AI Literacy for Teachers

Empowering Educators through AI Literacy
Develop essential skills to integrate AI effectively, critically, and intentionally into your teaching practices while understanding its profound impact on human agency, wellbeing, and academic integrity.
Integrate AI Intentionally
Develop the essential skills to weave AI tools into your teaching practices effectively, critically, and with clear purpose.
Human Agency & Wellbeing
Critically examine how AI impacts the human experience, ensuring that technology supports both teacher agency and student wellbeing.
Pedagogical & Academic Integrity
Navigate the intersection of innovative pedagogical practices and the preservation of academic integrity in an AI-enhanced classroom.
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AI Literacy
Among the many definitions of AI literacy, I find the definition by Digital Promise to be relevant and comprehensive.  I appreciate its focus on human-centeredness and acknowledgement of fast-paced changes in AI development. 
"AI literacy is a set of foundational skills and competencies that enable individuals to understand how AI works, responsibly evaluate AI systems, and use AI effectively as a human-centered tool across various contexts, including learning, work, and civic applications, while adapting to its ongoing evolution." 
AI Literacy Training for Teachers
Effective AI literacy training equips educators with the essential knowledge and skills to navigate artificial intelligence tools with intention, responsibility, and pedagogical success.
Training should be discipline-specific while maintaining common foundational principles.
Programs must require the integration of technical, ethical, socio-emotional, and pedagogical dimensions.
Implementation benefits from collaborative, campus-wide engagement and the development of a shared institutional language.
Professional development should prioritize intentionality, human agency, equity, and pedagogical integrity.
Educators must commit to ongoing adaptation as new technologies continue to evolve.
Educator literacy should actively inform the future of edtech development.


Upcoming Academic Engagements
We are taking a break due to the current situation in the Gulf. 
Past Events (Academic Year 2025-2026)
Panel Discussion: AI in Higher Education – Curriculum Transformation, Research Innovation, and Ethical Governance. Road to AI Impact Summit 2026, organized by Symbiosis International University Dubai  in collaboration with the Indian Embassy in the UAE, 12 February 2026. 
Plenary session: AI literacy across the curriculum. Online Pedagogy: Remote Teaching and Learning Strategies in the 21st Century. Ministry of Higher Education and Scientific Research University AbouBekr Belkaid, Tlemcen, Algeria, 4 February 2026.
Invited Talk: Operationalizing AI literacy for language teachers. Applied Linguistics and Language Teaching Forum, Abu Dhabi, UAE, 31 January 2026 .
Invited Talk: AI literacy across the curriculum. AI Week. American University of Sharjah, UAE, 28 January 2026.
Keynote: Student-Centered Support in the AI Age: AI Companions, Counseling, and Human Connection. The 6th ADU School Counselors Forum: Innovating Student Support: The Future of School Counseling in the Age of AI. Abu Dhabi University-Al Ain Campus, UAE, 15 January 2026.
AI-powered tools for academic reading and research. Faculty Development Program, Manav Rachna University, India, 25 November 2025.
Panel Discussion: Reclaiming learning in the age of AI. Faculty 360° 2025 Summit. Zayed University, UAE, 21 November 2025.
Cultivating Trust, Agency, and Wellbeing in AI-Driven Academia. Faculty 360° 2025 Summit. Zayed University, UAE, 21 November 2025.
Panel Discussion: Revolutionizing curriculum design with AI. The 2nd ADU International Conference on Education - Advancing Teaching Practices. Abu Dhabi University-Al Ain Campus, UAE, 1-2 October 2025.
The leader’s role in AI innovation. The 2nd ADU International Conference on Education - Advancing Teaching Practices. Abu Dhabi University-Al Ain Campus, UAE, 1-2 October 2025.
Articles
Explore my latest articles which address a range of critical issues concerning AI literacy for teachers.
Review of "AI Ethics: Policy Guidance for Language Education":

