Effect of the Use of AI-Assisted Scaffolding on Students’ Predicting Skills in Acid-Base Practical Work

Low science process skills among students, particularly in the predicting aspect, indicate that many students still experience difficulties in anticipating experimental outcomes based on scientific concepts and evidence. This study aimed to examine the implementation of Artificial Intelligence (AI)-assisted cueing scaffolding techniques and investigate their effect on students' predicting ability in deep learning through acid-base laboratory activities at SMA Negeri 13 Kota Jambi. The study employed a mixed-methods approach using a Sequential Explanatory design, with the quantitative phase adopting an Only Posttest Control Group Design. The research sample consisted of two classes: an experimental class receiving guided inquiry learning integrated with AI-assisted cueing scaffolding, and a control class receiving guided inquiry learning with direct teacher guidance. Data were collected using science process skills observation sheets focusing on the predicting indicator and essay tests, and were analyzed using the Mann–Whitney test. The findings revealed that AI-assisted cueing scaffolding was successfully implemented across three learning sessions following the guided inquiry stages. Students in the experimental class demonstrated a gradual improvement in predicting ability and achieved higher average scores than those in the control class. Statistical analysis showed an Asymp. Sig. (2-tailed) value of < 0.001, indicating a significant difference between the two groups. The novelty of this study lies in integrating AI-assisted cueing scaffolding into deep learning-based guided inquiry during acid-base laboratory activities to enhance students' predicting skills. It can be concluded that AI-assisted cueing scaffolding is effective in improving students' ability to predict, an essential component of science process skills. These findings provide an innovative instructional alternative for chemistry learning and may serve as a reference for integrating AI-based scaffolding strategies into other science topics to strengthen students' higher-order thinking and scientific reasoning.