Exploring Generative AI Readiness among Saudi EFL University Teachers: A TPACK-Informed Multi-Institutional Study
This exploratory study of 96 Saudi EFL university teachers reveals moderate self-reported readiness for generative AI integration, highlighting significant institutional disparities, a lack of correlation between prior training and most readiness dimensions, and key barriers such as academic integrity concerns and insufficient practical support.
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Language teachers have long been the architects of communication, guiding students through the intricate rules of grammar, the nuances of pronunciation, and the cultural contexts that give words meaning. Now, a new force has entered the classroom: generative artificial intelligence. These are computer systems capable of creating text, images, and ideas that mimic human output, offering to help teachers draft lessons, correct student work, or generate practice materials. But this technology brings a complex set of questions. It is not enough for a teacher to simply know how to turn a machine on; they must understand when it is appropriate to use, how to spot errors or cultural mismatches in the machine's output, and how to navigate the ethical minefields of academic honesty and data privacy. In Saudi Arabia, where English is a vital subject for global connection, educators are facing the challenge of integrating these powerful tools into their daily practice without losing the human element of teaching.
A recent study set out to map the landscape of this transition. Researchers surveyed ninety-six English teachers from five different universities across Saudi Arabia to understand their readiness to use generative artificial intelligence. The investigation was built on a framework that views teaching as a blend of three essential skills: knowing the subject matter, understanding how to teach it, and mastering the technology used in the classroom. The researchers wanted to see if these teachers felt confident in their technical skills, their ability to weave the technology into lessons, their awareness of cultural and ethical issues, and the support they received from their institutions. They also asked the teachers to describe the biggest obstacles standing in their way and what kind of help they needed to move forward.
The results revealed a picture of cautious optimism mixed with significant uncertainty. On average, the teachers reported a moderate level of readiness. They were not rejecting the technology, nor were they fully confident in their ability to wield it effectively. The most comfortable area for the teachers was the technical side; they felt they could set up and use common tools like chatbots. They were also reasonably aware of the ethical concerns, such as data privacy. However, their confidence dropped when the questions turned to the classroom itself. Teachers felt less sure about how to monitor students using these tools outside of class, how to ensure the content generated by the machines was culturally appropriate for Saudi learners, or how to integrate the technology into their daily teaching routines in a meaningful way.
One of the most striking findings was that having received formal training in artificial intelligence did not automatically make a teacher feel more ready to use it. The study found no clear link between prior training and higher scores in technical knowledge, lesson planning, or classroom practice. This suggests that simply attending a workshop or completing a course is not enough; the quality, depth, and practical focus of that training matter far more than the fact that it happened. The only area where training seemed to make a difference was in the teachers' perception of institutional support, perhaps because those who had trained were more attuned to what they were missing or what they needed from their universities.
Gender played a more visible role in the results. Male teachers reported higher levels of readiness than female teachers across several areas, but the gap was widest regarding institutional support. Men felt their universities were more supportive of their efforts to use artificial intelligence than women did. This suggests that the environment in which a teacher works—whether they feel encouraged, resourced, and guided—might be just as important as their personal skills. The study also looked at differences between the five universities involved. While one university showed a higher average readiness score than another, the differences were small and the groups of teachers from each school were uneven in size, meaning these findings are preliminary and should be viewed with care.
When the researchers asked the teachers to describe the biggest barriers to using artificial intelligence, the answers were clear and practical. The most frequent concern was academic integrity, specifically the fear that students would misuse the tools to submit work that was not their own. Following closely behind were issues with infrastructure, such as unreliable internet or a lack of access to the necessary software. Teachers also expressed a strong desire for more practical, hands-on training. They did not just want to know what the technology was; they wanted to know how to build lessons around it, how to create materials that worked, and how to assess student work in a world where machines can write essays.
The study also uncovered a deep interconnectedness between the different skills teachers need. The data showed that teachers who felt strong in one area, such as technical knowledge, tended to feel strong in others, like lesson planning or ethical judgment. This suggests that these skills are not isolated islands but part of a larger, unified capability. However, the researchers noted that the survey tool itself might need further testing to ensure it measures these distinct skills accurately, as the lines between them can sometimes blur.
Ultimately, this research paints a portrait of a profession in transition. Saudi English teachers are not afraid of artificial intelligence, but they are waiting for the right conditions to embrace it fully. They need more than just access to software; they need a supportive environment that addresses their concerns about academic honesty, provides reliable technology, and offers training that goes beyond the basics to show them how to use these tools responsibly and effectively. The path forward is not about replacing the teacher with the machine, but about equipping the teacher with the knowledge and support to guide students through a new era of learning.
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