#leadership #teaching #genAI #enablement #ai-literacy # My teaching philosophy **May 2026** ## Teaching as leadership I believe that excellent teaching demonstrates leadership worth emulating. As a teacher, I see my role as demonstrating preparedness, engagement, empathy, a willingness to experiment, a commitment to equity, and the provision of meaningful feedback. This belief has been shaped by four years teaching internationally and four and a half years of teaching pre-service and in-service K–12 teachers in the United States. It has also been influenced by many years of experience creating educational products in higher education, international organizations, and the private sector. ## Principles for learning-centered teaching My approach to teaching and classroom management is guided by three principles: (1) learner-centered design, (2) authentic learning experiences, and (3) meaningful reflection and feedback. Fundamentally, I aim to create learning environments that embrace student goals alongside my own and those of the institution. This orientation reflects my care for empowering learners to create work that extends beyond the classroom. I always hope that learners can produce something that can be used for an interview, their professional practice, or future study. This said, when I think and practice learning design, I seek to build environments grounded in partnerships to create opportunities for collaboration, feedback, reflection, and responsive adjustments to the learning experience. ## Teaching in partnership with AI The nature of partnerships in teaching is changing. When I was last teaching pre-service and in-service K–12 teachers, all partnerships were human-driven. Since early 2023, however, emerging human–AI partnerships have begun to reshape how teaching and learning can occur. As a result, a fundamental shift in my teaching philosophy is the belief that ==teachers and students need to experiment together with Artificial Intelligence (AI) and reshape the classroom experience.== At the same time, I continue to believe it is essential to motivate learners by connecting content to their goals and allowing them to make meaningful choices in their learning journey. For this reason, I often gravitate toward project-based learning. This approach allows students to engage in AI-partnered work, where they can experience both the benefits and the limitations of that collaboration. This is where genuine challenges emerge: 1) what are the right partnerships, 2) what should be the limits of AI partnership, and 3) what are the psychological and/or cognitive problems that can arise for learners in human-AI partnership? These are questions that have wrestled with and admire educational researchers who take on. In recognizing AI as a learning partner, I believe it is essential to make AI literacy ([[AI#AI Literacy]]) a goal of teaching. AI presents opportunities to enable new practices, accelerate human learning, and support new forms of interaction. To me, the emergence of AI is comparable to the rise of the Internet in the 1990s. Just like we did in the 1990s and 2000s, the classroom should be a place for learners to practice constructing foundational knowledge *with AI* and importantly *of AI*. For example, answering what it is, what it can do, how it works, how it is perceived, and ethical considerations with it across domains. Students should be supported in answering not only how to use AI, but when to begin using it and when to stop. ## Teaching as community and change Teaching is a form of leadership, but it is also an act of community-building. As in most professional contexts, communities grounded in mutual respect, trust, empathy, and high expectations create the conditions for deep learning and new possibilities. Across my teaching experiences, I have taught more than 1,000 students in China and more than 500 pre-service and in-service K-12 teachers in the United States. In professional settings, I have also mentored junior and mid-career staff and helped others achieve their goals in the pursuit of professional development opportunities. Within higher education, I have contributed to and helped create multiple communities. Notably, during my time at George Washington University, I established the Generative AI in Teaching (GAIT) community, bringing together faculty from across the institution that explored questions on AI use (both practically and ethically) and developed recommendations for the use of AI in teaching practice. I also convened an AI Staff Working Group, collaborating with central library staff to better understand and address community needs related to AI. These efforts reflect my commitment to leadership in teaching through collaboration, community, and shared inquiry. ## Teaching excellence **Excellent teaching should never be static.** It evolves with experience, incorporates perspectives beyond one’s domain, responds to research, and is occasionally reshaped by technological change. Artificial Intelligence represents a profound shift in communication and access to information. It has shifted the challenge of study and research from **finding** information, including an answer, to a new problem of **verifying** the information and answer received. This is a challenge affecting teaching and learning that will continue well into the future. Because of this, learning design and teaching needs to change and adapt to the needs of learners across all ages, and yes, what the market demands. Ultimately, I believe teaching excellence involves providing a model that encourage others to learn, grow, and strive to be better.