The DOI matches its Crossref record; 40 of the 43 references it cites were found in a registry or an index.
Supporting Teachers’ Professional Development With Generative AI: The Effects on Higher Order Thinking and Self-Efficacy
Abstract
Generative AI has emerged as a noteworthy milestone and a consequential advancement in the annals of major disciplines within the domains of human science and technology. This study aims to explore the effects of generative AI-assisted pre-service teaching skills training on pre-service teachers’ self-efficacy and higher order thinking. The participants of this study were 215 pre-service mathematics, science, and computer teachers from a university in China. Firstly, a pretest-posttest quasi-experimental design was implemented for an experimental group (teaching skills training by generative AI) and a control group (teaching skills training by traditional methods) by investigating the teacher self-efficacy and higher order thinking of the two groups before and after the experiment. Secondly, a semi-structured interview comprising open-ended questions was administered to 25 pre-service teachers within the experimental group to present their views on generative AI-assisted teaching. The results showed that the scores of pre-service teachers in the experimental group, who used generative AI for teachers’ professional development, were considerably higher than those of the control group, both in teacher self-efficacy (F = 8.589, p = 0.0084< 0.05) and higher order thinking (F = 7.217, p = 0.008 < 0.05). It revealed that generative AI can be effective in supporting teachers’ professional development. This study produced a practical teachers’ professional development method for pre-service teachers with generative AI.
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In the citing paper
“These interventions embedded GenAI within learning platforms to generate real-time hints, guiding questions, automated scoring, or corrective feedback in response to student inputs [32,47,49,59].”
From A Systematic Literature Review on the Pedagogical Implications and Impact of GenAI on Students' Critical Thinking (2026) · cites this paper as [47]
In the citing paper
“These interventions were frequently embedded in performance-based assessments supported by CT-aligned rubrics (e.g., Bloom's Revised Taxonomy, Paul & Elder's Elements of Thought) [15,47,95].”
From A Systematic Literature Review on the Pedagogical Implications and Impact of GenAI on Students' Critical Thinking (2026) · cites this paper as [47]
In the citing paper
“These cognitive affordances are amplified when paired with pedagogical intentionality [47].”
From A Systematic Literature Review on the Pedagogical Implications and Impact of GenAI on Students' Critical Thinking (2026) · cites this paper as [47]
Citations
Cites
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2019) · arXiv · doi:10.48550/arxiv.1910.10683 · Cited by 10,929
Self-efficacy: Toward a unifying theory of behavioral change
Bandura, A. (1978) · Advances in Behaviour Research and Therapy · doi:10.1016/0146-6402(78)90002-4 · Cited by 10,586
The differential antecedents of self-efficacy beliefs of novice and experienced teachers
Tschannen-Moran, M., & Hoy, A. W. (2007) · Teaching and Teacher Education · doi:10.1016/j.tate.2006.05.003 · Cited by 1,976 · cited 1×
“In addition, teachers’ self-efficacy also plays an important role in learning and teaching [11], [12].”
BackgroundA Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development
Wu, T., He, S., Liu, J., Sun, S., Liu, K., Han, Q.-L., & Tang, Y. (2023) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2023.123618 · Cited by 1,452
A SWOT analysis of ChatGPT: Implications for educational practice and research
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2195846 · Cited by 1,384
ChatGPT for Education and Research: Opportunities, Threats, and Strategies
Rahman, M. M., & Watanobe, Y. (2023) · Applied Sciences · doi:10.3390/app13095783 · Cited by 1,080 · cited 1×
“ThereisnodoubtthatAIGChasalso evokedpolarizedreactionsineducation,havingasignificant andfar-reachingimpactonschooleducationinashortperiod [7].”
Is ChatGPT a General-Purpose Natural Language Processing Task Solver?
Qin, C., Zhang, A., Zhang, Z., Chen, J., Yasunaga, M., & Yang, D. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.85 · Cited by 869
Purposely Teaching for the Promotion of Higher-order Thinking Skills: A Case of Critical Thinking
Barak, M., Ben‐Chaim, D., & Uri, Z. (2007) · Research in Science Education · doi:10.1007/s11165-006-9029-2 · Cited by 757
Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education
Qadir, J. (2023) · 2023 IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon54358.2023.10125121 · Cited by 707 · cited 1×
“Since November 2022, with the emergence of ChatGPT and GPT-4, the generative artificial intelligence represented by Chat-GPT has become a significant landmark and effective advance in the history of major human science and technology [6].”
BackgroundJeon, J., & Lee, S. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11834-1 · Cited by 696
Research works printed but not linked: 2
- 10.18260/1-2--34923 · DOI
- Archambault, The preparation and perspective of online K-12 teachers in Nevada, 1836
Cited by
Sorted by citations
Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies
Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025) · Computers & Education · doi:10.1016/j.compedu.2024.105224 · Cited by 531
Artificial intelligence in teaching and teacher professional development: A systematic review
Tan, X., Cheng, G., & Ling, M. H. (2025) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100355 · Cited by 420
Wang, J., & Fan, W. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04787-y · Cited by 322
RetractedKong, S.-C., & Yang, Y. (2024) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2024.3392830 · Cited by 298
Wu, D., Zhang, S., Ma, Z., Yue, G. X.-G., & Dong, R. K. (2024) · Systems · doi:10.3390/systems12090332 · Cited by 127
Metadata
- Authors
- Lu, J., Zheng, R., Gong, Z., & Xu, H.
- Affiliations
- Hangzhou Normal University (CN)
- Venue
- IEEE Transactions on Learning Technologies
- Published
- 2024
- Volume
- 17
- Pages
- 1267-1277
- ISSN
- 1939-1382 (ISSN-L)
- 2372-0050
- OpenAlex
- W4392173880
- Cited by
- 144
- References
- 43
- Citations by year
- 2026: 65 · 2025: 65 · 2024: 14
- FWCI
- 54.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Learning Technologies (publishedVersion)
- Funders
- Ministry of Education's Artificial Intelligence to Promote the Construction of Teachers' Team
- Major Humanities and Social Sciences Research Projects in Zhejiang Higher Education Institutions (2023GH005)
- Teaching Academic and Reform Project of Hangzhou Normal University
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Education › Teacher Education and Leadership Studies
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- generative AI, teacher professional development, pre-service teachers, teacher self-efficacy, higher-order thinking skills, teaching skills training, mathematics teachers, science teachers, informatics teachers, initial teacher education
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