2026· AI-Enhanced Learning· Vol 2, pp. 231-253· 0 citations
TL;DR
The study found that AI-focused professional development significantly enhanced faculty knowledge and comfort with AI integration among the 100 faculty members who participated in the study, and revealed a critical gap in ethical AI knowledge.
Abstract
To effectively integrate AI into education, university instructors need to have AI-specific technological, pedagogical, and content knowledge (TPACK). Research indicates that university instructors often feel unprepared with these competencies; thus, they lack the knowledge to effectively integrate AI tools into their teaching practices. While substantial literature exists on AI in education, there remains a significant gap in faculty-centered research, particularly regarding instructor knowledge, comfort, and ethical understanding of AI implementation in higher educational contexts. This study examined faculty perceptions regarding their AI-TPACK knowledge, ethics-based AI knowledge, and then assessed whether those perceptions were influenced by training in AI tools. Using a quantitative descriptive cross-sectional research design that is based on Celik’s TPACK framework, this empirical research examined faculty members’ self-perceived competencies in each area. The study found that AI-focused professional development significantly enhanced faculty knowledge and comfort with AI integration among the 100 faculty members who participated in the study. Also, the findings revealed a critical gap in ethical AI knowledge, underscoring the urgent need for ethics-specific training to build faculty confidence in classroom implementation. Universities should leverage these findings to offer targeted professional development initiatives that close identified gaps and improve instructional effectiveness and faculty digital literacy skills.
: In the new digital and AI era, hybrid teaching models increasingly incorporate intelligent resources into everyday practice. The main aim of this paper is to analyze how teachers perceive their AI competencies, the purposes for which they apply AI in teaching practice, and how confident they feel when integrating intelligent models into their teaching practices. A quantitative survey was conducted in Serbia, involving 80 teachers from diverse fields and educational levels. The questionnaire combined items on digital and AI competencies with questions addressing teachers’ self-perceptions and the psychological effects of AI integration. Results show that teachers primarily associate educational technology with AI, use it mainly for lesson preparation, and report psychological effects such as enhanced confidence, motivation, and innovation. At the same time, ambivalence and uneven adoption highlight challenges, including limited experience, lack of training, and concerns about risks. The study contributes empirical evidence to the emerging field of teacher AI competence research, situating Serbian educators’ perspectives within the broader international discourse. It underscores the importance of professional development and supportive environments to ensure that AI integration fosters pedagogical innovation and promotes teacher well-being.
Maja Veljković Michos, Valentina B. Bošković Marković, Milica Čolović· SINTEZA· 0 citations
This study examines faculty self-perceived knowledge for generative AI (GenAI) integration in higher education using the TPACK-21 framework.
A survey was administered to 127 faculty members at a large Southern U.S. university. Self-perceived knowledge was assessed across seven TPACK domains, and relationships were analyzed by gender, age, and appointment type. Descriptive statistics, one-way analyses of variance, and Pearson correlation coefficients were used to examine perceived knowledge across the seven domains and the relationships among them.
Faculty reported high self-perceived knowledge in traditional domains, including pedagogical knowledge, content knowledge, and pedagogical content knowledge. In contrast, lower self-perceived knowledge was observed in technology-integrated domains, including technological pedagogical knowledge, technological content knowledge, and overall TPACK. Statistically significant gender differences were found in the technological knowledge and technological pedagogical knowledge domains, with male faculty reporting modestly higher self-perceived knowledge; however, the effect sizes were small. No other significant differences were identified across demographic variables. Correlation analyses showed that technological knowledge of GenAI was strongly associated with self-perceived knowledge in technology-integrated domains.
The findings suggest a gap between faculty members' established pedagogical strengths and their confidence in integrating GenAI into teaching and learning. Targeted, discipline-specific professional development programs may help bridge this gap and support faculty in designing GenAI-enhanced instruction that promotes 21st-century skills.
Armanto Sutedjo, Mahjabin Chowdhury, S. Liu· Frontiers in Education· 0 citations
The rapid development of artificial intelligence (AI) has been significantly influencing the transformation of higher education, with faculty playing a key role in this process. Previous research has largely focused on students, while the perspectives of university faculty in Serbia remain underexplored. Drawing on the understanding of beliefs as key predictors of behaviour, this study examines faculty beliefs about AI and the factors shaping them. The study was conducted on a sample of 125 educators working at eight higher education institutions in Serbia. The findings indicate that faculty most frequently use AI in research and course preparation, and less commonly in teaching and assessment. A gap was identified between theoretical reflections and faculty's actual beliefs about AI's potential. While faculty recognise AI's contribution to efficiency and the development of students' digital competencies, they remain neutral regarding its role in core aspects of teaching and assessment. Differences in faculty's beliefs are associated with the frequency and domains of AI use, professional development and institutional support.
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.
Aslihan Unal, John Hobe· Education sciences· 0 citations
The integration of Artificial Intelligence (AI) within Technical-Vocational Education and Training (TVET) is increasingly shaping the educational landscape, presenting both novel pedagogical opportunities and complex challenges. This systematic literature review investigates how instructors and students perceive and experience the implementation of AI-supported teaching and learning approaches in TVET settings. This review addresses the growing need to understand the human dimensions of AI adoption in vocational education, particularly from the perspectives of those directly involved in teaching and learning. As AI technologies become increasingly embedded in educational practices, examining the experiences, perceptions, and concerns of instructors and students is essential for informing effective and responsible implementation strategies. By synthesizing evidence across diverse TVET contexts, this review provides insights into emerging opportunities, challenges, and implications for policy and practice. Following the PRISMA 2020 framework, an initial database search on Lens.org yielded 580 records. After applying rigorous inclusion and exclusion criteria, including filters for publication date, document type, and subject matter, 19 empirical studies were selected for final qualitative synthesis. The findings reveal three overarching themes. First, while instructors exhibit optimism regarding efficiency gains, they express significant concerns about dehumanization, cognitive decline, and threats to academic integrity. Second, students experience enhanced psychological safety through instant feedback, yet face a paradox of being "Engaged but Amotivated" alongside risks of severe technological dependency. Third, AI implementation in TVET is uniquely constrained by the necessity for tactile skill mastery, industry precision, and alignment with local cultural practices. Ultimately, maximizing AI's potential in vocational education requires addressing systemic infrastructure barriers and preserving the hands-on, human-centric core of TVET.
Iron G. Morales, John Hillard Mansueto, Russel M. Dela Torre· International journal of res...· 0 citations
This research explores the prevalence and nature of Artificial Intelligence (AI) utilization among college students, particularly in enhancing their learning experiences. Through a participant-centered approach, 100 undergraduate students from the United States were surveyed to understand their engagement with AI tools in higher education. The study examines the frequency of AI usage, how students utilize AI in coursework, and their perceptions of AI's potential to enhance learning. Results indicate a significant level of AI usage among students, primarily for content management and academic support. Students perceive AI positively, attributing benefits to improved learning outcomes and increased efficiency. They envision AI as a tool for content creation, comprehension, and fostering inclusivity in education. The findings highlight the importance of integrating ethical considerations and promoting digital literacy in AI-enabled learning environments. This research contributes valuable insights for educators, policymakers, and technologists involved in higher education, emphasizing the need for responsible AI adoption and inclusive practices to harness its transformative potential.
Christina Costa, Martha Almendarez Langland, Jason Roberson et al.· The Journal of Scholarship o...· 0 citations