QLD Education GPT Suite

The catalyst was a simple problem: writing external exam practice questions for QCAA subjects is time-consuming and requires deep knowledge of the exam format, command verbs, and marking guide conventions. I built the first GPT for Digital Solutions because I needed it myself. When I shared it with teachers in other faculties, requests started coming in for other subjects.

Each subject-specific GPT is built around the actual QCAA syllabus documents, assessment objectives, and past exam structures. They generate technology-free and technology-active questions at the right difficulty, with sample marking guides that reflect how QCAA examiners award marks. Every tool includes a disclaimer that it is not endorsed by QCAA and is intended for practice, not prediction.

Beyond external exam prep, I built a set of general teaching workflow tools, including a Learning Intention and Success Criteria Bot and an Education Adjustment Suggester. The Education Adjustment Suggester is designed as a planning aid for classroom teachers. Give it a student's diagnosis or IEP information and it surfaces practical lesson adjustment ideas the teacher might not have considered. It is explicitly not a compliance tool. It is there to help teachers think through adjustments more thoroughly, not to generate documentation or make NCCD determinations. That distinction matters, and it is built into how the tool frames its outputs. It has been used 800+ times.

The Data Test series came after teachers in science faculties asked for something different. QCAA science subjects include internal data tests that many students find difficult to practise for. The Biology, Chemistry, and Physics Data Test GPTs fill that gap, generating stimulus-based questions with answers and justifications that mirror the internal assessment format.