The Role of Artificial Intelligence in the Future of the Teaching Profession: Analysis of Competencies, Challenges, and Development Directions

The lack of teacher readiness in dealing with the integration of artificial intelligence (AI) in education is a significant challenge in the era of digital transformation. Teachers are required not only to master technology but also to possess ethical, reflective, and collaborative competencies in applying AI meaningfully. Therefore, this study aims to identify the competencies required of teachers, the challenges of implementing AI in educational settings, and the direction of relevant and sustainable professional development. This study employs a systematic literature review method on 12 selected articles from the Scopus database, based on a search using the keywords ‘Artificial Intelligence’, ‘teacher competence’, ‘AI in education’, and ‘TPACK’ in English-language articles published between 2020 and 2025. The articles were analysed thematically to explore the interrelationships between teacher competencies, challenges, and development strategies. The analysis results highlight the importance of mastering AI literacy, data management skills, and technology-based pedagogical abilities. The main challenges identified include ethical constraints, infrastructure limitations, resistance to change, and insufficient training. This study recommends the AI-TPACK approach, design thinking, and a growth mindset as a framework for adaptive and future-oriented teacher development

Bridging Artificial Intelligence Literacy and Technology Acceptance Among Elementary School Teachers: Evidence from a Structural Equation Model

AbstractThis study investigates the correlation between artificial intelligence (AI) literacy and acceptance among Indonesian elementary school teachers using a structural equation model. A cross-sectional survey of 409 teachers indicated elevated AI acceptance and literacy levels. AI literacy strongly predicted acceptance and vice versa, suggesting a bidirectional relationship between these two variables. Demographic factors exerted minimal influence, whereas the frequency of AI use showed a moderate correlation between the two constructs. The structural equation model revealed that social influence, facilitating conditions, and the progressive development of AI competencies significantly influenced teachers' behavioral intentions and ethical awareness. These findings underscore the necessity of comprehensive, experiential professional development programs that promote deep, reflective, and ethical engagement with AI technologies. This study advocates for a systemic, culturally responsive approach to AI integration in elementary education, aligning training, infrastructure, collaborative culture, and personalized support to prepare teachers for effective and responsible AI utilization.Keywords: artificial intelligence, AI literacy, UTAUT, teacher acceptance, elementary education. AbstrakPenelitian ini menyelidiki korelasi antara literasi dan penerimaan kecerdasan buatan (artificial intelligence/AI) di kalangan guru sekolah dasar di Indonesia dengan menggunakan model persamaan struktural. Sebuah survei cross-sectional terhadap 409 guru mengindikasikan adanya peningkatan tingkat penerimaan dan literasi AI. Literasi AI secara kuat memprediksi penerimaan dan sebaliknya, menunjukkan adanya hubungan dua arah antara kedua variabel ini. Faktor demografis memberikan pengaruh yang minimal, sedangkan frekuensi penggunaan AI menunjukkan korelasi yang moderat antara kedua variabel tersebut. Model persamaan struktural mengungkapkan bahwa pengaruh sosial, kondisi yang memfasilitasi, dan perkembangan kompetensi AI secara signifikan mempengaruhi niat perilaku dan kesadaran etis guru. Temuan ini menggarisbawahi perlunya program pengembangan profesional yang komprehensif dan berbasis pengalaman yang mendorong keterlibatan yang mendalam, reflektif, dan etis dengan teknologi AI. Studi ini mengadvokasi pendekatan sistemik dan responsif secara budaya terhadap integrasi AI dalam pendidikan dasar, menyelaraskan pelatihan, infrastruktur, budaya kolaboratif, dan dukungan pribadi untuk mempersiapkan guru dalam pemanfaatan AI yang efektif dan bertanggung jawab.Kata kunci: kecerdasan buatan, literasi AI, UTAUT, penerimaan guru, pendidikan dasar

Teachers' Perceptions and Readiness for Mobile Artificial Intelligence Integration in Elementary Education

The integration of artificial intelligence (AI) with mobile technologies, referred to as mobile AI, has transformed elementary education by providing personalized, interactive, and accessible learning experiences; however, its successful integration is significantly influenced by teachers’ perceptions, preparedness, and pedagogical competencies. This study employed a predominantly quantitative descriptive approach, complemented by qualitative data from open-ended questions, to investigate Indonesian elementary school teachers’ perceptions and readiness to integrate mobile AI tools. The findings revealed a gap between teachers’ positive perceptions and their moderate practical readiness. Personal experience was identified as the strongest predictor of readiness, whereas cognitive understanding and practical ability were significant predictors of perceptions. The structural equation model (SEM) supported these findings and revealed that readiness results from a series of developmental sequences rather than isolated events. This study highlights the need to address both psychological and practical barriers to adoption and offers actionable recommendations for harnessing the transformative potential of mobile AI in elementary education

AI-TPACK enhanced project-based STEM pedagogy: A model for cultivating 21st century skills in pre-service teachers

