Rethinking the use of template for 3-D visualisation with technology
In the 13 Feb 2025 lesson, we tried using a template for visualisation with a project. Students are patiently trying. Again, different students have different needs, and I prepared videos for them so that they can use the template to "apply knowledge" to their own design, and the outcome was positive.
See facilitation plan
https://docs.google.com/document/d/1tGY4o68GLYVY5-QjPDIiyQDdr9XJnDFSQub71Cx8Mv8/edit?tab=t.0
I do not need to strain myself, and I can direct my instructions by just saying, Refer to my YouTube video #3 based on students' need. In a self-directed learning classroom with diverse needs of students, we have to create "agents" to help us. YouTube is one "teacher-directed" agent, and Chat GPT is a "self-directed agent. Because GPT cannot provide video based on students' outcomes, I am playing a uniquely human role as a teacher. And I asked Chat GPT what he thinks. Below is what my AI agents did for me, and I particularly like the concept of "higher order facilitation", where humans take the unique role of facilitating and letting AI take the machine's role of facilitation.
https://chatgpt.com/share/67c3e74d-597c-8010-b60e-c9dceae82987
AI-Augmented Teaching: Leveraging Instructional Agents for Self-Directed Learning
Reflections on the 13 February 2025 Lesson
In the 13 February 2025 lesson, we explored using a template for visualization within a project-based learning approach. The students demonstrated patience and persistence in applying the technique, despite their diverse learning needs. To scaffold their learning, I prepared instructional videos that enabled them to use the template to apply knowledge to their own designs. The outcome was positive, with students effectively engaging with the process at their own pace.
Facilitating Self-Directed Learning with Instructional Agents
A key realization from this experience is that teaching in a self-directed learning environment requires scalable facilitation tools. Instead of repeatedly delivering the same instructions, I directed students to my pre-recorded YouTube videos. For example, I could simply say, "Refer to my YouTube video #3 based on your needs," allowing students to access information as required.
In a self-directed learning (SDL) classroom, where students have diverse needs, teachers must create instructional agents to assist them. Two such agents I’ve integrated are:
YouTube as a Teacher-Directed Agent
Provides structured, pre-planned instruction that students can access independently.
Allows differentiation by letting students revisit explanations as needed.
Reduces the teacher’s cognitive load, enabling a focus on higher-order facilitation.
ChatGPT as a Self-Directed Agent
Supports contextualized inquiry by responding to students’ questions based on their unique reflections and design challenges.
Encourages metacognitive thinking, helping students articulate problems and generate possible solutions.
Cannot provide video demonstrations, reinforcing the unique role of the teacher.
The Evolving Role of the Teacher
With these tools in place, my role shifts from delivering direct instruction to orchestrating learning experiences. I am no longer the sole provider of knowledge; rather, I:
Design and curate instructional resources (videos, AI prompts, peer exemplars).
Facilitate meaningful student interactions (peer discussions, critique sessions, real-time scaffolding).
Adapt instructional strategies based on student progress and self-reflections.
Play a uniquely human role by interpreting student needs, recognizing struggles, and guiding them beyond what AI or pre-recorded materials can offer.
Implications for AI-Augmented Teaching
AI Enhances, Not Replaces, Human Facilitation
AI tools provide structured and responsive learning pathways but lack the adaptive, empathetic, and evaluative capabilities of human teachers.
The teacher remains irreplaceable in interpreting student progress and providing nuanced interventions.
Teachers as Orchestrators of Learning Agents
Instead of delivering repetitive instruction, teachers design ecosystems of instructional agents that students can navigate.
This approach aligns with AI-driven curriculum models, leveraging technology to optimize learning while preserving the essential human element of teaching.
Future Possibilities: AI-Generated Adaptive Scaffolds
Experimenting with AI-personalized feedback loops (e.g., guiding questions for students based on their self-reflections).
Exploring AI-assisted formative assessments that provide real-time suggestions for student design improvements.
Using AI to dynamically adjust task complexity based on student responses, ensuring both challenge and support.
Conclusion
The integration of instructional agents like YouTube and ChatGPT into the classroom marks a paradigm shift in teaching. Instead of being overburdened by direct instruction, teachers can now leverage technology to enhance self-directed learning, enabling students to take ownership of their educational journey. However, the human role remains crucial—AI may guide, but only teachers can truly inspire, interpret, and intervene effectively.
Moving forward, refining these approaches with AI-generated personalized scaffolding and adaptive learning interventions will further enhance student engagement, creativity, and problem-solving in design education. The balance between AI augmentation and human insight is where the true transformation in education lies.
Comments
Post a Comment