Emerging Methodologies for Educational Technology
An Exploration of Contemporary Instructional Design Methodologies
I. Introduction and Objective
Introduction
Educators have historically used different mixed medias for the purpose of providing the learner with tools they need to transfer knowledge to understanding. This essay explores how educators are adapting their teaching methodologies in response to new AI tools, such as digital twins and interactive avatars. With technology, it’s a fine balance of what you gain (ease of creating material, scalability, multi-language) and what you give up (interactivity, learner autonomy, human touch).
B. Objective
As an educator and entrepreneur in this space, I am excited to start the conversation about the different tools and methods that we use today, and a projected future state of where I think the puck is headed.
I use my own journey building Launch Academy as a case study in creating educational content to examine how these tools are used to design learning resources, structure activities, and reshape teacher–student interaction. The goal is to offer practical insights for educators who wish to experiment with AI in a thoughtful, ethical, and learner-centred way and to compare and contrast the different modalities through a matrix of factors.
Throughout the course of only a year, I have seen a personal evolution along the spectrum of analog to digital in my teaching pedagogy. I started by using only a textbook and a slide deck, which evolved into recording video lessons for YouTube, then using a digital twin to create these lessons, and now am focused on creating an interactive avatar to guide students through the material.
There are gains and tradeoffs for each modality, but in my opinion, interactive avatars are an exciting emerging tool for teachers to be able to create educational materials that are personalized, localized, and scalable.
A. In-Person Learning
In-person learning is the oldest and most established instructional modality, relying on a teacher delivering content directly to a group of students in a shared physical space. This one-to-many method has existed for more than 2,500 years and is still today the predominant modality in society for learning, especially for younger kids.
The technology required for this format is minimal: a chalkboard or whiteboard, printed materials, and more recently, projectors or slide presentations. Because the teacher controls pacing, explanations, and real-time adjustments, students benefit from immediate clarification and spontaneous discussion.
However, research shows that traditional lecture-based learning—where students passively listen—results in low retention, with students recalling only 5–20% of the material shortly after the lesson.
According to Harvard professor Eric Mazur, the lecture is the most popular but least effective form of teaching. Interactive learners who take on a more active role in learning retain 3x as much information than passive listeners. This is especially true for female students! The person who learns the most in any classroom is the teacher.
In contrast, incorporating active-learning elements (such as discussion, problem-solving, and peer collaboration) can increase retention to 50–70%, and students are up to three times more likely to correctly apply what they learned compared to passive instruction. “I see, I forget. I hear, I remember. I do, I understand.”
Taking active learning seriously means revamping the entire teaching enterprise. Eric Mazur sees education as a two-step process: information transfer, and assimilating that information. Traditionally students attend a lecture and then do homework on their own. But by adopting an active learning pedagogy, students are encouraged to come to class having read or watched the course material. Together as a group they discuss, debate, and make sense of the information.
Despite its limitations in scalability, traditional in-person learning remains powerful because of its built-in human connection, opportunities for socialization, and the teacher’s ability to adapt responsively to student needs.
With the adoption of large language models, teachers are now able to create lesson plans and brainstorm activities easily.
B. Video-Based Learning
Video-based learning represents a major shift from traditional, ephemeral in-person lessons to content that can be replayed, shared, and scaled to large audiences. This modality typically requires a camera, microphone, screen-recording software, and an editing tool—though AI has dramatically lowered the barrier to entry by enabling creators to generate lessons using digital twins or automated narration.
Video lessons excel in scalability, reusability, and language adaptability, allowing learners to watch with subtitles or translations and revisit difficult concepts at their own pace. However, the experience is fundamentally passive: students retain far less from video than from active learning environments unless interactive elements (like reflection pauses, embedded quizzes, or guided practice) are intentionally added. Studies show that learners often recall only 20–40% of video content after a single viewing, and retention drops sharply without follow‑up practice. Still, video empowers educators to reach global learners with consistent, well‑structured material—making it invaluable for foundational instruction and flipped-classroom models.
Case Study: Khan Academy
C. Interactive Avatar–Based Learning
Interactive avatar–based learning is an emerging modality that blends the structure of video lessons with the adaptability of in-person instruction. Instead of passively watching, learners interact with a responsive AI instructor that can pause, ask questions, assess understanding, adjust pacing, and branch into different pathways based on interests or errors.
This modality requires more advanced technology—AI-driven avatars, natural language processing, branching logic tools, and generative media platforms—but it offers a powerful level of personalization, localization, and learner autonomy that traditional formats cannot match.
