The study identifies the challenge of introducing

The gap

Evidence profile

Sourced from the limitations and recommendations and stated challenges of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 8 journals. Those papers have been cited 7 times in total.

Supporting evidence — 8 representative gaps

• Examining the use of artificial intelligence in pre-service teacher education (2026) · Contemporary Educational Technology · doi

  The studies analyzed in this review were mainly carried out in particular geographical contexts, which could restrict the applicability of the findings to different educational systems and cultures. In addition, the swift progress in AI technologies has the potential to affect the relevance of some findings over time, as the emergence of new tools and applications continues to reshape the educational landscape. It should also be acknowledged that this review was based on the existing published literature, and there may be further unpublished studies or ongoing research that could offer additional insights into the subject. Despite these limitations, this systematic review provides valuable insights into the current state of AI integration in PST education and establishes a foundation for future research and practice. Although there are certain limitations, this systematic review gives significant insights into the status of AI integration in PST education and establishes a basis for future research and implementation. Given the ongoing progress and influence of AI technologies in education, it is imperative for teacher education institutions, policymakers, and academics to work together and tackle the obstacles and possibilities that come with integrating AI into education. By providing PSTs with the necessary skills to effectively use AI technologies and understand the ethical considerations, we can guarantee that the future generation of educators can utilize AI’s promise to improve teaching and learning in the 21st century. Author contributions: Conceptualization: EBP, OVS, MRZ; Data curation: OVS, KMB; Formal Analysis: EBP, KMB, MVM; Methodology: EBP, MRZ, RLB; Writing – original draft: OVS, MRZ; Writing – review & editing: EBP, RLB, MVM. All authors approved the final version of the article.

  generallimitationsevidence 5/5
  Keywords: review education authors technologies insights systematic future ethical article intelligence analyzed educational progress published there
• Empowering pre-service teachers with generative AI: a GenAI-TPACK-based approach to digital storytelling (2026) · Education and Information Technologies · cited 1× · doi

  This section summarises the practical implications of the findings, particularly for the design of teacher education programmes and for course-level implementations grounded in the GenAI-TPACK framework. A set of program-level and course-level implications emerges from these findings. Teacher education programs could benefit from a holistic orientation in which generative AI is situated not merely as a technical aid but as part of an integrated repertoire that connects pedagogical intent, ethical awareness, and content knowledge (GenAI-TPACK, with TEAK). In practice, this orientation can be aligned with national standards (MoNE) and internationally recognized competency frameworks (e.g., UNESCO AI-CFT, DigCompEdu), while capacity-building for teacher educators supports consistent implementation. Within courses, hands-on, scenario- and case-based activities that involve scripting, storyboarding, and multimodal production may help candidates link tool choices to instructional goals and document decisions transparently, including brief disclosures of AI use consistent with institutional guidance (e.g., CoHE). Attention to equity and localization, such as access to no-cost or low-bandwidth tools, Turkish-language prompting and outputs, and accessibility features, appears important for sustained adoption. To complement self-reports, programs may incorporate light-touch formative and summative evidence (curriculum-fit checks, short engagement indicators, brief classroom observations) and solicit student feedback to triangulate results. Developing small shared repositories of open resources, prompt templates, rubric examples, and model disclosure statements could further support diffusion and continuous improvement. Finally, future work might extend these results through mixedmethod or quantitative designs with larger and more diverse samples, including artifact analyses and inter-rater reliability, to strengthen generalizability and refine how GenAI-TPACK components are enacted in authentic contexts. Education and Information Technologies1 37 Limitations and future research directions This study was conducted within the framework of a qualitative research design and provides an in-depth understanding of pre-service primary teachers’ experiences with generative AI-supported digital storytelling processes. However, several limitations should be considered. The study was carried out with a limited number of secondyear pre-service teachers enrolled at a public university in Türkiye. Despite the richness of the qualitative data, the generalizability of the findings to broader populations remains limited. Data collection was based on self-reflective reports, digital storytelling products, and written open-ended responses provided by the participants.

  generalrecommendationsevidence 5/5
  Keywords: teacher education level genai tpack implications design course framework programs orientation generative consistent within based
• Training Needs Assessment for Teachers on ICT and AI in 21st Century Inclusive Classrooms (2026) · Journal of Education and Training Studies · doi

  We suggest to start a province-wide, competency-based Continuous Professional Development programme, organized into three progressive levels, namely, basic, intermediate and advanced, all in accordance with modern pedagogical demands, including ICT-based integration, AI-based lesson planning and inclusive digital pedagogies. Pragmatic modules ought to be demonstrated to be applicable and modules must be linked to professional certification and promotion credits to instill accountability and long-term sustainability. 2. It is necessary to create the District ICT-AI Support Cells one in each district, and its foundation is QAED/DEA. These units would be offering on-demand technical support, guidance to assistive technologies, such as screen readers, augmentative and alternative communication tools, captioning and accessible formats, and ease coaching visits to schools, which lowers the reliance on ad-hoc teacher troubleshooting. 3. There is a strategic necessity to prioritise under-resourced institutions, especially the rural ones. A basic infrastructure package must be provided, including practicable, reliable broadband and back-up power options, projection or smart-display technologies, teacher laptops or tablets, and other necessary accessibility tools, and should be introduced to inclusive schools and special-education integrated clusters. The phased roll-out of this kind will reduce the digital divide. 4. A Punjab-specific AI-in-Education policy should tackle the privacy of data, student safety, academic honesty and bias reduction. Such principles must be used to guide specific education to the headteachers and teachers about the responsible use of AI by ensuring that parental consent is taken where necessary. The focus must be on the implementation of approved AI applications in the planning of lessons and their availability without uncontrolled utilization, which will lead to unethical practices and bias. 187 Journal of Education and Training Studies Vol. 14, No.

