dragan Gašević

et al.

Computers and Education Artificial Intelligence, Journal Year: 2024, Volume and Issue: unknown, P. 100333 - 100333

Published: Nov. 1, 2024

Language: Английский

Citations

4

Pre-service Teachers Preparedness for AI-integrated Education: An Investigation from Perceptions, Capabilities, and Teachers’ Identity Changes DOI Creative Commons
Lihang Guan, Yue Zhang, Mingyue Gu

et al.

Computers and Education Artificial Intelligence, Journal Year: 2024, Volume and Issue: unknown, P. 100341 - 100341

Published: Dec. 1, 2024

Language: Английский

Citations

3

<p><span>Transforming Teachers’ Roles and Agencies in the Era of Generative AI: Perceptions, Acceptance, Knowledge, and Practices</span></p> DOI
Xiaoming Zhaı

Published: Jan. 1, 2024

Language: Английский

Citations

0