By Damon Rickett
At the International School of Belgrade, educators are exploring how AI can support teaching and learning through collaborative inquiry. Staff participate in Professional Learning Communities (PLCs), where groups of educators investigate emerging practices and innovations. One such PLC has been examining how AI can help teachers better understand student learning and improve instructional decision-making. In the early stages, teachers began using AI primarily as a thinking partner. Rather than relying on it for final answers, they experimented with structured prompting to explore ideas, challenge assumptions, and generate hypotheses about student learning.
A common framework used by the PLC included prompts that:
- Assign the AI a role (e.g., “Act as a literacy coach”)
- Define a task (“Your task is to analyze this data…”)
- Specify a response format (“Respond by creating a table that …)
- Provide supporting materials such as assessment data, curriculum documents, or student work samples
When combined with critical thinking and professional expertise, these conversations with AI helped educators surface new perspectives on familiar challenges. In one example, a team of teachers used AI-supported analysis to explore patterns in mathematics performance. Through iterative discussion with the AI model, the team developed a hypothesis: students were struggling not simply with procedures, but with the lack of a consistent schema—a mental framework—for approaching certain types of problems. The teachers responded by explicitly teaching and revisiting problem-solving schemas across units of instruction. Over time, they observed improved student confidence and performance when tackling complex tasks. Importantly, the AI did not provide the solution. Instead, it helped expand the educators’ thinking, prompting them to explore possibilities they might otherwise have overlooked.
Making Better Use of the Data Schools Already Have
Schools today are often rich in data but poor in time. Assessment data, progress monitoring tools, and digital learning platforms generate enormous amounts of information, yet educators rarely have the capacity to analyze it fully. Within the PLC at the International School of Belgrade, teachers began experimenting with LLMs to support data organization and instructional planning. By providing anonymized baseline and formative assessment data, teachers asked AI tools to:
- Identify patterns in student performance
- Suggest potential learning gaps
- Organize students into flexible small groups
- Propose targeted instructional strategies
Tasks that previously might have taken days—or even weeks—were completed in minutes. Teachers remained responsible for professional judgment and instructional decisions, but AI helped surface insights more quickly. In one example, teachers used AI to design differentiated word-study instruction. By prompting the model to act as a curriculum developer, educators generated small-group instructional plans tailored to specific student needs. These plans were then reviewed, modified, and implemented by the teachers themselves.
The Rise of Microapps in Education
Another emerging development is the creation of microapps—small, purpose-built AI tools designed to solve very specific problems. Rather than relying solely on large, general-purpose platforms, educators are beginning to develop lightweight tools that streamline everyday tasks. At the International School of Belgrade, teachers have begun experimenting with in-house microapps that support instructional planning and curriculum integration.
For example:
- One microapp supports integrating social–emotional learning (SEL) into physical education lessons by simulating a conversation among multiple AI “agents,” each representing a different educational perspective (e.g., PE teacher, SEL specialist, curriculum coordinator).
- Another microapp helps teachers generate guided reading texts that align with both the Science of Reading and reading behaviors.
These tools do not replace professional expertise. Instead, they act as catalysts for creativity, helping educators generate ideas and resources more efficiently.
From Artificial Intelligence to Intelligence Augmentation
A growing movement within the AI field emphasizes what some researchers call Humanistic AI—an approach that focuses on collaboration between humans and machines rather than replacement. This perspective is sometimes described as Intelligence Augmentation (IA): using computational tools to amplify human insight, creativity, and problem-solving capacity. Education may be uniquely positioned to benefit from this model. Teaching has always been a profession grounded in relationships, judgment, and ethical decision-making. AI can assist with analysis, organization, and idea generation—but the human educator remains central to the learning experience. For schools across the CEESA region, the most promising path forward may not be asking whether to use AI, but rather exploring how to use it thoughtfully, ethically, and creatively. Professional learning communities, collaborative experimentation, and reflective practice will likely play a key role in this journey. If early experiments are any indication, AI may not replace educators—but it may become one of the most powerful thinking partners they have ever had.
If you are interested in discussing AI implementation in your school, feel free to contact me at drickett@isb.rs.
Author’s note: No generative AI tools were used to write the original draft of this article. AI tools were used in the editorial revision process to fact-check and refine supporting information.