📄 social_science

Developing Pre-service Primary Teachers’ Creative Pedagogical Behaviours through STEAM Design-Based Learning in Viet Nam

This study demonstrates that a 15-week STEAM design-based learning course significantly enhances pre-service primary teachers' creative pedagogical behaviors in Vietnam by fostering a disciplined process of adapting STEAM ideas to local curriculum and classroom constraints, despite challenges in micro-teaching enactment and limited critical use of GenAI for reflection.

Original authors: Tuan Minh Dang

Published 2026-06-28

📖 6 min read🧠 Deep dive

CC BY 4.0

Original authors: Tuan Minh Dang

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The Big Picture: From "Cool Idea" to "Teachable Lesson"

Imagine you are a chef. You have a brilliant, fancy idea for a new dish: a "Galactic Spaghetti" that changes color when you eat it. It sounds amazing and creative, right? But if you try to serve this to a group of 7-year-olds in a school cafeteria, it might be a disaster. The sauce might be too spicy, the color-changing ingredient could be toxic, or the kids might just be too distracted by the color to actually eat their lunch.

This study is about training future primary school teachers (the chefs) to stop just dreaming up "Galactic Spaghetti" and start figuring out how to actually serve a delicious, safe, and educational meal to real children.

The researchers in Vietnam wanted to see if a 15-week course could help these future teachers turn creative ideas into creative teaching. They focused on STEAM (Science, Technology, Engineering, Arts, and Math) and used a new tool called Generative AI (like ChatGPT) to help them brainstorm.

The Experiment: A 15-Week "Design Gym"

The study took place at a university in Hanoi, Vietnam. They put 63 future teachers through a "design gym" for 15 weeks. Instead of just sitting in lectures, these students had to:

Brainstorm a STEAM project (like building a water filter or a smart trash bin).
Build a prototype of it.
Teach a short version of the lesson to their peers (called "microteaching").
Get feedback and redesign the lesson.
Use AI to help them come up with ideas along the way.

What They Found: The "Aha!" Moments

The researchers looked at the students' work, their lesson plans, and interviewed them to see how their "creative teaching muscles" grew. Here are the main takeaways, explained simply:

1. Creativity isn't just "Newness"; it's "Fit"

Before the course, the students thought creativity meant coming up with the wildest, most unique idea possible. By the end, they realized that true creative teaching is about adaptation.

The Analogy: It's like having a giant, heavy oak tree (a great idea) and realizing you need to fit it into a small, sunny window box (a primary classroom). The creativity isn't in the tree; it's in the skill of pruning the branches, changing the soil, and making sure the tree actually survives in that specific window.
The Result: The students got much better at "pruning" their ideas. They learned to simplify complex science concepts so a 6-year-old could understand them and to use materials that are actually available in Vietnamese schools.

2. The "Stress Test" (Microteaching)

The most important growth happened when the students tried to teach their lesson, even if just for a few minutes to their classmates.

The Analogy: Writing a lesson plan is like drawing a map of a treasure hunt. Microteaching is actually walking the path. You might think the path is clear on paper, but when you walk it, you realize there's a giant rock blocking the way or the map is confusing.
The Result: The students learned that their "maps" (lesson plans) often had holes in them. They realized they needed to change their timing, clarify their instructions, and make sure the "treasure" (the science lesson) was actually found by the "explorers" (the students). This ability to look at their own work, spot the problems, and fix them is called Reflective Pedagogical Agency. This was the area where they improved the most.

3. The AI Assistant vs. The Human Captain

The students used AI (Generative AI) heavily, but not in the way you might expect.

The Analogy: Think of AI as a very fast, very knowledgeable travel agent. It can instantly suggest 50 different vacation spots and write a perfect itinerary. However, if you let the travel agent drive the car, you might end up in a swamp because they don't know the road conditions.
The Result: The students used AI mostly at the beginning to brainstorm ideas and list materials. But they rarely used it to critique their own work or check if the lesson was actually safe and age-appropriate. They learned that they had to be the Captain. They used the AI's suggestions as raw ingredients, but they had to cook the meal themselves, tasting it to make sure it wasn't too salty or too spicy for the kids.
Key Finding: The more students relied on AI to do the thinking for them, the less their own creative teaching skills grew. The magic happened when they used AI to expand their options, then used their own human judgment to pick and refine the best one.

4. The "Product" vs. The "Process"

The Result: The final projects (the water filters, the bridges) were actually quite good and feasible for real classrooms. However, the students were still a bit shaky on how to teach the lesson around the product. They were great at building the "toy," but sometimes forgot to explain the "science" behind it clearly.
The Lesson: A cool science project is only useful if the teacher can guide the students to ask "Why does this work?" rather than just "Look at this cool thing."

The Bottom Line

This study tells us that teaching future teachers to be creative isn't about telling them to "be more imaginative." It's about giving them a disciplined process:

Have an idea.
Try to teach it.
Realize where it fails.
Fix it based on the reality of the classroom.

It also warns us that while AI is a fantastic tool for generating ideas, it cannot replace the teacher's brain. The teacher must be the one to decide if an idea is safe, fair, and actually educational for a specific group of children.

In short: The future teachers learned that being a "creative teacher" doesn't mean having the flashiest idea; it means having the skill to take a good idea and mold it until it fits perfectly into the messy, real world of a primary school classroom.

