Design of curricular evaluation instruments assisted by generative artificial intelligence
Keywords:
artificial intelligence, CIPP model, curriculum evaluation, measurement instruments, program evaluationAbstract
The use of generative artificial intelligence is having an increasingly significant impact on everyday life, ranging from simple tasks to highly complex processes. In this context, it is establishing itself as a valuable support tool for the design and validation of educational assessment instruments. The present study aims to design curriculum assessment instruments by applying the CIPP model, Messick’s modern psychometric-based instrument design theory, and the principles of prompting engineering, using generative artificial intelligence as a methodological support tool. The research is based on the Theory-Based Design and Development methodology. The results are presented in the form of tangible products, including: (a) a matrix of dimensions, criteria, and indicators derived from the CIPP model; (b) a definition of the assessment construct; and (c) the component-based prompting framework, which consists of three prompts. In conclusion, it is shown that the integration of the CIPP model, psychometric theory, and prompting engineering allows for the design of structured prompts that guide generative artificial intelligence to generate valid and coherent items, strengthening the quality and relevance of the design of curriculum assessment instruments
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