AI Trends in Teacher and Student Training

Topic Information

Dear Colleagues,

Artificial intelligence is transforming education at all levels, from early childhood education to university. This Topic seeks to explore the latest trends and developments in the application of AI in education for teachers and students, showcasing case studies, innovative practices and emerging technologies. A variety of topics related to AI in teacher and student education will be addressed, including, but not limited to, AI-powered teaching tools, student data analysis, research advances, and the ethical implications of AI integration. In this regard, it is important to uncover both positive and negative consequences on society. By examining how AI is reshaping academic environments, this theme seeks to contribute to a deeper understanding of how educational institutions can leverage AI to improve educational outcomes and operational efficiency.

Potential topics include, but are not limited to, the following:

• AI-powered personalized learning platforms;
• Use of AI in the analysis and prediction of student performance;
• AI-driven research innovations in various academic areas;
• Ethical concerns and challenges in implementing AI in education;
• AI administrative tools to improve the management and efficiency of educational institutions;
• The role of AI in fostering accessibility and inclusion in education;
• The impact of AI on the future of teaching and learning methodologies across different educational levels;
• Case studies on the successful integration of AI in educational environments.

Dr. José Fernández-Cerero
Dr. Marta Montenegro-Rueda
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
AI ai	5.0	6.9	2020	20.7 Days	CHF 1600	Submit
Computers computers	4.2	7.5	2012	16.3 Days	CHF 1800	Submit
Education Sciences education	2.6	5.5	2011	29.2 Days	CHF 1800	Submit
Societies societies	1.6	3.0	2011	34.4 Days	CHF 1400	Submit
Future Internet futureinternet	3.6	8.3	2009	17 Days	CHF 1600	Submit
Technologies technologies	3.6	8.5	2013	21.8 Days	CHF 1600	Submit

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Published Papers (5 papers)

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All AI Computers Education Sciences Societies Future Internet Technologies

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20 pages, 369 KB  

Open AccessArticle

Exploring University Students’ Acceptance and Satisfaction of the Flipped Learning Approach in Instructional Technology Related Class

by Asma’a Abu Qbeita and Al-Mothana Gasaymeh

Educ. Sci. 2025, 15(9), 1181; https://doi.org/10.3390/educsci15091181 - 8 Sep 2025

Abstract

There is increasing interest in integrating various forms of Information and Communication technologies (ICT) into education. Well-established theoretical guidelines should guide the integration of these technologies. A flipped classroom is an example of an educational approach that integrates ICT and is guided by [...] Read more.

There is increasing interest in integrating various forms of Information and Communication technologies (ICT) into education. Well-established theoretical guidelines should guide the integration of these technologies. A flipped classroom is an example of an educational approach that integrates ICT and is guided by an active learning philosophy. The current study aims to evaluate participants’ acceptance of the flipped learning instructional model using six indicators—perceived usefulness, ease of use, hedonic motivation, attitude, self-efficacy, and educational quality—and to assess overall satisfaction. Additionally, it examines how these factors relate to overall satisfaction with this approach. The study utilized a descriptive cross-sectional research design with an exploratory and correlational orientation. The target population for this study included undergraduate students enrolled in the “Computer Applications in Education” course offered by the College of Education over three consecutive semesters: the second semester of the 2023/2024 academic year and the first and second semesters of 2024/2025. All students in this course experienced the flipped learning model as part of their instructional activities. Out of the 180 students, 137 completed the data collection tool, which was a questionnaire. The results showed that participants’ acceptance of the flipped learning approach was generally positive, ranging from moderate to high across all measured dimensions. The majority reported high levels of hedonic motivation, positive attitudes, perceived educational quality, and ease of use of the flipped learning requirements. Students found the flipped learning experience enjoyable, effective, and manageable. They believed it enhanced their learning and reported moderate self-efficacy and perceived usefulness. While satisfaction with flipped learning was moderate overall, it was strongly associated with enjoyment, positive attitudes, self-efficacy, and perceived educational quality, as evident in the results of the correlation analysis. Regression analysis revealed that these four factors were significantly associated with students’ satisfaction, whereas perceived usefulness and ease of use were not significantly associated when considered alongside other variables. These results suggest that emotional engagement, confidence, and perceived educational value are key contributors to students’ satisfaction with flipped learning. Full article

(This article belongs to the Topic AI Trends in Teacher and Student Training)

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20 pages, 510 KB  

Open AccessArticle

Students’ Perceptions of Generative AI Image Tools in Design Education: Insights from Architectural Education

by Michelle Boyoung Huh, Marjan Miri and Torrey Tracy

Educ. Sci. 2025, 15(9), 1160; https://doi.org/10.3390/educsci15091160 - 5 Sep 2025

Viewed by 269

Abstract

The rapid emergence of generative artificial intelligence (GenAI) has sparked growing interest across educational disciplines, reshaping how knowledge is produced, represented, and assessed. While recent research has increasingly explored the implications of text-based tools such as ChatGPT in education, far less attention has [...] Read more.

