Fostering pre-service teachers' generative AI literacy and critical thinking: An RSCQA approach
With the wide application of Generative Artificial Intelligence (GenAI) technology in society, GenAI literacy and critical thinking are considered vital competencies for success in the future. As future teachers, pre-service teachers (PSTs) must possess these key competencies. Previous research has...
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| Vydané v: | Educational Technology ＆ Society Ročník 28; číslo 3; s. 202 - 225 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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International Forum of Educational Technology ＆ Society
01.07.2025
International Forum of Educational Technology & Society, National Taiwan Normal University, Taiwan International Forum of Educational Technology & Society |
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| ISSN: | 1176-3647, 1436-4522, 1436-4522 |
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| Abstract | With the wide application of Generative Artificial Intelligence (GenAI) technology in society, GenAI literacy and critical thinking are considered vital competencies for success in the future. As future teachers, pre-service teachers (PSTs) must possess these key competencies. Previous research has pointed out that although learning and applying GenAI knowledge and technology can improve PSTs' GenAI literacy, the results were not as expected. This study incorporated a KWL (Know, Want, Learned)-based reflection strategy based on the SCQA (Situation, Complication, Question, and Answer) model, and proposed an RSCQA (Reflection, Situation, Complication, Question, and Answer) approach, which aims to help PSTs develop GenAI literacy and critical thinking. A quasi-experiment was designed for this study to verify the validity of the RSCQA approach, which was used by the experimental group, while the Conventional SCQA (CSCQA) approach was used by the control group. Results of the study demonstrated that using the RSCQA approach improved PSTs' GenAI literacy and critical thinking, and they excelled in multimodal demonstration capability. This study also conducted an ENA analysis of the content of PSTs' reflections, and the results demonstrated that reflective strategies help PSTs engage in higher-order cognitive activities. The results of the qualitative interviews further indicated that the reflective strategy enhanced PSTs' learning effectiveness and strengthened their critical thinking. Overall, the RSCQA approach helps PSTs engage in reflective learning and perform better in GenAI literacy and critical thinking. The results of this study provide practical experience and operational examples of PST cultivation. |
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| AbstractList | With the wide application of Generative Artificial Intelligence (GenAI) technology in society, GenAI literacy and critical thinking are considered vital competencies for success in the future. As future teachers, pre-service teachers (PSTs) must possess these key competencies. Previous research has pointed out that although learning and applying GenAI knowledge and technology can improve PSTs’ GenAI literacy, the results were not as expected. This study incorporated a KWL (Know, Want, Learned)-based reflection strategy based on the SCQA (Situation, Complication, Question, and Answer) model, and proposed an RSCQA (Reflection, Situation, Complication, Question, and Answer) approach, which aims to help PSTs develop GenAI literacy and critical thinking. A quasi-experiment was designed for this study to verify the validity of the RSCQA approach, which was used by the experimental group, while the Conventional SCQA (CSCQA) approach was used by the control group. Results of the study demonstrated that using the RSCQA approach improved PSTs’ GenAI literacy and critical thinking, and they excelled in multimodal demonstration capability. This study also conducted an ENA analysis of the content of PSTs’ reflections, and the results demonstrated that reflective strategies help PSTs engage in higher-order cognitive activities. The results of the qualitative interviews further indicated that the reflective strategy enhanced PSTs’ learning effectiveness and strengthened their critical thinking. Overall, the RSCQA approach helps PSTs engage in reflective learning and perform better in GenAI literacy and critical thinking. The results of this study provide practical experience and operational examples of PST cultivation. With the wide application of Generative Artificial Intelligence (GenAI) technology in society, GenAI literacy and critical thinking are considered vital competencies for success in the future. As future teachers, pre-service teachers (PSTs) must possess these key competencies. Previous research has pointed out that although learning and applying GenAI knowledge and technology can improve PSTs' GenAI literacy, the results were not as expected. This study incorporated a KWL (Know, Want, Learned)-based reflection strategy based on the SCQA (Situation, Complication, Question, and Answer) model, and proposed an RSCQA (Reflection, Situation, Complication, Question, and Answer) approach, which aims to help PSTs develop GenAI literacy and critical thinking. A quasi-experiment was designed for this study to verify the validity of the RSCQA approach, which was used by the experimental group, while the Conventional SCQA (CSCQA) approach was used by the control group. Results of the study demonstrated that using the RSCQA approach improved PSTs' GenAI literacy and critical thinking, and they excelled in multimodal demonstration capability. This study also conducted an ENA analysis of the content of PSTs' reflections, and the results demonstrated that reflective strategies help PSTs engage in higher-order cognitive activities. The results of the qualitative interviews further indicated that the reflective strategy enhanced PSTs' learning effectiveness and strengthened their critical thinking. Overall, the RSCQA approach helps PSTs engage in reflective learning and perform better in GenAI literacy and critical thinking. The results of this study provide practical experience and operational examples of PST cultivation. Keywords: Artificial Intelligence in Education, Critical thinking, Teacher training, Information literacy, Generative artificial intelligence |
| Audience | Academic |
| Author | Xiao-Ge Guo Jing Chen Le-Fu Huang Jian-Wen Fang Xiao-Pei Meng |
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| Title | Fostering pre-service teachers' generative AI literacy and critical thinking: An RSCQA approach |
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