Technical Summary: Developing Pre-service Primary Teachers' Creative Pedagogical Behaviours through STEAM Design-Based Learning in Viet Nam

Problem Statement
While STEAM (Science, Technology, Engineering, Arts, and Mathematics) projects are frequently described as creative, there is limited empirical understanding of how pre-service primary teachers learn to translate these creative concepts into pedagogically accountable lesson designs. A critical gap exists in distinguishing between the generation of novel ideas and the disciplined process of adapting those ideas to meet curriculum objectives, learner needs, material constraints, and classroom feasibility. Furthermore, the integration of Generative Artificial Intelligence (GenAI) into this design process adds complexity; while GenAI can assist in ideation, it risks obscuring the necessity of human pedagogical judgment. In the context of Viet Nam, where national curriculum reforms emphasize competency-based and integrated learning, there is a lack of evidence regarding how pre-service teachers cultivate creative pedagogical behaviors when designing STEAM lessons and utilizing GenAI.

Methodology
The study employed an embedded mixed-methods case study design involving 63 pre-service primary teachers enrolled in a 15-week university course titled "STEAM educational projects in primary education" at Vietnam National University, Hanoi. The course followed a design-based learning trajectory, moving from concept formation to lesson planning, prototype construction, microteaching, feedback, and redesign.

Data collection included:

Quantitative: A retrospective pre–post survey measuring Creative Pedagogical Behaviors (CPB) across four dimensions: idea generation, deepening/refining ideas, openness to exploration, and reflective pedagogical agency.
Artefact Analysis: 18 group lesson plans and STEAM artefacts were scored by two university lecturers using a seven-criterion rubric (e.g., STEAM integration, feasibility, microteaching enactment).
Qualitative: Open-ended survey responses and semi-structured interviews with 15 purposively selected students.
GenAI Usage: Self-reported data on the frequency and purpose of GenAI use during the design process.

Analysis involved paired t-tests for survey data, descriptive statistics for rubric scores, and a deductive-inductive thematic analysis for qualitative data. The study explicitly avoided causal claims, framing findings as reported developments and associated patterns.

Key Results

Development of Creative Pedagogical Behaviors: Participants reported a statistically significant increase in overall CPB ( $t(34) = 5.58, p = 0.000$ ), with the most substantial growth observed in reflective pedagogical agency (gain = 0.24, $p < .001$ ). This indicates a shift toward the ability to assess design decisions and revise them based on evidence.
Artefact Quality vs. Enactment: Rubric scores indicated that the majority of projects were at a "proficient" level (Mean = 3.16/4). The strongest criteria were STEAM integration and feasibility in Vietnamese classrooms. Conversely, microteaching enactment and reflection/redesign scores were lower, suggesting that while students could design viable concepts, the practical execution and iterative refinement of teaching strategies were less developed.
GenAI Utilization Patterns: GenAI was widely used (98.4% of respondents), primarily for ideation (79.4%), connecting STEAM components (69.8%), and revising objectives (66.7%). However, its use for critical review, checking ideas, or post-microteaching reflection was significantly lower (15.9–25.4%). A negative correlation was found between the frequency of GenAI use and CPB gain ( $r = -0.35$ ), suggesting that heavy reliance on AI without critical adaptation may not correlate with pedagogical growth.
Qualitative Insights: Interviews revealed that students viewed creativity not as the production of novel artifacts, but as a process of disciplined adaptation. Students described reducing complex technical ideas to age-appropriate tasks, localizing materials, and using microteaching as a "stress test" to identify flaws in timing, instructions, and engagement. They distinguished between using GenAI as a tool for expanding the idea space versus substituting their own professional judgment.

Key Contributions

Reconceptualizing Creativity: The study operationalizes creative pedagogy not as a personality trait or the novelty of a product, but as an observable, teachable behavior involving the adaptation of ideas to constraints (curriculum, materials, time) and the justification of design choices.
STEAM Teacher Education: It demonstrates that STEAM design-based learning serves as a professional learning environment where pre-service teachers transition from "appealing product ideas" to "pedagogically valid science learning experiences."
GenAI in Design: The findings challenge the assumption that increased AI usage automatically enhances creativity. Instead, they highlight that the pedagogical value of GenAI depends on the user's capacity for critical evaluation, localization, and the maintenance of human agency in the design loop.
Methodological Integration: The study combines self-report, moderated rubric scoring, and qualitative interviews to provide a triangulated view of teacher learning, preventing the reduction of creativity to either survey scores or showcase products.

Significance and Claims
The paper claims that the study provides empirical evidence for the importance of disciplined pedagogical adaptation in teacher education. It argues that for pre-service teachers to effectively implement STEAM, they must learn to navigate the tension between innovative design and classroom feasibility. The study posits that microteaching is essential not merely as a performance assessment but as a design test that reveals hidden pedagogical issues.

Regarding GenAI, the study claims that while AI can expand the design space and facilitate the linking of STEAM components, it cannot replace the teacher's role in validating, contextualizing, and ethically adapting content. The significance lies in demonstrating that creative pedagogy is a learned professional judgment developed through cycles of design, enactment, feedback, and redesign, rather than a static disposition. The authors caution against overclaiming causality due to the single-cohort, retrospective design but assert that the findings offer a robust framework for understanding how pre-service teachers develop the capacity to make STEAM ideas teachable in real-world contexts.