  generalrecommendationsevidence 5/5
  Keywords: must education based necessary professional basic including planning inclusive digital modules district support technologies tools
• READINESS OF ELEMENTARY TEACHERS ON THE USE OF ARTIFICIAL INTELLIGENCE: BASIS FOR PANDAI ACTION PLAN (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  Based on the findings of the study, the following research recommendations were suggested Expand PANDAI Model Validation Across Diverse Contexts Future studies should explore the applicability and effectiveness of the PANDAI (Positive Attitude and Development through Artificial Intelligence) framework across various educational levels, regions, and subject areas. Comparative studies could assess its impact on teacher motivation, instructional innovation, and student outcomes. 1. Longitudinal Studies on AI Readiness and TPACK Growth Given the strong correlation between TPACK and AI readiness, longitudinal research is recommended to track how professional development, policy changes, and technological access influence teachers’ growth in both domains over time. 2. Investigate Barriers to AI Integration Among Less Experienced Educators Since the current sample primarily included veteran teachers with advanced degrees, future research should examine the readiness and challenges faced by early-career educators or those without graduate-level training. This could inform differentiated support strategies. 3. Design and Test AI-Enhanced TPACK Training Modules Researchers should develop and evaluate targeted training programs that integrate AI tools into TPACK-based instructional design. Experimental studies could measure changes teacher competence, confidence, and classroom implementation. 4. Explore Student Perspectives on AI-Infused Pedagogy To complement teacherfocused findings, future research should investigate how students perceive and respond to AI-enhanced learning environments. This could provide insights into engagement, equity, and ethical considerations.

  generalrecommendationsevidence 5/5
  Keywords: tpack future teacher readiness training based pandai across explore development instructional student longitudinal growth changes
• Teacher Preparedness for AI-Integrated Classrooms in Jammu District of Jammu and Kashmir: Challenges and Professional Development Needs (2026) · International Journal For Multidisciplinary Research · doi

  Based on the findings of the study, the following recommendations are proposed: 1. Educational institutions should strengthen digital infrastructure, particularly in rural schools. 2. Continuous professional development programs focusing on AI integration should be organized for teachers. 3. Ethical guidelines regarding AI usage, plagiarism, and data privacy should be developed and implemented. 4. Teacher education programs should include AI literacy and digital pedagogy components. 5. Institutions should establish collaborative professional learning communities and peer mentoring systems. 6. Context-sensitive training programs should be designed for teachers working in resource-constrained settings. 7. Policymakers should develop comprehensive frameworks supporting responsible and inclusive AI integration in education.

  generalrecommendationsevidence 5/5
  Keywords: programs institutions digital professional integration teachers education based following recommendations proposed educational strengthen infrastructure particularly
• Generative AI in pre-service EFL/ESL teacher education: A systematic review of empirical studies (2026) · Journal for the Education of Gifted Young Scientists · doi

  This review highlights several directions for future research. First, more geographically diverse studies are needed, as current research remains concentrated in Asian contexts. Expanding research across different educational systems would provide a more comprehensive understanding of how GenAI is integrated in teacher education globally. Second, future research should move beyond perception-based studies toward more practice-oriented and longitudinal investigations. In particular, classroom-based and practicum-focused studies could provide deeper insights into how GenAI influences instructional decision-making and teaching effectiveness over time. Greater use of process- oriented data, such as AI interaction data, teaching artifacts, and performance-based measures, would also strengthen the empirical evidence base. Third, future studies should explore a wider range of GenAI tools beyond dominant large language models, including multimodal tools that may better support diverse language teaching needs. Comparative studies may also help clarify how different GenAI tools shape pre-service teachers’ instructional practices. Finally, regarding research themes and teacher development (RQ3), future research should further examine how engagement with GenAI shapes pre-service teachers’ cognition, pedagogical practices, and professional development in more integrated ways. Greater attention to these interconnections may help develop a more holistic understanding of teacher learning with GenAI.

  generalrecommendationsevidence 5/5
  Keywords: genai future teacher based teaching tools diverse different provide understanding integrated beyond oriented instructional greater
• A comparative study of AI readiness in language teacher education in the Global South (2026) · Discover Education · doi

  The study identifies ethical concerns, policy gaps, and limited training as persistent challenges to AI integration in language teacher education. The study notes that the rapid rise of AI has outpaced educational policies. The study highlights the need for modular training, institutional readiness benchmarks, and localized policy reform to address the challenges of AI integration in language teacher education.

  generalstated challengesevidence 5/5
  Keywords: study identifies ethical concerns policy gaps limited training
• Creativity and writing with generative artificial intelligence in the master’s degree in teacher training (2025) · Frontiers in Education · cited 6× · doi

  The study identifies the challenge of introducing and integrating GenAI into established teaching activities. The research also highlights the need for teachers to develop pedagogical strategies for using AI in the classroom. The study notes the importance of addressing ethical considerations and the potential misuse of Artificial Intelligence, particularly in relation to intellectual property.

  generalstated challengesevidence 5/5
  Keywords: study identifies challenge introducing integrating genai established teaching

Questions about this gap