Early studies in adaptive learning systems suggest that interactive, feedback-rich environments can increase retention to 60–80%, especially when learners actively make decisions or demonstrate understanding during the lesson. The unknown factor is emotional engagement: some students may find avatars engaging, while others may miss human warmth or be sensitive to uncanny design elements. Still, for scalable, multilingual, adaptive instruction, interactive avatars represent one of the most promising frontiers in educational technology.
Case Study: Zero University
III. Cross-Modal Comparison
Factors
In-person Class
Recorded Video
Interactive Avatar
Scalability
LOW
HIGH
HIGH
Language Adaptability
LOW
MEDIUM
HIGH
Interactivity
HIGH
LOW
HIGH
Personalization
MEDIUM
LOW
HIGH
Knowledge Base
MEDIUM
MEDIUM
HIGH
Learner Autonomy
LOW
MEDIUM
HIGH
Reusability
LOW
HIGH
HIGH
Collaborative
MEDIUM
LOW
MEDIUM
Cost to Learner
MEDIUM
LOW
LOW
Teacher Manpower
HIGH
HIGH
LOW
The comparisons above are based on a couple assumptions.
IV. Case Study: Launch Academy
A. Origin
I am a technologist by background, not an educator. I fell into teaching STEAM to children a couple of years ago.
My son and daughter love playing video games. I am a visual designer and a developer, so I loved the idea of us building a game together. In 2023 we started creating small projects together in Scratch. The kids loved it and I was blown away by their creativity and problem solving.
There were so many opportunities to learn the basics of Computer Science and Visual Design while we created little games together in a fun and accessible way. I thought how cool would it be if we could create a small group of their peers and learn together. This is how Launch Academy was born.
B. Initial Challenges & Instructional Gaps
Every week, a small group of 7 students gathered after school. The lectures that I created on comparison operators, data types and the binary number system were met with blank stares from tired kids who had just spent the whole day at school. As soon as they had an iPad in front of them, all attention went out the window and I lost them to YouTube.
Luckily for me, I was concurrently taking Introduction to Instructional Design. This helped me to understand the learner experience, structure my lessons in a way that would transfer knowledge to understanding, and drove the decisions I made around the supporting educational materials.
Launch Academy's Mission
A. In-Person Learning
When I started Launch Academy in 2024, I began creating my teaching materials in a very traditional way. I gathered a small group of students together once a week for one hour, gave a 10‑minute lecture of the day's topic with a supporting slide show, gave a 10‑minute demo of the skill I wanted them to learn, and then gave them time to complete the exercise on their own devices while I checked in with them individually on their progress.
From a technical standpoint, this was the least complicated. I spent a couple of hours researching Scratch’s educator handbook, creating the slides, practicing the demo, and then delivering the content. The only tool I used was Google Slides. Although the content of the lesson was pre‑planned, there was still interactivity because the children could ask questions and receive feedback.
One of the biggest benefits of this format was peer interaction. Each semester we hosted a game jam where students formed teams and collaborated on creating a game aligned to a specific theme.
According to Google’s research from the Aristotle Project, modern work is increasingly team‑based. To prepare my students for the future, I needed to focus not only on how they work individually but also on how they work together.
To support this, students presented their final projects to the class and engaged in structured peer feedback. Every suggestion was welcome; there were no wrong answers. After hearing the group’s reflections, the presenter summarized the feedback and identified actionable revisions.
Giving children structured opportunities to exchange feedback, hear diverse perspectives, and take ownership of their work proved far more motivating than any lecture. Learning is a social experience.
Another method I incorporated was the “See–Think–Wonder” routine when introducing a new game. Based on Harvard’s Project Zero, these routines help children organize their thoughts and process new stimuli.
Tech Stack: Google Slides
B. Video-Based Learning
In August of 2025, I shifted to a recorded video format on YouTube to teach children how to use AI to create digital artifacts.
The primary benefit was scalability. I could not enroll more than seven children in my in‑person class, and those lessons were ephemeral—there was no way to rewatch or share them. Video allowed global access, asynchronous learning, and multilingual subtitles. Families in Spain, where I was based, often worried about English proficiency; subtitles alleviated that concern.
I experimented with recording myself and my screen. Although the format expanded my audience, I struggled with being on camera and delaying filming when the setup didn’t feel right.
Using Descript helped me combine webcam footage and screen recordings. I recorded lessons as though teaching live and then edited out extraneous segments. However, I was frustrated that updating lessons required re‑filming and that content risked becoming outdated as new models and tools emerged.
