Designing a Multi-Agent Interactive Platform for Teacher Training: A TPACK-Aligned Model Integrating Intelligent Educational Agents

Abstract

This study introduces the design and development of a TPACK-based interactive digital platform embedded with intelligent educational agents aimed at preparing teacher trainees across TESL, Music, and Visual Arts programs for the demands of the digital era. Utilizing the Design and Development Research (DDR) framework, the platform leverages AI-driven tools such as generative chatbots (e.g., ChatGPT), immersive virtual environments (Spatial.io), and gamified assessment systems (e.g., Quizizz, Minecraft) to personalize instruction, automate feedback, and simulate collaborative teaching-learning scenarios. Data were collected from 150 teacher trainees and 7 expert lecturers using Fuzzy Delphi and usability testing methods. Results show improved pedagogical readiness (mean score = 4.5/5), high motivation (85% agreement), and expert consensus on platform design. This research contributes to the emerging domain of multi-agent ecosystems in education, presenting a replicable, scalable model that aligns with Malaysia’s digital education transformation goals and the ET&S Special Issue on intelligent agents in education.