The rapid emergence of generative artificial intelligence (GenAI) has sparked growing interest across educational disciplines, reshaping how knowledge is produced, represented, and assessed. While recent research has increasingly explored the implications of text-based tools such as ChatGPT in education, far less attention has been paid to image-based GenAI tools—despite their particular relevance to fields grounded in visual communication and creative exploration, such as architecture and design. These disciplines raise distinct pedagogical and ethical questions, given their reliance on iteration, authorship, and visual representation as core elements of learning and practice. This exploratory study investigates how architecture and interior architecture students perceive the use of AI-generated images, focusing on ethical responsibility, educational relevance, and career implications. To ensure participants had sufficient exposure to visual GenAI tools, we conducted a series of workshops before surveying 42 students familiar with image generation processes. Findings indicate strong enthusiasm for GenAI image tools, which students viewed as supportive during early-stage design processes and beneficial to their creativity and potential future professional competitiveness. Participants regarded AI use as ethically acceptable when accompanied by transparent acknowledgment. However, acceptance declined in later design stages, where originality and critical judgment were perceived as more central. While limited in scope, this exploratory study foregrounds student voices to offer preliminary insights into evolving conversations about AI in creative education and to inform future reflection on developing ethically and pedagogically responsive curricula across the design disciplines. Full article

(This article belongs to the Topic AI Trends in Teacher and Student Training)

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19 pages, 433 KB  

Open AccessArticle

A TAM-Based Analysis of Hong Kong Undergraduate Students’ Attitudes Toward Generative AI in Higher Education and Employment

by Kam Cheong Li, Grace Ho Lan Chong, Billy Tak Ming Wong and Manfred Man Fat Wu

Educ. Sci. 2025, 15(7), 798; https://doi.org/10.3390/educsci15070798 - 20 Jun 2025

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Abstract

This study explores undergraduate students’ attitudes towards generative AI tools in higher education and their perspectives on the future of jobs. It aims to understand the decision-making processes behind adopting these emerging technologies. A multidimensional model based on the technology acceptance model was [...] Read more.

This study explores undergraduate students’ attitudes towards generative AI tools in higher education and their perspectives on the future of jobs. It aims to understand the decision-making processes behind adopting these emerging technologies. A multidimensional model based on the technology acceptance model was developed to assess various factors, including perceived ease of use, perceived benefits, perceived concerns, knowledge of AI, and students’ perceptions of generative AI’s impact on the future of jobs. Data were collected through a survey distributed to 93 undergraduate students at a university in Hong Kong. The findings of multiple regression analyses revealed that these factors collectively explained 23% of the variance in frequency of use [(F(4, 78) = 5.89, p < 0.001), R² = 0.23]. Perceived benefits played the most significant role in determining frequency of use of generative AI tools. While students expressed mixed attitudes toward the role of AI in the future of jobs, those who voiced concerns about AI in education were more likely to view generative AI as a potential threat to job availability. The results provide insights for educators and policymakers to promote the effective use of generative AI tools in academic settings to help mitigate risks associated with overreliance, biases, and the underdevelopment of essential soft skills, including critical thinking, creativity, and communication. By addressing these challenges, higher education institutions can better prepare students for a rapidly evolving, AI-driven workforce. Full article

(This article belongs to the Topic AI Trends in Teacher and Student Training)

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14 pages, 204 KB  

Open AccessArticle

Perceptions of AI in Higher Education: Insights from Students at a Top-Tier Chinese University

by Yi Yan, Bin Wu, Jiaqi Pi and Xiaowen Zhang

Educ. Sci. 2025, 15(6), 735; https://doi.org/10.3390/educsci15060735 - 12 Jun 2025

Viewed by 3111

Abstract

While AI integration in higher education has transformative potential, existing studies may not fully capture the unique socio-cultural and institutional contexts of top-tier universities in China. This study investigates students’ perceptions of AI utilization at a leading Chinese university, drawing on the Technology [...] Read more.

While AI integration in higher education has transformative potential, existing studies may not fully capture the unique socio-cultural and institutional contexts of top-tier universities in China. This study investigates students’ perceptions of AI utilization at a leading Chinese university, drawing on the Technology Acceptance Model (TAM). Quantitative data were collected via a 5-point Likert scale questionnaire (n = 253), complemented by open-ended qualitative responses. Results revealed that while they viewed AI as useful for enhancing efficiency and easy to use, concerns about content accuracy, over-reliance, and ethical issues persisted. Their high interest in AI contrasted with lower self-assessed proficiency, highlighting a gap between enthusiasm and competence. Institutional support significantly motivated adoption, whereas social influence played a lesser role. Students valued AI’s support in language learning, writing, research, and programming but noted its limitations in complex problem-solving. They also called for human-centric AI tools offering emotional support and personalized guidance. These findings may offer educators, policymakers, and AI developers valuable insights to address students’ concerns and optimize learning experiences in competitive academic environments. Full article

(This article belongs to the Topic AI Trends in Teacher and Student Training)

22 pages, 699 KB  

Open AccessArticle

Integration of Artificial Intelligence in K-12: Analysis of a Three-Year Pilot Study

by Boško Lišnić, Goran Zaharija and Saša Mladenović

AI 2025, 6(3), 49; https://doi.org/10.3390/ai6030049 - 1 Mar 2025

Viewed by 2412

Abstract

A three-year pilot study investigated the effectiveness of artificial intelligence (AI) as a motivational tool for teaching programming concepts within the Croatian Informatics curriculum. The study was conducted in schools through the extracurricular activity EDIT CodeSchool with the Development of Intelligent Web Applications [...] Read more.

A three-year pilot study investigated the effectiveness of artificial intelligence (AI) as a motivational tool for teaching programming concepts within the Croatian Informatics curriculum. The study was conducted in schools through the extracurricular activity EDIT CodeSchool with the Development of Intelligent Web Applications (RIWA) module. Twelve schools in Split-Dalmatia County in the Republic of Croatia participated, resulting in 112 successfully completed student projects. The program consisted of two phases: (1) theoretical instruction with examples and exercises, and (2) project-based learning, where students developed final projects using JavaScript and the ml5.js library. The study employed project analysis and semi-structured student interviews to assess learning outcomes. Findings suggest that AI-enhanced learning can effectively support programming education without increasing instructional hours, providing insights for integrating AI concepts into existing curricula. Full article

(This article belongs to the Topic AI Trends in Teacher and Student Training)

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