Tech Stack: ChatGPT (ideation and scripting), Descript (recording and editing), YouTube (distribution)
In October 2025, Digital Twins transformed the workflow. I trained an AI avatar to deliver my tutorials. This eliminated filming anxiety—my digital twin was always “camera‑ready.” Lessons became scalable, multilingual, and easy to iterate.
I used HeyGen for avatar generation and Descript for editing. While effective, this approach was not without challenges. Some viewers felt it lacked the human touch, and occasional uncanny‑valley lip‑sync issues broke immersion. I mitigated this by emphasizing supporting visuals instead of talking‑head footage.
YouTube tutorials are excellent for quick procedural learning: students can replicate steps precisely. Some children produced impressive projects this way—but struggled to begin independent creations from scratch.
A YouTube coding tutorial is similar to the “butterfly method” in fraction operations: it teaches procedural fluency without guaranteeing conceptual understanding. Authentic understanding is rooted in direct experience, iterative practice, and contextual application.
Tech Stack: ChatGPT (ideation and scripting), HeyGen (avatars), Descript (editing), Google Flow (visuals)
C. Interactive Avatar–Based Learning
As of November 2025, it became possible to create interactive digital avatars. These avatars enable dynamic, adaptive learning experiences: pausing for learner actions, testing comprehension, branching by interest, and giving tailored next steps.
I find this profoundly exciting. Instead of static tutorials, lessons become responsive conversations. Teachers can scaffold learning while allowing the avatar to adjust pacing and path.
What remains unknown is how children will emotionally respond to this modality and whether the novelty will enhance or hinder engagement.
Tech Stack: ChatGPT (ideation and scripting), HeyGen (avatars)
AJ Juliani
A. Adopt Blended Modality Ecosystems
Each modality, whether in‑person, video‑based, or avatar‑mediated, offers powerful strengths but also inherent limitations. A blended learning ecosystem allows educators to combine these strengths intentionally:
In‑person time can be devoted to social learning, collaboration, discourse, and creativity.
Video lessons can support foundational knowledge acquisition, allowing learners to pause, replay, and revisit content independently.
Interactive avatars can personalize pathways, offering adaptive support and multilingual access.
By distributing instructional goals across modalities, teachers can optimize cognitive load, increase accessibility, and promote deeper understanding.
B. Use Evidence‑Based Pedagogical Frameworks
The rise of AI tools makes instructional design frameworks more important, not less. Tools should be applied within the structure of:
Understanding by Design (UbD) for backwards planning
Active Learning to move learners from passive watching to doing
Cognitive Load Theory to avoid overwhelm
Making Thinking Visible routines for metacognition
Growth Mindset messaging to support perseverance
These frameworks ensure that technology enhances, not replaces, sound pedagogy.
C. Center Human Connection—Even in AI‑Enhanced Environments
AI can scale access, personalize instruction, and automate routine tasks, but it cannot replace the fundamental human experience of learning together. Educators should design materials that:
maintain opportunities for peer learning
create safe spaces for mistake‑making and iteration
support emotional engagement and belonging
Technology amplifies the teacher’s role—it should never diminish it.
VII. Takeaways and Conclusion
The rapid emergence of new educational modalities, ranging from centuries‑old in‑person instruction to interactive AI‑driven avatars, signals a pivotal moment in the evolution of teaching and learning. Each modality offers unique pedagogical affordances, and the challenge for educators is learning how to orchestrate them in ways that maximize accessibility, engagement, and authentic understanding.
The Launch Academy case study demonstrates that even within a single year, my toolkit expanded dramatically. What began as a set of simple slide‑based lessons evolved into a multimodal ecosystem of videos, digital twins, and interactive avatars. This transformation was not driven by novelty, but by a desire to better meet learners’ needs.
AI‑enhanced tools have the potential to democratize access to high‑quality learning materials, provide multilingual pathways, and personalize instruction at a scale unimaginable in traditional classrooms. Yet the heart of learning remains human. Meaningful education depends on relationships, feedback, socialization, and the psychological safety to take intellectual risks.
Moving forward, educators must pair emerging technological tools with evidence‑based instructional frameworks. AI can relieve teachers of production burdens, but it cannot replicate the empathy, nuance, and relational wisdom that define great teaching. The opportunity ahead lies in designing learning experiences that leverage the strengths of each modality, while ensuring that technology remains in service of human flourishing.
As both an educator and an educational entrepreneur, I am inspired by what is possible. The future of learning will not be characterized by a single methodology, but by flexible, adaptive ecosystems that empower teachers and learners alike. When thoughtfully integrated, AI tools can help children develop the skills that matter most: imagination, resilience, collaboration, and the confidence to create.
© EdTechEvolution 2025.