The objective of this paper is to evaluate the performance of the AI-TPACK-livened project-based STEM pedagogy model for the improvement of the 21st-century skills of the students of teacher education. The idea is perfectly in line with Technological Pedagogical Content Knowledge (TPACK), AI, project-based learning (PjBL), and also a cross-disciplinary STEM approach to provide an adaptable and contextual learning environment. The methods of quantitative, qualitative, and one-group pretest-posttest were used for a study. It covered 213 potential teacher students. The Partnership for 21st Century Learning (P21) Framework-based 21st-century skills scale determined the level of critical thinking, creativity, communication, and cooperation. The paired sample t-test and Cohen’s d calculation were used to determine the intervention’s significance and efficacy. Besides, in order to learn about students’ experiences throughout the learning process, semi-structured interviews were conducted. The authors state that their work is consistent with this model of students’ critical thinking, creativity, communication, and collaboration skills. The qualitative data are in agreement with the student stories about the involvement, the self-reflection, and the collaborative nature of the learning experience as well. The work promotes the utilization of the AI-TPACK model in teacher education as an innovative pedagogical strategy that can effectively respond to 21st-century challenges

The Changing Landscape of ELT: Past Lessons, Future Visions

The landscape of English Language Teaching (ELT) has evolved significantly over the past 75 years, marked by major shifts in theoretical, technological, and sociocultural approaches to language teaching and learning. From the dominance of behaviorist methods in the mid-20th century to todays innovations in digital, tech-mediated language learning, these transformations have created both opportunities and challenges for teachers. The rapid growth of technology, along with the changing status of English as a global language and the evolving goals of language learning, has further reshaped how languages are taught and learned. Yet, amidst these profound changes, the role of teachers remains central. Teachers are tasked not only with adapting evidence-based methods to address the diverse needs of students but also with fostering meaningful interactions, encouraging critical thinking, and maintaining high levels of student engagement. As ELT continues to advance, teachers are called upon to continually reflect on their practices, adopt new evidence-based approaches, and adjust their teaching methods to meet the evolving needs of their students

Bridging Artificial Intelligence Literacy and Technology Acceptance Among Elementary School Teachers: Evidence from a Structural Equation Model

This study investigates the correlation between artificial intelligence (AI) literacy and acceptance among Indonesian elementary school teachers using a structural equation model. A cross-sectional survey of 409 teachers indicated elevated AI acceptance and literacy levels. AI literacy strongly predicted acceptance and vice versa, suggesting a bidirectional relationship between these two variables. Demographic factors exerted minimal influence, whereas the frequency of AI use showed a moderate correlation between the two constructs. The structural equation model revealed that social influence, facilitating conditions, and the progressive development of AI competencies significantly influenced teachers' behavioral intentions and ethical awareness. These findings underscore the necessity of comprehensive, experiential professional development programs that promote deep, reflective, and ethical engagement with AI technologies. This study advocates for a systemic, culturally responsive approach to AI integration in elementary education, aligning training, infrastructure, collaborative culture, and personalized support to prepare teachers for effective and responsible AI utilization

Exploring the Integration of Artificial Intelligence into Special Education Teacher Preparation through the TPACK Framework

With the introduction of artificial intelligence (AI), specifically generative AI and large language models (e.g., ChatGPT, Google Gemini), into education, there is a conversation regarding what knowledge teachers still need and will need moving forward. In this article, we describe how AI can, and should, be aligned to the Technological Knowledge, Pedagogical Knowledge, and Content Knowledge (TPACK) framework, as a part of special education teacher preparation. Additionally, we explore the implications of AI on the TPACK framework, specifically how AI can be integrated within each of the three components, specific tools that support each aspect, and guiding questions that teacher-educators and pre-service teachers should be using when considering AI. We will provide teacher-educators with example activities they can use with their pre-service teachers to introduce AI and integrate its use within their curriculum, framed within the TPACK

Professional development of informatics teachers using artificial intelligence based on self-assessment of AI competence

