Aug 2026· Education sciences· 0 citations· 19 references
TL;DR
Examination of preservice teachers’ perceptions of AI and the competencies they considered necessary for effective AI integration highlighted the importance of preparing preservice teachers to integrate AI in pedagogically meaningful and ethically responsible ways.
Abstract
Preparing future educators for technology-enhanced learning environments has become increasingly important as artificial intelligence (AI) continues to influence teaching and learning. Guided by the Intelligent Technological Pedagogical Content Knowledge (i-TPACK) framework, this mixed-methods study examined preservice teachers’ perceptions of AI and the competencies they considered necessary for effective AI integration. Participants included 108 preservice teachers enrolled in a teacher preparation program at a public university in the southeastern United States. Data were collected using a survey containing Likert-scale and open-ended questions. Quantitative data were analyzed using descriptive statistics, exploratory factor analysis, and independent-samples t-tests, while qualitative responses were analyzed using thematic coding. The exploratory factor analysis identified a four-factor empirical structure that partially corresponded with the original theoretical domains, with varying levels of internal consistency. Preservice teachers generally viewed AI favorably and recognized its potential to support teaching and learning. Participants with internship experience reported significantly higher scores for perceived changes brought by AI and reasons for using AI than those without internship experience. Qualitative findings identified five competencies considered important for responsible AI integration: AI literacy, prompt engineering, critical evaluation, ethical AI use, and pedagogical balance. Participants also expressed concerns about academic dishonesty, misinformation, overreliance on AI, reduced critical thinking, and loss of human interaction. The findings highlight the importance of preparing preservice teachers to integrate AI in pedagogically meaningful and ethically responsible ways.
The proliferation of Artificial Intelligence and simulation technologies has opened transformative possibilities for teacher education. Despite these advancements, developing the capacity of teacher trainees to engage and motivate learners effectively during classroom instruction remains a persistent pedagogical concern. This study investigated the effectiveness of AI-integrated microteaching and simulated classroom environments in enhancing pedagogical engagement skills and motivation skills among teacher trainees — operationally defined as the measurable competencies to stimulate active learner participation and sustain intrinsic motivation during instructional delivery. A Descriptive Survey Research Design was employed. Using purposive sampling, 100 B.Ed. teacher trainees from a recognized teacher education institution in Jammu constituted the study sample. Data were collected using a validated Student Engagement and Motivation Skill Observation Checklist and a structured 30-item Likert-scale questionnaire spanning three dimensions, with established reliability (Cronbach’s α = 0.87 and 0.84 respectively). Mean and Standard Deviation were computed to determine the extent and consistency of perceived effectiveness of AI-integrated microteaching across the sample, while percentage analysis was used to capture the distribution of trainee responses. Results indicated that 82% of trainees rated AI-integrated microteaching as highly effective in building engagement skills; the high Mean (4.21) confirmed strong overall perceived effectiveness, while the low SD (0.43) reflected a high degree of agreement among trainees. Similarly, 78% reported substantial enhancement in motivation skills through simulated classroom environments (Mean = 4.08, SD = 0.51), indicating consistently positive perceptions with minimal variation. The study recommends systematic incorporation of AI-integrated pedagogical tools within teacher education curricula to strengthen professional teaching competencies
S. Gupta, Reeta Dwivedi, Jyoti Sharma· International journal of res...· 0 citations
This study evaluated teachers' competency in incorporating Artificial Intelligence (AI) in developing educational materials at Saint Estanislao Kostka College Incorporated. Anchored on the Technology Acceptance Model (TAM), Shulman's Pedagogical Content Knowledge (PCK), and Continuous Professional Development (CPD), the study examined teachers' professional engagement, instructional support, content choices across disciplines, and students' learning competencies in AI-assisted instructional material development. A descriptive-quantitative research design was employed using purposive sampling among teacher-respondents during the Academic Year 2023–2024. Data were collected through an adapted questionnaire utilizing a five-point Likert scale and analyzed using frequency count, percentage, weighted mean, and Factorial Multivariate Analysis of Variance (MANOVA). The findings revealed that teachers demonstrated a very competent level of AI competency across all assessed dimensions, indicating strong professional engagement, effective instructional support, appropriate content selection across disciplines, and the ability to promote students' learning competencies through AI-assisted educational materials. The analysis further showed no significant differences in competency when grouped according to sex and educational attainment. Overall, the study concludes that teachers possess the competencies necessary to integrate AI responsibly, ethically, and effectively in instructional material development. It recommends strengthening continuous professional development, implementing systematic review processes for AI-generated instructional materials, enhancing institutional support, and expanding future studies through larger populations and additional variables. The study aligns primarily with Sustainable Development Goal (SDG) 4 – Quality Education by supporting teacher competency and instructional quality, while also contributing to SDG 9 – Industry, Innovation and Infrastructure, SDG 10 – Reduced Inequalities, and SDG 17 – Partnerships for the Goals through responsible AI integration and collaborative educational innovation. By strengthening teachers' AI competencies, the study contributes to educational, institutional, technological, and community sustainability through the responsible and ethical use of AI in teaching and learning.
