Didactic design of prompts to assess learning: Integration of artificial intelligence in undergraduate training
Didactic design of prompts to assess learning: Integration of artificial intelligence in undergraduate training
Keywords:
design, student assessment, artificial intelligence, teacher trainingAbstract
In today's complex educational-technological context, language plays a crucial role in the interaction between people and machines, especially in the use of artificial intelligence. However, there is uncertainty and disagreement regarding the use of this digital technology and prompt designs for undergraduate learning assessment. This research focused on determining whether the use of artificial intelligence through the didactic design of prompts generates statistically significant differences in scores, obtained through a checklist, between a control and an experimental group. The results show a marked difference in scores, with higher passing grades in the experimental group, where the didactic design of prompts was implemented. The Mann-Whitney U test confirms these statistically significant differences, allowing us to conclude that the integration of artificial intelligence with active methodologies that involve students in the design and evaluation of prompts for problem-based learning substantially improves academic outcomes. This suggests that the combination of this technology can be an effective tool to enhance learning in higher education environments.
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