Зміст статті акцентує на важливості підготовки вчителів інформатики до використання штучного інтелекту (ШІ) в професійній діяльності та розвитку їх ШІ компетентності з метою підготовки учнів до сучасних викликів та можливостей за допомогою цифрових технологій. Стрімкий розвиток ШІ вимагає від вчителя інформатики неперервного професійного розвитку, а програми підвищення кваліфікації повинні сприяти у формуванні відповідних компетентностей щодо відбору та аналізу освітніх ресурсів на основі ШІ, створення навчального контенту із його використанням, а також надання підтримки школярам у середовищах, де навчання частково або повністю керується ШІ. Аналіз досліджень дозволив визначити підходи до використання ШІ в освітньому процесі та можливості використання рамки ШІ компетентності для вчителів і учнів для визначення напрямів професійного розвитку вчителів, зокрема запровадження ШІ хабів та залучення до викладання на курсах підвищення кваліфікації вчителів з високим рівнем ШІ компетентності. Анкетування 180 вчителів щодо самооцінювання рівня ШІ компетентності та потреб у програмах професійного розвитку дозволило зіставити результати теоретичних розвідок і запитів вчителів інформатики в порівнянні з іншими педагогами визначити стратегії та напрями професійного розвитку вчителів для ефективного впровадження інноваційних інструментів ШІ серед яких: аналіз навчальних даних, етика використання ШІ, створення навчальних матеріалів та ін. Використання ШІ в інформатичній галузі має потенціал для покращення результатів навчальних досягнень учнів. Аналіз результатів опитування педагогів підтверджує готовність вчителів інформатики до професійного розвитку, опанування програм підвищення кваліфікації з використання ШІ. Професійний розвиток вчителів інформатики щодо використання ШІ на основі інтеграції технічних, педагогічних, етичних і регуляторних напрямів Дослідження розглядає важливість та напрями підготовки вчителів для використання ШІ в післядипломній освіті та висвітлює ідеї та підходи до розвитку ШІ компетентності вчителів інформатики, сприяючи підвищенню якості освіти та підготовці молодого покоління до викликів майбутнього.The article focuses on the importance of preparing computer science teachers to use artificial intelligence (AI) in their professional practice and to develop their AI competence to equip students with the skills needed to face modern challenges and opportunities through digital technologies. The rapid advancement of AI demands continuous professional development from computer science teachers. Professional training programs should support the formation of competencies related to selecting and analysing AI-based educational resources, creating instructional content using AI, and assisting students in environments where learning is partially or fully AI-driven. An analysis of research allowed the identification of approaches to integrating AI into the educational process and highlighted the potential of the AI competence frameworks for teachers and students as tools to define directions for professional growth. This includes the establishment of AI hubs and the involvement of highly competent AI teachers in delivering professional development courses. A survey of 180 teachers regarding their self-assessed AI competence and needs for professional development programs enabled a comparison between theoretical insights and the actual demands of computer science educators in contrast to teachers of other disciplines. Based on this, strategies and directions for teachers’ professional growth were identified to ensure the effective implementation of innovative AI tools. These include learning analytics, AI ethics, instructional material design, and more. The integration of AI into computer science education shows significant potential to enhance student learning outcomes. Survey results confirm the readiness of computer science teachers to engage in professional development and participate in AI-focused training programs. The professional development of computer science teachers in the context of AI should be based on the integration of technical, pedagogical, ethical, and regulatory aspects. This study explores the significance and key areas of teacher preparation for AI use in postgraduate education and presents ideas and approaches to fostering AI competence among computer science teachers, ultimately supporting educational quality and preparing the younger generation for the challenges of the future

Improving English Oral Communication through Multimodal Learning Strategies for Secondary School Students

Background – The rapid integration of digital technologies and artificial intelligence (AI) in education presents both opportunities and challenges, especially in improving English oral communication and promoting ethical digital behavior. AI-driven multimodal platforms that combine visual, auditory, reading/writing, and kinesthetic modes offer inclusive learning, but teachers must develop ethical, reflective, and collaborative competencies to ensure responsible AI use. Issues such as digital inequality, limited infrastructure, and insufficient professional development highlight the need for innovative frameworks aligned with Kurikulum Merdeka. Purpose – This study aims (1) to design and analyze a conceptual framework for an AI-driven multimodal learning platform that personalizes English oral communication, provides real-time feedback, and strengthens students’ digital citizenship; and (2) to identify essential teacher competencies and challenges related to AI integration to guide sustainable professional development. Method/Approach – A qualitative conceptual design was applied by synthesizing literature on multimodality, AI in education, teacher competence, and digital citizenship. This was supported by a systematic literature review (SLR) of 12 Scopus-indexed articles (2020–2025) using the keywords “Artificial Intelligence,” “teacher competence,” “AI in education,” and “TPACK.” Thematic analysis with iterative coding ensured analytical reliability. Findings – The proposed multimodal–AI framework shows strong potential to enhance oral communication through AI-enabled personalization, speech-recognition feedback, and interactive multimodal tasks. The review identifies three core teacher competency domains: AI literacy and ethical awareness, data-driven digital pedagogical design, and collaborative reflective practice. Major challenges include limited infrastructure, unequal digital access, ethical concerns, and inadequate AI-focused training. Conclusion – Adopting AI–TPACK, design thinking, and growth-mindset principles can guide effective professional development in multimodal–AI learning environments. Novelty/Originality/Value – The study’s originality lies in integrating language proficiency and ethical digital citizenship within a unified multimodal–AI framework, offering theoretical contributions and practical direction for future educational innovation

Analysis of Science Teachers' Content Knowledge on the Concept of Global Warming

The ability of teachers to interpret the curriculum is essential in the preparation stage of teaching. This ability includes how teachers sequentially organize content from simple to more complex material. Teachers are also expected to master the subject matter, meaning they have broad and deep understanding of the material. Therefore, the aim of the research is to explore teachers' understanding of the material taught. This research was conducted using a descriptive method by applying an instrument for understanding the concept of global warming. The participants in this study were 19 Science teachers who are members of the Science Teachers Working Group (MGMP) in Majene Regency, West Sulawesi. The results showed that, in general, Science teachers have fairly good CK, evidenced by the percentage of teachers with moderate and high CK being 55% and 15%, respectively. Teachers understand the topic being discussed. However, not in depth or not mastered well. This is evidenced by the lack of depth of teachers' answers related to a problem, in other words, teachers cannot elaborate on the answers with things that can be accepted by students