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The Effect of Guided Inquiry Model with Deep Learning Approach on Student’s HOTS in Elements, Compounds, and Mixtures at Junior High School

Friska Pakpahana, Retno Dwi Suyanti

Abstract


The current education curriculum places a strong emphasis on developing HOTS skills (such as analyzing, evaluating, and creating) to prepare students for the challenges of the 21st century. School learning often focuses on lower-level cognitive domains (memorizing and understanding). This research seeks to address this gap by offering a potentially effective learning model. The guided inquiry model positions students as active participants in learning, encouraging them to investigate, discover, and formulate concepts independently with teacher guidance. This strongly supports the development of critical thinking and problem-solving skills. Therefore, this study aims to analyze the effect of the guided inquiry model combined with a deep learning approach on students' higher-order thinking skills (HOTS) regarding the topics of elements, compounds, and mixtures, as well as the extent of cognitive improvement in each aspect of HOTS. This research is quasi-experimental research that consisted of two classes, namely the experimental class and the control class. The sampling technique used was purposive sampling. The hypothesis test significance result was < 0.05, so that Hₐ was accepted and H₀ was rejected. Thus, the guided inquiry model with a deep learning approach had a significant effect on increasing students' HOTS in the material of elements, compounds, and mixtures compared to conventional learning. The most developed HOTS cognitive aspect in the experimental class was C4 at 61%.

Keywords


Guided Inquiry Model; Deep Learning Approach; HOTS; Conventional Model

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References


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DOI: http://dx.doi.org/10.17977/jps.v13i32025p210