It's been a busy start to 2026, so I was really excited to sit down and spend some focused time on catching up with academic research and reading. One of the things I read this week was "AI Ethics: Policy Guidance for Language Education", authored and shared by TIRF - The International Research Foundation for English Language Education on LinkedIn just the other day. There is a clear need for practical frameworks for ethical AI use in language learning and teaching, and this guidance paper delivers on that front, to some extent, with concrete examples and excerpts from policies various institutions are using. For example, I found the excerpt from British Council rather useful. The section on citing AI sources is also excellent, and the discussion on plagiarism and detection is reasonably comprehensive. Those of us who remember Chomsky will appreciate a quote from him that includes the word “plagiarism”.

Despite the title, though, I feel this paper isn't really about language education specifically. It reads more like general guidance with a slim section on language skills that sticks to traditional skills. If you're looking for insights on how AI use and AI policies impact English language acquisition, intercultural communication, ESL writing instruction, or pronunciation practice (among other English language education topics), you may be disappointed.

Most references are from 2023 and 2024, with only three from 2025. In AI, that seems like an eternity. A lot must have changed in the past year, and that doesn't seem to be reflected here. AI literacy for teachers gets mentioned a few times (questions on p. 8, more on p. 24) but never gets the focused treatment it deserves. Given that AI literacy is foundational to everything else, this feels like a missed opportunity.

Overall, it's a useful starting point for institutional policy discussions, but language educators will need to look elsewhere for discipline-specific practical guidance.
LinkedInEditors
Your Pedagogical Framework Should Ground Your Choices
At my recent conference presentation, a teacher raised two questions I've heard a number of times now: "How do we keep up with all these AI tools? How do we know which ones to choose?" The questions took me back to 2023 when I was in Hong Kong and where anxiety due to the fear of missing out was pal
LinkedInEditors
When a Word Takes on a Whole New Life
In late 2020, Shari Dureshahwar Lughmani, a wonderful colleague and a true mentor who also happens to be a dear friend, invited me to co-author a chapter for an edited book on language teacher agency and identity. This was the beginning of an exciting journey as we joined a community of other writer
LinkedInEditors
Who Really Wrote This? Rethinking Authorship in the Age of AI
It was the summer of 2022 when I sat down to plan my research agenda for the coming academic year. Something had been bothering me: our students were producing summaries and paraphrases that were technically too good, especially given their current English proficiency levels.
File upload
A case study exploring AI and its impact on professional communication
Chigaeva-Heddad, S.I. (2025). Artificial Intelligence and its impact on professional communication: A case study. In Linguistics, Language Teaching, and Translation Studies: Current Issues and Research Perspectives (pp. 157-165). Chuvash State University, Cheboksary, Russia.

AI Terms Made Simple
This list is updated based on the topics I cover in my workshops and seminars. 
AI Bypassers
AI tools designed to rephrase or alter AI-generated text, with the specific goal of making it undetectable by AI-detection systems.
AI Humanizers
AI Humanizers are tools that modify AI-generated text to make it sound more natural and human-like, often used to avoid detection by AI detection systems.
AI Sycophancy
When language models echo, flatter, or agree with users—even if it means ignoring facts or contradicting themselves to gain approval.
Burstiness
Burstiness measures how much perplexity varies throughout a document, reflecting text flow. Human writing naturally varies between simple and complex sentences, creating rhythm. AI-generated content typically lacks this variation. AI text generators often produce lower burstiness scores, creating monotonous content with repetitive patterns.
Perplexity
Perplexity functions as "a surprise meter" or the opposite of predictability. Higher perplexity indicates text with unexpected words or sentence structures—typically human-authored content. Lower perplexity suggests more predictable text, likely AI-generated.
Let's Connect
Share Your Insights & Experiences
Join a growing community of educators and professionals passionate about AI literacy to exchange ideas and best practices.
Collaborate & Grow Together
Explore opportunities for joint projects, resource sharing, and professional development to advance AI literacy initiatives.
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