Why media education in the age of generative AI should cultivate historical understanding, critical inquiry, creative judgment, and responsible authorship.
I approach teaching film and media as the development of judgment: learning not only how media are made or how theories describe them, but how to look closely, ask better questions, make deliberate choices, and understand the consequences of those choices.
Whether students are analyzing a film made decades ago or experimenting with generative artificial intelligence, I want them to move beyond passive consumption and technical proficiency toward intentional seeing, critical interpretation, and meaningful authorship.
My teaching has developed across film and media studies, communication, creative production, emerging technologies, and higher education. Across these settings, my central commitment has remained consistent: students should understand media simultaneously as cultural objects, technological systems, forms of expression, and opportunities for purposeful human agency.
Connecting History, Theory, and Practice
I do not treat film history, media theory, and creative practice as separate domains. Students understand each more deeply when they encounter them in relation to one another.
Historical knowledge gives contemporary media context. Theory provides conceptual language for interpreting what technologies and cultural forms make possible. Practice places those ideas under pressure by requiring students to make choices themselves.
A course in film history, for example, should do more than establish chronology. It should help students understand why particular forms became possible at particular moments and how technological, cultural, industrial, and aesthetic changes shaped them.
Similarly, a production course should do more than teach students how to operate tools. Students should understand why they are making particular formal decisions, what those decisions communicate, and what traditions they enter into or challenge when they make them.
My own scholarship has reinforced this approach. My doctoral research combined critical analysis of cinematic realism with a substantial practice-based film project. That experience strengthened my conviction that making can function as a mode of inquiry.
When students create media, they encounter theoretical questions materially: where to position a viewer, what to include or exclude, how duration changes perception, how editing constructs relationships, and how representational choices carry cultural and ethical consequences.
The same principle guides my teaching of emerging media today.
Teaching Emerging and Generative Media
Generative AI creates an unusual pedagogical challenge because the technology can make sophisticated outputs appear easy.
A student can produce an impressive image or video within minutes without necessarily understanding why it works, what it communicates, or what role the student has actually played in creating it.
My teaching therefore emphasizes the distinction between generation and authorship.
I ask students to think of generative systems not as substitutes for creative thought but as environments in which human judgment becomes more important.
Students must learn to articulate intention, evaluate alternatives, identify weaknesses, revise decisions, and assemble generated material into something coherent and purposeful.
The educational objective is not simply successful output.
It is the development of a student who can explain what they intended, why they made particular choices, what changed during the process, and what responsibility they retain for the resulting work.
This principle informs my work in AI filmmaking and my development of AI Cinematic Realism (AICR) as both a research framework and a pedagogy. My broader research agenda examines how cinematic realism, authorship, and creative agency are being reconfigured in the post-camera era.
Rather than presenting generative AI as historically unprecedented, I situate it within longer histories of photography, animation, digital cinema, visual effects, and changing conceptions of cinematic authorship.
Students should encounter emerging technologies as developments that have histories, cultural assumptions, institutional contexts, and consequences—not simply as the newest collection of tools.
Critical Inquiry, Judgment, and Authorship
Critical inquiry, judgment, and authorship are closely related, but they are not interchangeable.
- Critical inquiry asks students to question, analyze, interpret, compare, and investigate.
- Judgment asks them to evaluate possibilities and make deliberate choices.
- Authorship asks them to take responsibility for what those choices ultimately become.
Together, these capacities form the center of how I think about media education.
An important purpose of teaching film and media is helping students develop a creative and intellectual voice of their own.
For me, creative voice does not mean teaching students to reproduce an instructor’s aesthetic preferences. It develops when students gain enough historical knowledge, critical vocabulary, technical understanding, and confidence to make choices they can genuinely defend.
I therefore value learning environments in which experimentation and critique reinforce one another.
Creative work benefits from iteration: making something, encountering its limitations, receiving thoughtful responses, reconsidering assumptions, and trying again.
Critique is most productive when it helps students articulate intention and evaluate whether a work actually communicates that intention rather than merely determining whether it conforms to a presumed model of correctness.
This process is especially important for students encountering unfamiliar technologies.
Emerging-media environments can reward confidence before understanding. I want learning spaces to create room for curiosity without requiring students to perform expertise they do not yet possess.
