Effect of Teaching Experience with the use of AI
Teachers' perceptions of AI integration vary based on their teaching experience, with notable differences between experience groups. In particular, teachers with more than 10 years of experience tend to have more positive perceptions of AI integration than teachers with less than 5 years of experience. This difference in perception based on teaching experience highlights the influence of educators' professional background on their attitudes toward AI integration in education (Yau et al., 2022).
In addition, this study emphasizes the importance of developing effective teacher professional development programs in the field of AI education. It suggests that providing targeted training and support to teachers can improve their readiness and attitudes towards AI education, potentially bridging the perception gap observed among teachers with different levels of experience (Yue et al., 2024).
In addition, the research also highlights the need to support teachers to ensure their efficiency and effectiveness in integrating AI into their work practices. Using AI as a tool to support educators can help improve their skills and foster a more positive outlook on AI integration in education (Chounta et al., 2021)..
In conclusion, the synthesis of these studies suggests that teaching experience plays an important role in shaping teachers' perceptions of AI integration in education. Providing tailored professional development programs and support systems for educators can be an important tool in fostering positive attitudes toward AI and improving their readiness to effectively integrate AI tools into classroom practice.
Evidence suggests that more experienced teachers are generally more open to using technology in their classrooms than less experienced teachers (Pierce & Ball, 2009). This trend suggests that educators with longer tenure in the classroom are more receptive to incorporating technological advances such as AI into their pedagogical practices.
In addition, Chiu & Chai (2020) found that teachers perceive that teaching with technology requires more time, both for preparation and during class, compared to traditional teaching methods. This perception may be influenced by teachers' different levels of experience, where more experienced educators may have developed strategies to efficiently integrate technology, including AI, into their teaching routines
In addition, research shows that teachers' confidence in using technology is positively correlated with their experience using computers, suggesting that familiarity with technology increases educators' willingness to adopt innovative tools such as AI in their teaching practices (Teo et al., 2016). This further supports the notion that teachers with more experience are more likely to embrace technological advancements in education.
In summary, the existing literature consistently shows that teachers with more teaching experience are more likely to have positive attitudes toward the integration of technology, including AI, in educational settings. These findings underscore the importance of considering the professional background and experience of educators when implementing innovative technologies, such as AI, into classroom practices.
Age Influence
Based on age classification, teachers have similar views on the use of AI in learning. The results of this study are in line with previous research, which showed no significant difference in teachers' perceptions of technology integration based on age (Mahdi & Aldera, 2013; Almalki, 2020). These studies show that teachers from different age groups tend to have similar views on the use of technology in classroom practices. This consistency in perceptions across age groups suggests that when it comes to technology adoption, including AI integration, age may not be a determining factor in shaping educators' attitudes. Instead, factors such as teaching experience, education, and familiarity with technology may play a more significant role in influencing the acceptance and use of AI tools in educational settings.
The results of this study showing that age does not significantly affect teachers' perceptions of AI integration in learning contradict the findings of previous studies, such as Johnson et al.'s (2019) study, which found that younger teachers are generally more accepting of new technologies than older teachers (K. Chen & Chan, 2014). Although some studies have highlighted age as a factor influencing technology acceptance, the current study shows that age does not play a significant role in shaping teachers' attitudes toward AI in education.
These contrasting findings highlight the complexity of the factors that influence educators' acceptance of technology, including AI, in classroom practice. While age has been identified as a relevant factor in some studies, the results of this study suggest that other variables, such as teaching experience, training, and familiarity with technology, may have a greater impact on teachers' perceptions of AI integration in educational settings (Zulkarnain & Yunus, 2023).
The differences between the current and previous research highlight the need for further exploration and a deeper understanding of the various determinants that shape teachers' attitudes toward technology adoption, particularly in the context of AI in education. By considering a broader range of factors beyond age, future research can provide more comprehensive insights into the dynamics of technology adoption among educators and inform the development of targeted strategies to promote effective integration of AI into classroom practices.
Theoretical Implications
The influence of teaching experience on teachers' perceptions of AI integration has significant theoretical and practical implications for the development of teacher preparation programs.Theoretically, frameworks such as TPACK can be the basis for designing programs that improve teachers' readiness and attitudes toward AI education (Yue et al., 2024). Integrating AI technologies into teachers' professional learning can promote adaptive teaching practices and develop professional vision (Tammets & Ley, 2023). Developing AI literacy among teachers is essential for effective integration of AI tools (Zhao et al., 2022). While the instructional paradigm shift requires the preparation of educators who can facilitate the learning process through innovative approaches (Atibuni et al., 2022).
In terms of age, the findings suggest that the AI in Learning training program can be designed uniformly without considering differences in teacher age. The findings suggest that AI in learning training programs do not need to be differentiated based on teacher age. The same training can be given to all age groups, focusing on the practical benefits of using AI in learning. This can simplify the implementation of the training program without having to adapt the materials based on age. A unified AI training program for teachers of all ages has significant theoretical and practical implications. Theoretically, this approach aligns with self-determination theory (Chiu & Chai, 2020), encourages collaborative learning (Chiu et al., 2022), and challenges age-based perceptions of technology integration (Mahdum et al., 2019).
Practical Implications
In practice, training programs should take into account the experience level of teachers, with more intensive approaches for less experienced teachers and opportunities for mentoring for experienced teachers (L. Chen et al., 2020). Investing in programs that build technological and pedagogical skills can improve the competence of future teachers in AI education (Tunjera & Chigona, 2023). Project-based learning experiences can foster a mindset that is more receptive to the use of new technologies such as AI (Belda-Medina & Goddard, 2024). Ongoing professional development programs can build confidence in effectively integrating AI tools (Ayanwale et al., 2024).. Curriculum reform and professional development opportunities are essential to strengthen the integration of pedagogical content knowledge (PCK) among teachers (Kshetree, 2023).
Additionally, this approach simplifies the training process (R. Jiang, 2022), increases teacher confidence in applying AI (N. Kim & Kim, 2022), facilitates the scalability of AI education initiatives (Bataineh & Anderson, 2015) and empowers teachers to explore innovative methods (Otero et al., 2023). This unified approach ultimately promotes inclusivity, standardization, and practical relevance in professional development for AI integration in education, simplifying implementation without the need for age-specific customization.
Research Limitations
This study was limited to a population of teachers in Papua and Central Java, so generalizing the results should be done with caution. In addition, the quantitative approach used did not explore teachers' perceptions qualitatively, which could have provided deeper insights into the factors influencing their perceptions of AI integration in learning. This study may also be influenced by other unmeasured factors, such as educational level, personal interest in technology, and access to technology resources.
Future research can use longitudinal studies that can track changes in teachers' perceptions of AI over time, especially after they have received training or experience using AI in the classroom. In addition, comparative research across regions or countries can provide a broader understanding of how cultural and socioeconomic contexts affect the adoption of AI in education. Experimental studies that compare the effectiveness of different methods for integrating AI into learning can also provide valuable insights for developing best practices for using AI in the classroom.