Richard Batbatan· International Journal of Sus...· 0 citations
As artificial intelligence (AI) continues to reshape modern society, there is an urgent need to equip K–12 educators with the skills and confidence to integrate AI tools into their instructional practice. This pilot study examined the preliminary effectiveness of an asynchronous professional development course designed to increase educators’ comfort with AI, shift their perceptions, and expand access to instructional resources. A mixed-methods approach was used to analyze data from 30 participants, including K–12 teachers, preservice educators, and others in educational roles in K–12 schools, who completed pre- and post-course surveys. Quantitative results revealed statistically significant increases in comfort with AI, perceptions of AI, access to resources, and familiarity with AI tools. Correlational analyses found strong positive relationships between perceptions, resource access, and comfort. No significant differences were observed across demographic variables; while this does not establish equivalence, it suggests the course may be broadly accessible across participant groups. Qualitative findings, including participant reflections, highlighted the transformative impact of the course, with educators reporting a shift from skepticism to enthusiasm. The course’s modular design, grounded in best practices for professional learning, was well-received and scalable. Recommendations include expanding the course to a larger and more mixed sample, integrating AI training into preservice teacher education, and updating content regularly to reflect the rapidly evolving AI landscape. This research demonstrates that thoughtfully designed, flexible professional development can build AI literacy and empower educators to adopt emerging technologies with confidence and purpose. As data collection is ongoing, these findings represent early trends that will inform future iterations and expanded implementation.
This qualitative study examines the perspectives of in-service teachers regarding the integration of Artificial Intelligence (AI) into educational settings. A purposive sampling framework combining criterion and snowball sampling strategies was employed, semi-structured interviews were conducted with 23 in-service teachers. Data were analyzed through content analysis. The analysis revealed three themes: teachers’ current digital practices, AI acceptance and integration of AI. The findings showed that teachers currently use digital technologies for various pedagogical purposes and have also begun using AI technologies in educational settings. Also, teachers perceived AI as useful because of easier access to information, time efficiency, decision-making support, personalized feedback, and professional development. However, they also expressed pedagogical and ethical concerns regarding student overreliance, academic dishonesty, the potential misuse of AI, data security, and the digital divide. The results indicate that, given the multifaceted nature of AI technologies successful AI integration requires specific teacher competencies, particularly critical AI literacy and ethical awareness competencies. Findings also suggest that successful integration requires practical, subject-specific training for both in-service and pre-service teachers, training for students, family engagement, and financial support. This study provides insights into how teachers use AI technologies, their perceptions of required competencies, the challenges and concerns they perceive. Limitations and suggestions for future research are also discussed.
Feray Uğur Erdoğmuş· Participatory Educational Re...· 0 citations
The rapid advancement of artificial intelligence (AI) in education has identified the need to understand how future educators perceive and engage with these technologies. This study investigates the AI self-efficacy of English as a Foreign Language (EFL) student teachers across three distinct educational contexts: Japan, Poland, and Slovakia. Recognising the crucial role of self-efficacy in technology adoption, this research aims to compare how pre-service teachers in these countries perceive their capabilities in utilising AI tools for language learning and teaching. The study employed a mixed-method design to collect quantitative data using a specifically designed evaluation scale and qualitative data via an open-ended questionnaire. The sample comprised 98 EFL student teachers from the selected countries. Results revealed observable differences in AI self-efficacy scores among participants from Japan, Poland, and Slovakia, with Japanese participants reporting higher confidence levels than their Polish and Slovak counterparts. The findings highlight a need for further research examining which contextual, educational, or experiential variables may underlie these cross-country differences.
Z. Kráľová, Osamu Takeuchi, Viktorie Vršanská et al.· Asian-Pacific Journal of Sec...· 0 citations
This systematic literature review investigates how instructors and students perceive and experience the implementation of AI-supported teaching and learning approaches in TVET settings and provides insights into emerging opportunities, challenges, and implications for policy and practice.
Iron G. Morales, John Hillard Mansueto, Russel M. Dela Torre· International journal of res...· 0 citations
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