Event Information
ISTELive ContentThis research contributes to the growing body of research on human-AI collaboration, in this case contextualized to educators involved in curriculum vetting.
The paper adopts a mixed-methods research methodology that consists of the following main stages:
(1) developing a customised GPT vetter chatbot that is equipped with a set of vetting guidelines and pedagogical best practices;
(2) conducting focus group interviews with educators who were given access to the customized GPT, to collect their feedback and perceptions; and
(3) conducting a comparative analysis of the vetting outputs from both the human vetters and customized GPT vetter.
The paper reports the findings from the focus group interviews and comparative analysis, which indicate that a complementary partnership of a human expert augmented with an Artificial Intelligence (AI) vetting system could amplify the strengths of both, while mitigating their individual limitations.
By integrating AI and automating aspects of curriculum vetting, educators can focus more on instructional design, differentiation, and engaging pedagogical practices that directly impact student learning outcomes.
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