Abstract
Maha Al‐Freih
Abstract
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The impact of GenAI on learning outcomes: A systematic review and meta-analysis of experimental studies
10.1016/j.edurev.2025.100714 · 2025
10.3390/su16073034
10.3390/su16073034
The effectiveness of generative AI in education: A systematic review of empirical study
2024
Generative artificial intelligence in pedagogical practices: A systematic review of empirical studies (2022–2024)
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Systematic review of research on artificial intelligence applications in higher education—Where are the educators?
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Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education
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Artificial intelligence literacy in higher and adult education: A scoping literature review
10.1016/j.caeai.2022.100101 · 2022
Why generative AI literacy, why now and why it matters in the educational landscape? Kings, Queens and GenAI Dragons
10.55982/openpraxis.16.3.739 · 2024
What are artificial intelligence literacy and competency? A comprehensive framework to support them
10.1016/j.caeo.2024.100171 · 2024
Exploring EFL teachers’ behavioral intentions to integrate GenAI applications: Insights from PLS-SEM and fsQCA
10.1155/hbe2/5582099 · 2025
Relationship between pre-service teachers’ perceived competencies, affective dispositions, and readiness to use artificial intelligence: A study informed by the intelligent-TPACK
10.1016/j.caeo.2025.100305 · 2025
Unveiling the drivers of AI integration among language teachers: Integrating UTAUT and AI-TPACK
10.1080/07380569.2024.2441155 · 2025
What is technological pedagogical content knowledge?
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Technological pedagogical content knowledge: A framework for teacher knowledge
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TPACK updated to measure pre-service teachers’ twenty-first century skills
10.14742/ajet.3518 · 2017
TPACK in the age of ChatGPT and Generative AI
10.1080/21532974.2023.2247480 · 2023
Ethical principles for artificial intelligence in education
10.1007/s10639-022-11316-w · 2023
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10.3390/su16030978
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The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives
10.1016/j.caeai.2024.100221 · 2024
Toward an understanding of preservice English as a foreign language teachers’ acceptance of computer-assisted language learning 2.0 in the People’s Republic of China
10.1177/0735633117700144 · 2018
Theoretical models of integration of interactive learning technologies into teaching: A systematic literature review
10.26803/ijlter.20.12.14 · 2021
Understanding pre-service teachers’ needs for integrating AI-based tools in instruction through intelligent TPACK framework
10.1016/j.caeo.2025.100317 · 2025
Integrating generative artificial intelligence into student learning: A systematic review from a TPACK perspective
10.1016/j.edurev.2025.100741 · 2025
Exploring the factors affecting the adoption AI techniques in higher education: Insights from teachers’ perspectives on ChatGPT
10.1108/jrit-09-2023-0129 · 2025
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Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses
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Determining Power and Sample Size for Simple and Complex Mediation Models
10.1177/1948550617715068 · 2017
User acceptance of information technology: Toward a unified view
10.2307/30036540 · 2003
Translation, cross-cultural adaptation, and validation of measurement instruments: A practical guideline for novice researchers
10.2147/jmdh.s419714 · 2024
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The use of Cronbach’s alpha when developing and reporting research instruments in science education
10.1007/s11165-016-9602-2 · 2018
The use of Cronbach’s alpha when developing and reporting research instruments in science education
10.1007/s11165-016-9602-2 · doi-reference
Translation, cross-cultural adaptation, and validation of measurement instruments: A practical guideline for novice researchers
10.2147/jmdh.s419714 · doi-reference
User acceptance of information technology: Toward a unified view
10.2307/30036540 · doi-reference
Determining Power and Sample Size for Simple and Complex Mediation Models
10.1177/1948550617715068 · doi-reference
Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses
10.3758/brm.41.4.1149 · doi-reference
Exploring the factors affecting the adoption AI techniques in higher education: Insights from teachers’ perspectives on ChatGPT
10.1108/jrit-09-2023-0129 · doi-reference
Integrating generative artificial intelligence into student learning: A systematic review from a TPACK perspective
10.1016/j.edurev.2025.100741 · doi-reference
Understanding pre-service teachers’ needs for integrating AI-based tools in instruction through intelligent TPACK framework
10.1016/j.caeo.2025.100317 · doi-reference
Theoretical models of integration of interactive learning technologies into teaching: A systematic literature review
10.26803/ijlter.20.12.14 · doi-reference
Toward an understanding of preservice English as a foreign language teachers’ acceptance of computer-assisted language learning 2.0 in the People’s Republic of China
10.1177/0735633117700144 · doi-reference
The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives
10.1016/j.caeai.2024.100221 · doi-reference
10.20944/preprints202409.0826.v1
10.20944/preprints202409.0826.v1 · doi-reference
10.3390/su16030978
10.3390/su16030978 · doi-reference
Ethical principles for artificial intelligence in education
10.1007/s10639-022-11316-w · doi-reference
TPACK in the age of ChatGPT and Generative AI
10.1080/21532974.2023.2247480 · doi-reference
TPACK updated to measure pre-service teachers’ twenty-first century skills
10.14742/ajet.3518 · doi-reference
10.4018/978-1-5225-7001-1
10.4018/978-1-5225-7001-1 · doi-reference
Technological pedagogical content knowledge: A framework for teacher knowledge
10.1111/j.1467-9620.2006.00684.x · doi-reference
Unveiling the drivers of AI integration among language teachers: Integrating UTAUT and AI-TPACK
10.1080/07380569.2024.2441155 · doi-reference
Relationship between pre-service teachers’ perceived competencies, affective dispositions, and readiness to use artificial intelligence: A study informed by the intelligent-TPACK
10.1016/j.caeo.2025.100305 · doi-reference
Exploring EFL teachers’ behavioral intentions to integrate GenAI applications: Insights from PLS-SEM and fsQCA
10.1155/hbe2/5582099 · doi-reference
What are artificial intelligence literacy and competency? A comprehensive framework to support them
10.1016/j.caeo.2024.100171 · doi-reference
Why generative AI literacy, why now and why it matters in the educational landscape? Kings, Queens and GenAI Dragons
10.55982/openpraxis.16.3.739 · doi-reference
Artificial intelligence literacy in higher and adult education: A scoping literature review
10.1016/j.caeai.2022.100101 · doi-reference
10.1080/10494820.2026.2615818
10.1080/10494820.2026.2615818 · doi-reference
Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education
10.1016/j.chb.2022.107468 · doi-reference
10.3390/educsci14111209
10.3390/educsci14111209 · doi-reference
Systematic review of research on artificial intelligence applications in higher education—Where are the educators?
10.1186/s41239-019-0171-0 · doi-reference
Generative artificial intelligence in pedagogical practices: A systematic review of empirical studies (2022–2024)
10.1080/2331186x.2025.2485499 · doi-reference
10.3390/su16073034
10.3390/su16073034 · doi-reference
The impact of GenAI on learning outcomes: A systematic review and meta-analysis of experimental studies
10.1016/j.edurev.2025.100714 · doi-reference