Students should be able to experiment, fail productively, question technologies, and change their minds.
Accessibility as a Teaching Practice
Accessibility is also part of how I think about teaching—not as an accommodation added after the intellectual work of a course has already been designed, but as part of thoughtful educational design from the beginning.
Clear organization, meaningful headings, accessible documents and media, captioning, understandable instructions, multiple ways of engaging with course material, and transparent expectations make learning environments more usable.
But accessibility is also intellectually connected to media studies itself.
Technologies structure participation. Interfaces privilege some forms of interaction over others. Design decisions determine who can perceive, navigate, interpret, and contribute.
Media technologies are also social arrangements: their design shapes who can participate, how, and under what assumptions.
Thinking critically about accessibility therefore reinforces a broader lesson central to media education: design choices carry cultural, social, and ethical consequences.
That perspective also informs my teaching of AI.
Responsible engagement with emerging technologies requires considering not only what systems can do, but whom they serve, whom they exclude, what forms of labor and representation they depend upon, and when their use is appropriate.
Teaching Students to Navigate Change
The tools students encounter will keep evolving—often faster than any course can be redesigned around them.
For that reason, I do not believe the lasting purpose of media education can be mastery of a particular platform or software package.
Students need durable intellectual capacities: historical understanding, close analysis, creative judgment, ethical reasoning, research skills, adaptability, and the ability to connect technological change to larger cultural questions.
This is particularly urgent in an age of artificial intelligence.
If education concentrates only on teaching students how to operate today’s systems, much of that knowledge may quickly become obsolete.
If students instead learn how to evaluate technologies, understand their histories, interrogate their assumptions, and make intentional choices with them, they are better prepared for technologies that do not yet exist.
My role as a teacher is therefore not to position myself as the final authority on rapidly changing media.
It is to provide students with frameworks, histories, methods, and opportunities for practice that allow them to become increasingly independent thinkers and makers.
Film and media education is especially well suited to this task because it has always asked students to negotiate relationships among technology, culture, representation, creativity, and human experience.
Generative AI makes those relationships more visible.
It does not replace them.
Teaching Across Film, Media, and AI
My teaching experience spans more than two decades across film and media studies, communication, creative production, psychology, digital media, and emerging technologies.
At the University of the Philippines Film Institute, where I served as a tenured Assistant Professor of Film and Media Studies, I taught undergraduate and graduate courses in film history, theory, criticism, historical and critical research methods, directing, documentary production, experimental film, media literacy, and communication and media theory.
At Hong Kong Baptist University, I taught moving-image studies and supported courses in film history, European cinema, film and media arts, and communication research methods.
More recently, my teaching and curriculum development have expanded into generative AI, AI filmmaking, human–AI collaboration, and responsible adoption. At Bellevue College Continuing Education, this includes Generative AI: Practical and Ethical Use and AI Filmmaking and Creative Video Generation. I have also co-developed AI Essentials in Education (AI-Ed), a statewide AI literacy curriculum for Washington’s community and technical college system.
Across these contexts, the technologies and subjects change, but the underlying educational purpose remains remarkably consistent.
Students need opportunities to connect knowledge with judgment.
They need to understand not only what media can do, but why particular choices matter.
And they need to become capable of taking responsibility for the meanings they create.
From Philosophy to Course Design
These principles also inform my open syllabus, AI Cinematic Realism (AICR): Film Theory, Synthetic Media, and the Post-Camera Image, designed as an upper-division undergraduate or graduate seminar.
The course places generative cinema in dialogue with classical film theory, post-photographic media, authorship, ethics, and creative practice. Students move from Bazin and Kracauer through digital and synthetic media before applying AICR to questions of perceptual realism, worldbuilding, authorship, disclosure, and cinematic meaning. The course culminates in substantial critical or creative work rather than simple technical demonstration.
Ultimately, I want students to leave my courses able to do more than explain a theory, identify a historical development, or produce a technically successful piece of media.
I want them to be able to say:
I understand what I am trying to do. I can explain the choices I made. I can evaluate their consequences. And I can take responsibility for the work I have authored.
For me, that is where critical inquiry, judgment, and authorship meet.
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